WO2010029932A1 - Visual examination apparatus - Google Patents

Visual examination apparatus Download PDF

Info

Publication number
WO2010029932A1
WO2010029932A1 PCT/JP2009/065711 JP2009065711W WO2010029932A1 WO 2010029932 A1 WO2010029932 A1 WO 2010029932A1 JP 2009065711 W JP2009065711 W JP 2009065711W WO 2010029932 A1 WO2010029932 A1 WO 2010029932A1
Authority
WO
WIPO (PCT)
Prior art keywords
rgb
luminance
inspection
pixel
coordinate system
Prior art date
Application number
PCT/JP2009/065711
Other languages
French (fr)
Japanese (ja)
Inventor
昌年 笹井
Original Assignee
株式会社メガトレード
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 株式会社メガトレード filed Critical 株式会社メガトレード
Priority to CN200980134031.3A priority Critical patent/CN102138068B/en
Priority to JP2010528728A priority patent/JP5084911B2/en
Publication of WO2010029932A1 publication Critical patent/WO2010029932A1/en

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N21/956—Inspecting patterns on the surface of objects
    • G01N21/95607—Inspecting patterns on the surface of objects using a comparative method
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/46—Measurement of colour; Colour measuring devices, e.g. colorimeters
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/46—Measurement of colour; Colour measuring devices, e.g. colorimeters
    • G01J3/463—Colour matching
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
    • G01J5/0096—Radiation pyrometry, e.g. infrared or optical thermometry for measuring wires, electrical contacts or electronic systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N2021/9513—Liquid crystal panels
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N21/956—Inspecting patterns on the surface of objects
    • G01N2021/95638—Inspecting patterns on the surface of objects for PCB's
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N21/9501—Semiconductor wafers

Definitions

  • the present invention relates to an appearance inspection apparatus that acquires a color image from an inspection object and inspects the quality of the inspection object and an inspection method thereof, and more specifically, RGB luminance data of a color image is appropriately obtained.
  • the present invention relates to an appearance inspection apparatus which can be inspected with high accuracy by setting a value.
  • the formation state of printed circuit boards, semiconductor wafers, liquid crystal substrates, etc. is inspected by an appearance inspection apparatus.
  • an image of the surface is acquired by a camera, and the quality of the inspection object is inspected from the acquired image.
  • a color image is acquired from an inspection object, and inspection is performed based on RGB information of the color image (Patent Documents 1 to 3, etc.). .
  • Patent Document 4 JP 2007-101415 A JP 2006-78301 A JP 2006-78300 A JP 2007-309703 A
  • the threshold luminance width is set to a large value such as 20 ⁇ R ( ⁇ x) ⁇ 40, 120 ⁇ G ( ⁇ y) ⁇ 200, 60 ⁇ B ( ⁇ z) ⁇ 150. (See FIG. 9).
  • the threshold luminance width is set to be large in this way, there is a possibility that a portion that should be determined as defective cannot be determined as defective.
  • a portion that should be determined as defective cannot be determined as defective.
  • the luminance width of the reference luminance data is increased, the rectangular parallelepiped area in FIG. 9 is increased, and the luminance value of the exposed portion is included in the luminance width of the reference luminance data and can be determined as defective. Disappear.
  • the threshold value is narrowed so that the exposed portion can be determined as defective, a non-defective product is determined as a defective product, and the subsequent visual inspection takes time.
  • An object of the present invention is to provide an appearance inspection apparatus which can be set to an optimum value and improve the quality of inspection.
  • the present invention obtains a color image from an inspection object in an appearance inspection apparatus that inspects the formation state of the inspection object on the basis of an image acquired from the inspection object.
  • RGB information acquisition means for acquiring RGB luminance data in the inspection portion of the object
  • reference data storage means for storing RGB reference luminance data of each inspection portion in the RGB polar coordinate system with the axial direction as the luminance value
  • the RGB information acquisition Conversion means for converting the RGB luminance data of each inspection part acquired from the means into luminance data of the polar coordinate system, and the RGB reference in the RGB polar coordinate system stored in the reference data storage means and the converted luminance data of the polar coordinate system Compared with the luminance data, depending on whether or not the RGB reference luminance data includes the RGB luminance data of the inspection object. It is obtained so as to provide a judging means for judging quality of ⁇ zone.
  • the overall luminance is maintained while maintaining the RGB luminance ratio (color shade). Only a large value can be set, so that variations in luminance can be absorbed and inspection can be performed with high accuracy.
  • a conversion table for converting the luminance data of the RGB orthogonal coordinate system acquired from the inspection object into the RGB polar coordinate system is stored, and each of the acquired inspection regions is obtained with reference to the conversion table. Convert RGB coordinates.
  • RGB luminance data of a predetermined number of pixels adjacent to the reference inspection object is included.
  • RGB luminance is converted into polar coordinate luminance
  • the luminance value is compressed or expanded so as to fit in one byte.
  • the luminance value of RGB falls within the range of 1 byte of “0 to 255”, but when this is converted into the polar coordinate system, the angle ( ⁇ , ⁇ ) from the axial direction is from 0.
  • the distance (L) from the origin falls within the range of 0 to 255 ⁇ 3 (1/2) and exceeds 1 byte. Therefore, the angle from the axial direction is (255 ⁇ 4 / ⁇ ) times, and the distance from the origin is reduced to 1/3 (1/2) times. In this way, data can be compressed within a range of 1 byte.
  • a color image is acquired from the inspection object, and the RGB luminance in the inspection portion of the inspection object RGB information acquisition means for acquiring data, reference data storage means for storing RGB reference luminance data of each inspection part in an RGB polar coordinate system with the axial direction as a luminance value, and each inspection part acquired from the RGB information acquisition means Converting the RGB luminance data of the RGB coordinate data into luminance data of the polar coordinate system, comparing the converted luminance data of the polar coordinate system with the RGB reference luminance data in the RGB polar coordinate system stored in the reference data storage unit, The quality of the inspection area is determined based on whether or not the RGB reference luminance data includes the RGB luminance data of the inspection object. Since the RGB luminance values in the acquired inspection area vary greatly from product to product, only the overall luminance is increased while maintaining the RGB luminance ratio (color shade). Therefore, it is possible to absorb the variation in luminance and to inspect with high accuracy.
  • FIG. 1 shows an outline of the appearance inspection process in the present embodiment
  • FIG. 2 shows a functional block diagram of the appearance inspection apparatus 1.
  • FIG. 3 shows RGB luminance reference data used in the appearance inspection apparatus 1.
  • the appearance inspection apparatus 1 in this embodiment can inspect a printed circuit board, a semiconductor wafer, other cracks generated in an article, a state printed on the surface of the article, and the like.
  • an example is given. The case where the formation state of the printed circuit board is inspected will be described.
  • the appearance inspection apparatus 1 is acquired by the imaging means 2 that acquires a surface image from the inspection object 11 and the imaging means 2, as in a general appearance inspection apparatus.
  • RGB information processing means for obtaining RGB information of each pixel from the obtained image
  • correction processing means 6 for aligning the image of the inspection object 11 and the image that is the reference data, and the inspection object subjected to the alignment correction in this way
  • determining means 8 for determining the quality of the pixel using the RGB luminance data of each pixel of the object 11.
  • the conversion means 7 for converting the RGB luminance data of each image acquired from the inspection object 11 into the RGB luminance data of the polar coordinate system, and the converted RGB luminance data and stored in the storage means 5 in advance. This is compared with the RGB luminance reference data of the polar coordinate system, and the quality of each pixel is judged, and the result can be outputted via the output means 9.
  • a specific configuration of the appearance inspection apparatus 1 will be described in detail.
  • the imaging means 2 acquires the surface image from the reference object 10 and the inspection object 11 necessary for the inspection, and acquires the surface image by color.
  • This imaging means 2 irradiates light from an oblique direction, and acquires the reflected light by the CCD camera or the like above it.
  • images are acquired using different angles, different colors, and brightness with respect to the reference object 10 and the inspection object 11, and the acquired images are selected and used.
  • the reference object 10 generates reference data as a reference when the inspection object 11 is inspected.
  • the reference object 10 that has been determined to be non-defective by visual inspection or other inspection devices is generally used. To do.
  • the reference data generation means 4 acquires a surface image from a reference object 10 prepared in advance, and generates reference data from the image of the reference object 10.
  • the generated reference data includes data relating to the entire shape of the reference object 10, data relating to a plurality of rectangular areas inside the reference object 10, data relating to each pixel, and the like.
  • data relating to the overall shape includes data relating to the length and width of the printed circuit board
  • data relating to the rectangular area includes data such as pattern images in the rectangular area
  • data relating to each pixel includes data relating to each pixel.
  • Data such as RGB luminance, allowable luminance width, and search distance are used.
  • the “allowable luminance width” indicates the RGB luminance width in a pixel that is determined to be good or bad.
  • a portion having a large luminance change such as a silk edge, a pad edge, or a wiring pattern edge.
  • the “search distance” indicates a distance for searching whether or not there is a pixel corresponding to the reference object 10 with a predetermined pixel position as the center. For example, a silk edge, a pad
  • the search distance is set to a large value such as 3 to 5 pixels for a portion where the luminance change is large such as the edge of the wiring pattern or the edge of the wiring pattern.
  • the allowable luminance width expressed in polar coordinates is ⁇ ⁇ , ⁇ ⁇ , ⁇ ⁇ L are set, and the search distance is set to 3 pixels or the like.
  • the allowable luminance width and the search distance are not limited to these values, and may be set manually.
  • FIG. 3 shows reference data used when determining the quality of each pixel.
  • the luminance values of RGB are set on the respective axes, and the luminance values are set to increase in the direction of the arrows.
  • the RGB hue slightly changes depending on the resist unevenness of the inspection object 11, the change of the lot, and the color composition.
  • the luminance width of the RGB luminance reference data is set to be large as described above, most pixels are included in the range of the reference data. Anything that can be seen is included in the range of the reference data and judged as “good”.
  • the RGB luminance values of the pixels adjacent to the pixel are set to be included. Then, the RGB luminance reference data set in this way is stored in the storage means 5.
  • the correction processing unit 6 performs correction processing for making the image of the inspection object 11 imaged by the imaging unit 2 substantially coincide with the image of the reference object 10.
  • An example of the correction of the entire image in this correction processing is shown in FIG. In FIG. 4, a solid line portion shaded with diagonal lines indicates the reference object 10, and a broken line indicates the inspection object 11.
  • FIG. 4A when the inspection object 11 is smaller than the reference object 10 (FIG. 4A), correction processing is performed to enlarge the entire shape by ⁇ x and ⁇ y .
  • the inspection object 11 is rotated by also [delta] theta than reference object 10 performs correction processing as rotated by that angle.
  • FIG. 5A shows an example of a rectangular area where the reference object 10 is located
  • FIG. 5B shows a rectangular area at the same position of the inspection object 11.
  • the pad or wiring pattern of the inspection object 11 may be displaced in a predetermined direction from the pad or wiring pattern of the reference object 10.
  • a parallel movement correction process is performed so that the image in the rectangular area of the inspection object 11 substantially matches the reference object 10.
  • the RGB information acquisition means 3 acquires RGB luminance data of each pixel from the image of the inspection object 11 that has been corrected in this way.
  • the converted coordinates are converted into coordinates in the RGB polar coordinate system using the conversion means 7.
  • the values (x, y, z) of the orthogonal coordinate system are previously set to the values of the polar coordinate system ( ⁇ , ⁇ , L), a conversion table to be converted is prepared, and converted to RGB luminance data of the polar coordinate system with reference to this conversion table.
  • the relationship between orthogonal coordinates and polar coordinates is as follows.
  • x is the luminance value of R in the Cartesian coordinate system
  • y is the luminance value of G in the Cartesian coordinate system
  • z is the luminance value of B in the Cartesian coordinate system
  • ⁇ is the angle made with the x axis in the polar coordinate system
  • ⁇ is the polar coordinate
  • the angle L formed with the z-axis in the system indicates the overall luminance value in the polar coordinate system.
  • the determination means 8 determines whether or not the inspection object 11 has a pixel corresponding to each pixel of the reference object 10, and the first pixel determination means 81 and the second pixel as described below.
  • a pixel determination unit 80 including a determination unit 82 and a cluster determination unit 83 are provided.
  • the first pixel determination unit 81 specifies the position of the inspection object 11 corresponding to each pixel of the reference object 10 with the reference object 10 as a reference, and within a search distance centered on this position. Then, it is determined whether or not there is a pixel within an allowable luminance width with respect to the luminance of the pixel. In this determination, if even one pixel within the allowable luminance width of the RGB luminance reference data exists within the search distance, it is determined as “good pixel”, and conversely, a pixel within the allowable luminance width within the search distance. Is not determined at all, it is determined as “defective pixel”.
  • the correction processing means 6 can completely match the reference object 10 and the inspection object 11, the pixel at the position of the inspection object 11 corresponding to the pixel position of the reference object 10 may be inspected.
  • the resolution is increased, there is a possibility that the shift is about several pixels. For this reason, if there is an almost identical luminance within the search distance, it is determined as “good pixel” as a primary determination.
  • the determination result by the first pixel determination unit 81 is visually displayed on a display device or the like. For example, in the portion determined as “defective pixel”, an “x” mark or the like is displayed on the image of the reference object 10. Indicates.
  • the second pixel determination means 82 uses the inspection object 11 as a reference, and within the search distance centered on the position of the reference object 10, the allowable luminance width for the luminance of the pixel of the inspection object 11 It is determined whether or not there is a pixel inside. Also in this determination, if there is even one pixel within the allowable luminance width within the search distance, it is determined as “good pixel”, and conversely, there is no pixel within the allowable luminance width within the search distance. Is determined as “defective pixel”. When the comparison process is performed using the inspection object 11 as a reference, an image of the inspection object 11 after the above correction process is used.
  • the position of the reference object 10 corresponding to the position (the center position of the first search distance) of the inspection object 11 after the correction processing is specified, and the allowable luminance width / search distance at the position is stored. It is read out from the means 5 and it is determined whether or not a pixel within the allowable luminance width with respect to the luminance at the position of the inspection object 11 exists on the reference object 10 within the search distance.
  • the first search distance and the second search distance match, and the first allowable luminance width and the second allowable luminance width match.
  • the correction processing means 6 can completely match the reference object 10 and the inspection object 11, the pixel at the position of the inspection object 11 corresponding to the pixel position of the reference object 10 may be inspected.
  • the resolution is increased, there is a possibility that the shift is about several pixels.
  • the second determination result is visually displayed on the display device, overwritten on the determination image by the first pixel determination unit 81, and determined as a “defective pixel”. An “x” mark or the like is shown in the part.
  • the pixel determination unit 80 determines that there is at least one pixel within the allowable luminance width within the search distance of the inspection object 11, and within the allowable luminance width within the search distance of the reference object 10. On the condition that at least one pixel exists, the pixel existing at the position of the reference object 10 is determined as a good pixel. Conversely, when there is no pixel within the allowable luminance width within the search distance of the inspection object 11, or when there are no pixels within the allowable luminance width within the search distance of the reference object 10, A pixel present at the position of the reference object 10 is determined as a defective pixel.
  • the cluster determining means 83 determines whether or not the inspection object 11 is a defective product as a whole. judge. This pass / fail determination is determined to be a defective product when there are a predetermined number or more of adjacent pixels determined to be “defective pixels”.
  • the output unit 9 outputs the determination result by the cluster determination unit 83 in a reportable manner. At this time, since it is necessary to inform the user which part is a defective cluster, the position of the cluster determined to be a defective cluster by the cluster determination means 83 is visually output to the display device.
  • FIG. 7 shows a flowchart for generating reference data when inspecting the inspection object 11.
  • each image is acquired from a plurality of reference objects 10 prepared in advance (step S1).
  • the data relating to the entire area, the data relating to the rectangular area, and the data relating to the pixels are generated for each reference object 10 (step S2).
  • an average value of data relating to the entire area, an average value of data relating to the rectangular area, an average value of RGB data relating to pixels, and a standard deviation value are calculated (step S3).
  • the upper limit value of the allowable luminance width and the upper limit value of the search distance are manually input (step S4). This input is not performed at this stage, but may be performed in advance before step S1.
  • step S3 After the calculation of the average value and the standard deviation value in step S3, for the pixels having a large standard deviation value, the upper limit value of the allowable luminance width and the upper limit value of the search distance that are input previously are set, For pixels having a small standard deviation value, the allowable luminance width and the search distance are set to be small (step S5). Then, RGB luminance reference data is generated with RGB polar coordinates for each pixel and stored in the storage means 5 (step S6).
  • step T1 when inspecting the inspection object 11, the surface image is acquired from the inspection object 11 (step T1). This captured image may be misaligned depending on the image acquisition method, and may be different from the state of the image of the reference object 10 stored in the storage unit 5. Therefore, correction processing is performed to make the image states substantially coincide (step T2).
  • step T2 the entire shape is corrected. Specifically, three corner points on the inspection object 11 are extracted, and the vertical and horizontal lengths, rotation angles, parallel movement distances, and the like of the inspection object 11 are calculated from the three points. Then, based on these vertical and horizontal lengths, rotation angles, parallel movement distances, etc., correction processing is performed so that the entire image of the inspection object 11 substantially matches the entire image of the reference data.
  • the rectangular area is corrected.
  • the image of the inspection object 11 is translated so that the image of the predetermined rectangular area of the reference object 10 and the image of the corresponding rectangular area of the inspection object 11 substantially coincide. .
  • step T3 the position, RGB luminance, allowable luminance width, and search distance for each pixel of the reference object 10 are read from the storage means 5 (step T3). Then, the position of the inspection object 11 corresponding to the read pixel is specified, and within the RGB luminance reference data (allowable luminance width) set in the RGB polar coordinate system within the search distance with the position as the center. It is determined whether or not there is a pixel (step T4).
  • the RGB luminance data of the pixel read from the inspection object 11 is converted into the polar coordinate system with reference to the conversion table, and the RGB luminance data in the polar coordinate system is converted. And compare.
  • the first pixel determining unit 81 determines that no pixel within the allowable luminance width exists within the search distance, the pixel at the position of the reference object 10 is determined as a “defective pixel”. (Step T8).
  • the position of the reference object 10 corresponding to the position of the inspection object 11 is determined based on the image of the inspection object 11 after the correction process. It is determined whether or not there is a pixel within the RGB luminance reference data (allowable luminance width) set by the RGB polar coordinates within the search distance as the center. However, since each pixel of the inspection object 11 does not store data such as an allowable luminance width and a search distance, the allowable luminance width and the search of the position of the reference object 10 corresponding to the position of the inspection object 11 are stored. Use distance.
  • an allowable luminance width and a search distance of the position of the reference object 10 corresponding to the position of the inspection object 11 are read (step T5). Then, based on the read allowable luminance width and the search distance, the tolerance for the RGB luminance data of the inspection object 11 expressed in the polar coordinate system within the search distance with the position of the corresponding reference object 10 as the center. It is determined whether or not there is a pixel within the luminance width (step T6). At this time, the determination is made by converting the RGB luminance data acquired from the inspection object 11 into the RGB luminance data of the polar coordinate system using the conversion table. If it is determined by the second pixel determining means 82 that there is no luminance pixel within the allowable luminance width within the search distance, the pixel at the position of the reference object 10 is determined as a “defective pixel”. (Step T8).
  • step T4 if it is determined as “good pixel” in step T4 and “good pixel” is determined in step T6, the pixel corresponding to the position of the reference object 10 is determined as “good pixel” (step T7). .
  • step T9 If all the pixels have been inspected (step T9; Yes), the number of adjacent defective pixels among the pixels of the reference object 10 determined as “defective pixels” by the pixel determination unit 80 is then determined.
  • the inspection object 11 When there are more than a predetermined number of defective pixels (step T10), the inspection object 11 outputs that it is a defective product (step T11), while the number of all adjacent defective pixels Is less than the predetermined number, an output indicating that the product is non-defective is output (step T12).
  • a color image is acquired from the inspection object 11.
  • RGB information acquisition means 3 for acquiring RGB luminance data in the inspection portion of the inspection object 11, storage means 5 for storing RGB reference luminance data of each inspection portion in the RGB polar coordinate system with the axial direction as the luminance value,
  • the RGB luminance data of each inspection part acquired from the RGB information acquisition unit 3 is compared with the RGB reference luminance data in the RGB polar coordinate system stored in the storage unit 5, and the inspection object 11 is included in the RGB reference luminance data. Since the determination means 8 for determining whether the inspection area is good or not is provided depending on whether or not the RGB luminance data is included. Even if the RGB luminance values in the inspection area vary greatly from product to product, only the luminance can be set large while maintaining the RGB balance, and the luminance variation can be absorbed and high quality inspection can be performed. become able to.
  • a conversion table for converting the luminance data of the RGB orthogonal coordinate system acquired from the inspection object 11 into the RGB polar coordinate system is stored, and the RGB coordinates of each acquired inspection area are converted using this conversion table. Since each pixel is inspected, it is not necessary to perform an operation for coordinate conversion, and the processing speed at the time of inspection can be increased.
  • the RGB luminance data of a predetermined number of pixels adjacent to the reference inspection object 11 is included, so that the reference data and the inspection object 11 are aligned in pixel units. It can be inspected without it, and it can be inspected with fewer false alarms.
  • the luminance value is compressed or expanded to fit within 1 byte, so the converted luminance value is stored within the 1-byte range. Can be compressed.
  • the correction processing unit 6 is used to correct the image of the inspection object 11, but the image of the reference object 10 may be corrected. Alternatively, such a correction process may not be performed when complete alignment is possible.
  • a conversion table for converting to polar coordinates is prepared in advance, and the conversion table is referred to convert from the orthogonal coordinate system to the polar coordinate system.
  • coordinate conversion is performed for each pixel. You may make it calculate.
  • the present invention can also be applied to an inspection object 11 that requires an appearance inspection other than this.
  • each pixel is inspected, but RGB luminance data may be collected and inspected for each predetermined area.
  • one RGB luminance data is calculated for each region, and the calculation result is compared with the RGB reference luminance data expressed in the polar coordinate system.
  • ⁇ and ⁇ are expanded to 255 ⁇ 2 / ⁇ times. However, since they are within the range of 1 byte, the luminance value may be used as it is.
  • the maximum value is set to 255.
  • this is a value of 2 gradation bits raised to ⁇ 1, and this value can be used depending on the gradation bits. it can.
  • summary of the inspection processing method in one embodiment of this invention Functional block diagram of an appearance inspection apparatus in the same form
  • generation flow of the reference data in the form The figure which shows the flow of the inspection process in the same form

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Immunology (AREA)
  • Engineering & Computer Science (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Pathology (AREA)
  • Analytical Chemistry (AREA)
  • Health & Medical Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)

Abstract

In a case where a color image is used to examine the formation state of an object to be examined, the examination quality can be improved by establishing optimum values as examination threshold values for acquired RGB information of the color image.  A visual examination apparatus (1) for examining an object (11) comprises an RGB information acquiring means (3) that acquires a color image from the object (11) to acquire RGB intensity data of examined portions of the object (11); a storing means (5) that stores therein RGB reference intensity data of the examined portions in an RGB polar coordinate system the axes of which indicate the respective intensity values; and a determining means (8) that compares the RGB intensity data of the examined portions acquired by the RGB information acquiring means (3) with the RGB reference intensity data of the RGB polar coordinate system stored in the storing means (5) to determine whether the RGB intensity data of the object (11) is included in the RGB reference intensity data, thereby determining the quality of the examined areas.

Description

外観検査装置Appearance inspection device
　本発明は、検査対象物からカラー画像を取得して、その検査対象物の良否を検査する外観検査装置およびその検査方法に関するものであり、より詳しくは、カラー画像のＲＧＢの輝度データを適正な値に設定することで高精度に検査できるようにした外観検査装置に関するものである。 The present invention relates to an appearance inspection apparatus that acquires a color image from an inspection object and inspects the quality of the inspection object and an inspection method thereof, and more specifically, RGB luminance data of a color image is appropriately obtained. The present invention relates to an appearance inspection apparatus which can be inspected with high accuracy by setting a value.
　一般に、プリント基板や半導体ウエハ、液晶基板などは、外観検査装置によってその形成状態が検査される。このような外観検査装置によって検査対象物を検査する場合、一般的には、カメラによってその表面の画像を取得し、その取得された画像から検査対象物の良否を検査する。特に、近年では、このような検査を行うに際して、検査対象物からカラー画像を取得して、そのカラー画像のＲＧＢ情報に基づいて検査を行うようにしている（特許文献１～特許文献３など）。 Generally, the formation state of printed circuit boards, semiconductor wafers, liquid crystal substrates, etc. is inspected by an appearance inspection apparatus. When inspecting an inspection object by such an appearance inspection apparatus, generally, an image of the surface is acquired by a camera, and the quality of the inspection object is inspected from the acquired image. In particular, in recent years, when performing such inspection, a color image is acquired from an inspection object, and inspection is performed based on RGB information of the color image (Patent Documents 1 to 3, etc.). .
　このような外観検査装置において、プリント基板を検査する場合の一例について説明すると、まず、プリント基板を検査する場合は、プリント基板からその表面に形成されたパッドや配線パターン、レジスト、シルクなどの画像を取得する。そして、検査対象物の画像と基準画像とを位置合わせした後、検査対象物のある座標位置に存在する画素に対応する基準画像の画素を見つけ出し、その見つけ出された基準画素の許容輝度幅内に検査対象物の画素の輝度値が入っていれば、その画素を優良画素であると判断する。また、逆に、許容輝度幅内に入っていなければ不良画素であると判断し、所定数以上の不良画素が隣接して存在している場合に、そのプリント基板を不良品であると判断する（特許文献４）。
特開２００７－１０１４１５号公報 特開２００６－７８３０１号公報 特開２００６－７８３００号公報 特開２００７－３０９７０３号公報 In such an appearance inspection apparatus, an example of inspecting a printed circuit board will be described. First, when inspecting a printed circuit board, images of pads, wiring patterns, resists, silk, etc. formed on the surface from the printed circuit board To get. Then, after aligning the image of the inspection object and the reference image, the pixel of the reference image corresponding to the pixel existing at a certain coordinate position of the inspection object is found, and within the allowable luminance width of the found reference pixel If the luminance value of the pixel of the inspection object is included in the pixel, it is determined that the pixel is a good pixel. Conversely, if it is not within the allowable luminance width, it is determined as a defective pixel, and if a predetermined number or more of defective pixels exist adjacently, it is determined that the printed circuit board is defective. (Patent Document 4).
JP 2007-101415 A JP 2006-78301 A JP 2006-78300 A JP 2007-309703 A
　しかしながら、このような検査をカラー画像で検査する場合、次のような問題を生ずる。すなわち、検査対象物からカラー画像を取得して、画素ごとにＲＧＢの輝度データを検査する場合、ＲＧＢのそれぞれの基準輝度幅内にその検査対象物の画素が含まれているか否かを判断するが、例えば、レジスト下層にパターンが存在しているような場合は、良品であったとしても、そのレジストの厚みのむらや、ロットの変更、色の調合具合によって微妙にＲＧＢの色合いが変化してしまうことがある。特に輝度変化が大きい場合は、良品であったとしても、暗い緑から明るい緑までの輝度幅が（Ｒ，Ｇ，Ｂ）＝（２０，１２０，６０）～（４０，２００，１５０）の範囲で変化してしまうことがあり、ＲＧＢ直交座標系で閾値の輝度幅を２０＜Ｒ（Δｘ）＜４０、１２０＜Ｇ（Δｙ）＜２００、６０＜Ｂ（Δｚ）＜１５０と大きめに設定しなければならない（図９参照）。しかるに、このように閾値の輝度幅を大きめに設定すると、本来不良と判定すべき箇所を不良と判定できなくなる可能性がある。具体的には、例えば、レジストが剥げてパターンの銅が露出している不良部分が存在している場合、一般に、そのような部分は、薄いレジストで覆われていているため完全な銅色ではなく、うっすら赤みを帯びたレジスト色（輝度値が（Ｒ，Ｇ，Ｂ）＝（３５，１５０，８０））となる。このため、基準輝度データの輝度幅を大きくすると、図９における直方体の領域が大きくなり、この露出部分の輝度値はこの基準輝度データの輝度幅内に含まれて、不良と判定することができなくなる。一方、この露出部分を不良と判定できるように閾値の幅を狭くすると、良品であるものが不良品と判定してしまい、その後の目視検査に手間がかかってしまうという問題を生ずる。 However, when such an inspection is performed with a color image, the following problems occur. That is, when a color image is acquired from an inspection object and RGB luminance data is inspected for each pixel, it is determined whether or not the pixel of the inspection object is included in each RGB reference luminance width. However, for example, when a pattern exists in the resist lower layer, even if it is a non-defective product, the RGB tint changes slightly due to uneven resist thickness, lot changes, and color mixing conditions. It may end up. In particular, when the luminance change is large, even if it is a non-defective product, the luminance width from dark green to bright green is in the range of (R, G, B) = (20, 120, 60) to (40, 200, 150). In the RGB Cartesian coordinate system, the threshold luminance width is set to a large value such as 20 <R (Δx) <40, 120 <G (Δy) <200, 60 <B (Δz) <150. (See FIG. 9). However, if the threshold luminance width is set to be large in this way, there is a possibility that a portion that should be determined as defective cannot be determined as defective. Specifically, for example, when there is a defective portion where the resist is peeled off and the copper of the pattern is exposed, generally, such a portion is covered with a thin resist, so that the complete copper color is not used. The resist color is slightly reddish (luminance values are (R, G, B) = (35, 150, 80)). For this reason, when the luminance width of the reference luminance data is increased, the rectangular parallelepiped area in FIG. 9 is increased, and the luminance value of the exposed portion is included in the luminance width of the reference luminance data and can be determined as defective. Disappear. On the other hand, if the threshold value is narrowed so that the exposed portion can be determined as defective, a non-defective product is determined as a defective product, and the subsequent visual inspection takes time.
　そこで、本発明は、上記課題に着目してなされたもので、カラー画像を用いて検査対象物の形成状態を検査する場合に、取得されたカラー画像のＲＧＢに対して検査のための閾値を最適な値に設定して検査の品質を向上できるようにした外観検査装置を提供することを目的とする。 Therefore, the present invention has been made paying attention to the above problems, and when inspecting the formation state of an inspection object using a color image, a threshold value for inspection is set for RGB of the acquired color image. An object of the present invention is to provide an appearance inspection apparatus which can be set to an optimum value and improve the quality of inspection.
　本発明は、上記課題を解決するために、検査対象物から取得された画像に基づいて当該検査対象物の形成状態を検査する外観検査装置において、検査対象物からカラー画像を取得し、当該検査対象物の検査部分におけるＲＧＢ輝度データを取得するＲＧＢ情報取得手段と、軸方向を輝度値としたＲＧＢ極座標系で各検査部分のＲＧＢ基準輝度データを記憶させる基準データ記憶手段と、前記ＲＧＢ情報取得手段から取得された各検査部分のＲＧＢ輝度データを極座標系の輝度データに変換する変換手段と、当該変換された極座標系の輝度データと前記基準データ記憶手段に記憶されたＲＧＢ極座標系におけるＲＧＢ基準輝度データとを比較して、ＲＧＢ基準輝度データ内に検査対象物のＲＧＢ輝度データが含まれているか否かによって当該検査領域の良否を判定する判定手段とを設けるようにしたものである。 In order to solve the above problems, the present invention obtains a color image from an inspection object in an appearance inspection apparatus that inspects the formation state of the inspection object on the basis of an image acquired from the inspection object. RGB information acquisition means for acquiring RGB luminance data in the inspection portion of the object, reference data storage means for storing RGB reference luminance data of each inspection portion in the RGB polar coordinate system with the axial direction as the luminance value, and the RGB information acquisition Conversion means for converting the RGB luminance data of each inspection part acquired from the means into luminance data of the polar coordinate system, and the RGB reference in the RGB polar coordinate system stored in the reference data storage means and the converted luminance data of the polar coordinate system Compared with the luminance data, depending on whether or not the RGB reference luminance data includes the RGB luminance data of the inspection object. It is obtained so as to provide a judging means for judging quality of 査領 zone.
　このようにすれば、取得した検査領域におけるＲＧＢの輝度値が製品ごとに大きくばらついていたとしても、図３に示すように、ＲＧＢの輝度の割合（色合い）を保った状態で全体的な輝度のみを大きく設定することができ、輝度のばらつきを吸収して高精度に検査させることができるようになる。 In this way, even if the RGB luminance values in the acquired inspection region vary widely from product to product, as shown in FIG. 3, the overall luminance is maintained while maintaining the RGB luminance ratio (color shade). Only a large value can be set, so that variations in luminance can be absorbed and inspection can be performed with high accuracy.
　また、このような発明において、検査対象物から取得されたＲＧＢ直交座標系の輝度データをＲＧＢ極座標系に変換させる変換テーブルを記憶させ、当該変換テーブルを参照して前記取得された各検査領域のＲＧＢ座標を変換させる。 Further, in such an invention, a conversion table for converting the luminance data of the RGB orthogonal coordinate system acquired from the inspection object into the RGB polar coordinate system is stored, and each of the acquired inspection regions is obtained with reference to the conversion table. Convert RGB coordinates.
　このようにすれば、あらかじめ用意された変換テーブルを参照して座標変換するため、検査の都度、座標変換の演算をする必要がなく、検査時における処理速度を早くすることができる。 In this way, since coordinate conversion is performed with reference to a conversion table prepared in advance, there is no need to perform coordinate conversion every time inspection is performed, and the processing speed during inspection can be increased.
　さらに、ＲＧＢ基準輝度データを設定する場合、基準となる検査対象物の隣接する所定画素数のＲＧＢ輝度データを含ませるようにする。 Further, when setting the RGB reference luminance data, RGB luminance data of a predetermined number of pixels adjacent to the reference inspection object is included.
　このようにすれば、基準データと検査対象物とを画素単位で位置あわせしなくても検査することができ、虚報を減らして検査することができるようになる。 In this way, it is possible to inspect without aligning the reference data and the inspection object in pixel units, and it is possible to inspect with reduced false alarms.
　加えて、ＲＧＢの輝度を極座標系の輝度に変換した場合に、１バイトに収まるように輝度値を圧縮もしくは拡張させるようにする。 In addition, when RGB luminance is converted into polar coordinate luminance, the luminance value is compressed or expanded so as to fit in one byte.
　通常、直交座標系ではＲＧＢの輝度値は「０～２５５」の１バイトの範囲内に収まるが、これを極座標系に変換した場合、軸方向からの角度（θ、ρ）については、０から２／πの範囲内と十分に１バイトの範囲内に収まり、一方、原点からの距離（Ｌ）については、０から２５５×３（１／２）の範囲内と１バイトを超えてしまう。そのため、軸方向からの角度については、（２５５×４／π）倍とし、また、原点からの距離については、１／３（１／２）倍に縮小する。このようにすると、１バイトの範囲内に収めてデータを圧縮することができる。 Usually, in the rectangular coordinate system, the luminance value of RGB falls within the range of 1 byte of “0 to 255”, but when this is converted into the polar coordinate system, the angle (θ, ρ) from the axial direction is from 0. The distance (L) from the origin falls within the range of 0 to 255 × 3 (1/2) and exceeds 1 byte. Therefore, the angle from the axial direction is (255 × 4 / π) times, and the distance from the origin is reduced to 1/3 (1/2) times. In this way, data can be compressed within a range of 1 byte.
　本発明では、検査対象物から取得された画像に基づいて当該検査対象物の形成状態を検査する外観検査装置において、検査対象物からカラー画像を取得し、当該検査対象物の検査部分におけるＲＧＢ輝度データを取得するＲＧＢ情報取得手段と、軸方向を輝度値としたＲＧＢ極座標系で各検査部分のＲＧＢ基準輝度データを記憶させる基準データ記憶手段と、前記ＲＧＢ情報取得手段から取得された各検査部分のＲＧＢ輝度データを極座標系の輝度データに変換する変換手段と、当該変換された極座標系の輝度データと前記基準データ記憶手段に記憶されたＲＧＢ極座標系におけるＲＧＢ基準輝度データとを比較して、ＲＧＢ基準輝度データ内に検査対象物のＲＧＢ輝度データが含まれているか否かによって当該検査領域の良否を判定する判定手段とを設けるようにしたので、取得した検査領域におけるＲＧＢの輝度値が製品ごとに大きくばらついていたとしても、ＲＧＢの輝度の割合（色合い）を保った状態で全体的な輝度のみを大きく設定することができ、輝度のばらつきを吸収して高精度に検査させることができるようになる。 In the present invention, in the appearance inspection apparatus that inspects the formation state of the inspection object based on the image acquired from the inspection object, a color image is acquired from the inspection object, and the RGB luminance in the inspection portion of the inspection object RGB information acquisition means for acquiring data, reference data storage means for storing RGB reference luminance data of each inspection part in an RGB polar coordinate system with the axial direction as a luminance value, and each inspection part acquired from the RGB information acquisition means Converting the RGB luminance data of the RGB coordinate data into luminance data of the polar coordinate system, comparing the converted luminance data of the polar coordinate system with the RGB reference luminance data in the RGB polar coordinate system stored in the reference data storage unit, The quality of the inspection area is determined based on whether or not the RGB reference luminance data includes the RGB luminance data of the inspection object. Since the RGB luminance values in the acquired inspection area vary greatly from product to product, only the overall luminance is increased while maintaining the RGB luminance ratio (color shade). Therefore, it is possible to absorb the variation in luminance and to inspect with high accuracy.
　以下、本発明の一実施の形態について図面を参照しながら説明する。図１は、本実施の形態における外観検査の処理概要を示したものであり、図２は、その外観検査装置１における機能ブロック図を示したものである。また、図３は、その外観検査装置１で使用されるＲＧＢ輝度基準データを示したものである。 Hereinafter, an embodiment of the present invention will be described with reference to the drawings. FIG. 1 shows an outline of the appearance inspection process in the present embodiment, and FIG. 2 shows a functional block diagram of the appearance inspection apparatus 1. FIG. 3 shows RGB luminance reference data used in the appearance inspection apparatus 1.
　この実施の形態における外観検査装置１は、プリント基板や半導体ウエハ、その他、物品に生じた亀裂、物品の表面に印刷された状態などを検査できるようにしたもので、この実施の形態では、一例としてプリント基板の形成状態を検査する場合について説明する。 The appearance inspection apparatus 1 in this embodiment can inspect a printed circuit board, a semiconductor wafer, other cracks generated in an article, a state printed on the surface of the article, and the like. In this embodiment, an example is given. The case where the formation state of the printed circuit board is inspected will be described.
　この外観検査装置１は、図２の機能ブロック図に示すように、一般的な外観検査装置と同様に、検査対象物１１から表面画像を取得する撮像手段２と、この撮像手段２によって取得された画像から各画素のＲＧＢ情報を取得するＲＧＢ情報処理手段と、検査対象物１１の画像と基準データである画像とを位置合わせする補正処理手段６と、このように位置合わせ補正された検査対象物１１の各画素のＲＧＢ輝度データを用いて当該画素の良否を判定する判定手段８とを備えてなる。そして、特徴的に、検査対象物１１から取得された各画像のＲＧＢの輝度データを極座標系のＲＧＢ輝度データに変換する変換手段７と、当該変換されたＲＧＢ輝度データとあらかじめ記憶手段５に記憶された極座標系のＲＧＢ輝度基準データとを比較して各画素の良否を判定し、その結果を出力手段９を介して出力できるようにしたものである。以下、この外観検査装置１の具体的構成について詳細に説明する。 As shown in the functional block diagram of FIG. 2, the appearance inspection apparatus 1 is acquired by the imaging means 2 that acquires a surface image from the inspection object 11 and the imaging means 2, as in a general appearance inspection apparatus. RGB information processing means for obtaining RGB information of each pixel from the obtained image, correction processing means 6 for aligning the image of the inspection object 11 and the image that is the reference data, and the inspection object subjected to the alignment correction in this way And determining means 8 for determining the quality of the pixel using the RGB luminance data of each pixel of the object 11. Characteristically, the conversion means 7 for converting the RGB luminance data of each image acquired from the inspection object 11 into the RGB luminance data of the polar coordinate system, and the converted RGB luminance data and stored in the storage means 5 in advance. This is compared with the RGB luminance reference data of the polar coordinate system, and the quality of each pixel is judged, and the result can be outputted via the output means 9. Hereinafter, a specific configuration of the appearance inspection apparatus 1 will be described in detail.
　まず、撮像手段２は、検査に対し必要となる基準対象物１０や検査対象物１１からその表面画像を取得するもので、カラーによってその表面画像を取得する。この撮像手段２は、斜め方向から光を照射し、その上方でそのＣＣＤカメラなどによってその反射光を取得する。このとき、基準対象物１０や検査対象物１１に対して異なる角度および異なる色、明るさを用いて画像を取得し、その取得された画像を取捨選択して用いる。なお、この基準対象物１０は、検査対象物１１を検査するに際して基準となる基準データを生成するもので、目視もしくは他の検査装置などによって既に良品であると判定されたものを一般的に使用する。 First, the imaging means 2 acquires the surface image from the reference object 10 and the inspection object 11 necessary for the inspection, and acquires the surface image by color. This imaging means 2 irradiates light from an oblique direction, and acquires the reflected light by the CCD camera or the like above it. At this time, images are acquired using different angles, different colors, and brightness with respect to the reference object 10 and the inspection object 11, and the acquired images are selected and used. The reference object 10 generates reference data as a reference when the inspection object 11 is inspected. Generally, the reference object 10 that has been determined to be non-defective by visual inspection or other inspection devices is generally used. To do.
　基準データ生成手段４は、あらかじめ用意された基準対象物１０から表面画像を取得して、その基準対象物１０の画像から基準データを生成する。この生成される基準データは、基準対象物１０の全体形状に関するデータや、その内側の複数の矩形領域に関するデータ、各画素に関するデータなどによって構成される。このうち、全体形状に関するデータとしては、プリント基板の縦横の長さなどに関するデータ、また、矩形領域に関するデータとしては、矩形領域内のパターン画像などのデータ、各画素に関するデータとしては、各画素のＲＧＢ輝度や許容輝度幅及び探索距離などのデータなどが用いられる。ここで、「許容輝度幅」とは、良否判定となる画素におけるＲＧＢ輝度の幅を示すものであり、例えば、シルクの縁、パッドの縁、配線パターンの縁などのように輝度変化の大きい部分については大きく設定されるものである。また、「探索距離」とは、所定の画素位置を中心として基準対象物１０に対応する画素が存在するか否かを探索するための距離を示すものであって、例えば、シルクの縁、パッドの縁、配線パターンの縁などのように輝度変化の大きい部分については、探索距離も３画素から５画素などのように大きく設定されるものである。これらの許容輝度幅や探索距離は自動的に設定され、予め許容輝度幅や探索距離の上限値をマニュアルで設定しておき、例えば、図１においては、極座標で表現された許容輝度幅を±Δθ、±Δρ、±ΔＬと設定し、探索距離を３画素などと設定する。なお、この許容輝度幅や探索距離については、これらの値に限定されるものではなく、マニュアルで設定してもよい。 The reference data generation means 4 acquires a surface image from a reference object 10 prepared in advance, and generates reference data from the image of the reference object 10. The generated reference data includes data relating to the entire shape of the reference object 10, data relating to a plurality of rectangular areas inside the reference object 10, data relating to each pixel, and the like. Of these, data relating to the overall shape includes data relating to the length and width of the printed circuit board, data relating to the rectangular area includes data such as pattern images in the rectangular area, and data relating to each pixel includes data relating to each pixel. Data such as RGB luminance, allowable luminance width, and search distance are used. Here, the “allowable luminance width” indicates the RGB luminance width in a pixel that is determined to be good or bad. For example, a portion having a large luminance change such as a silk edge, a pad edge, or a wiring pattern edge. Is set to be large. The “search distance” indicates a distance for searching whether or not there is a pixel corresponding to the reference object 10 with a predetermined pixel position as the center. For example, a silk edge, a pad The search distance is set to a large value such as 3 to 5 pixels for a portion where the luminance change is large such as the edge of the wiring pattern or the edge of the wiring pattern. These allowable luminance width and search distance are automatically set, and the upper limit value of the allowable luminance width and search distance is set manually in advance. For example, in FIG. 1, the allowable luminance width expressed in polar coordinates is ± Δθ, ± Δρ, ± ΔL are set, and the search distance is set to 3 pixels or the like. The allowable luminance width and the search distance are not limited to these values, and may be set manually.
　図３に、この基準データの概要を示す。図３は、各画素の良否を判定する際に使用される基準データを示したものであり、各軸をＲＧＢの輝度値とし、矢印の方向に向かって輝度値を大きく設定している。一般に、このようなＲＧＢ直交座標系で基準データを設定する場合、検査対象物１１のレジストのむら、ロットの変更、色の調合具合によって微妙にＲＧＢの色合いが変化してしまう。特に、製品によって輝度変化が大きい場合は、暗い緑から明るい緑までの輝度幅が（Ｒ，Ｇ，Ｂ）＝（２０，１２０，６０）～（４０，２００，１５０）の範囲で変化してしまうことがある。このため、ＲＧＢ直交座標系で基準輝度データを設定すれば、輝度幅を２０＜Ｒ＜４０、１２０＜Ｇ＜２００、６０＜Ｂ＜１５０というように大き目に設定しなければならなくなる（図９の状態）。しかるに、このようにＲＧＢ輝度基準データの輝度幅を大きく設定すると、ほとんどの画素が基準データの範囲内に含まれてしまうため、実際には、ＲＧＢ輝度値のバランスが大きく異なって全く違う色に見えるものまで基準データの範囲内に含まれて「良」と判定されてしまう。より具体的には、レジストが剥げてパターンの銅が露出している箇所が存在している場合は、その部分は、本来「不良」と判定されなければならないが、この部分は、部分的に薄いレジストで覆われていているため、うっすら赤みを帯びたレジスト色（輝度値が（Ｒ，Ｇ，Ｂ）＝（３５，１５０，８０））となることが多い。このため、このような部分をＲＧＢ直交座標系の基準データで判定すると、不良と判定できなくなる。 Figure 3 shows an overview of this reference data. FIG. 3 shows reference data used when determining the quality of each pixel. The luminance values of RGB are set on the respective axes, and the luminance values are set to increase in the direction of the arrows. In general, when the reference data is set in such an RGB orthogonal coordinate system, the RGB hue slightly changes depending on the resist unevenness of the inspection object 11, the change of the lot, and the color composition. In particular, when the luminance change is large depending on the product, the luminance width from dark green to bright green changes within the range of (R, G, B) = (20, 120, 60) to (40, 200, 150). It may end up. For this reason, if the reference luminance data is set in the RGB orthogonal coordinate system, the luminance width must be set as large as 20 <R <40, 120 <G <200, 60 <B <150 (FIG. 9). State). However, if the luminance width of the RGB luminance reference data is set to be large as described above, most pixels are included in the range of the reference data. Anything that can be seen is included in the range of the reference data and judged as “good”. More specifically, when there is a portion where the resist is peeled off and the copper of the pattern is exposed, the portion must be determined as “bad” originally, but this portion is partially Since it is covered with a thin resist, it often has a slightly reddish resist color (luminance values (R, G, B) = (35, 150, 80)). For this reason, if such a portion is determined based on the reference data of the RGB orthogonal coordinate system, it cannot be determined as defective.
　そこで、この実施の形態では、図３に示すように、ＲＧＢ極座標系の空間で表現されるＲＧＢ輝度基準データを用いる。このような座標系を用いれば、ＲＧＢ輝度値のバランスを保った状態で輝度値が全体的に小さくなった場合であっても、その画素を良画素と判定することができる。すなわち、図３に示すように、輝度値が（Ｒ，Ｇ，Ｂ）＝（２０，１２０，６０）～（４０，２００，１５０）の範囲内の画素を判定する場合、全体のＲＧＢ輝度値のバランスを保って全体の輝度値のみ異なる画素を良画素と判定することができる。一方、（Ｒ，Ｇ，Ｂ）＝（３５，１５０，８０）などといった輝度値バランスの異なった画素、すなわち、色合いの全く異なる画素を不良画素と判定することができるようになる。なお、これらの画素のＲＧＢ輝度基準データを生成する場合、その画素に隣接する画素のＲＧＢ輝度値も含まれるように設定する。そして、このように設定されたＲＧＢ輝度基準データを、記憶手段５に格納する。 Therefore, in this embodiment, as shown in FIG. 3, RGB luminance reference data expressed in the RGB polar coordinate system space is used. If such a coordinate system is used, even if the luminance value is reduced as a whole while maintaining the balance of the RGB luminance values, the pixel can be determined as a good pixel. That is, as shown in FIG. 3, when determining pixels within the range of luminance values (R, G, B) = (20, 120, 60) to (40, 200, 150), the entire RGB luminance value is determined. Thus, it is possible to determine a pixel that is different from the entire luminance value while maintaining the above balance as a good pixel. On the other hand, pixels with different brightness value balances such as (R, G, B) = (35, 150, 80), that is, pixels with completely different hues can be determined as defective pixels. In addition, when generating the RGB luminance reference data of these pixels, the RGB luminance values of the pixels adjacent to the pixel are set to be included. Then, the RGB luminance reference data set in this way is stored in the storage means 5.
　補正処理手段６は、撮像手段２によって撮像された検査対象物１１の画像を、基準対象物１０の画像にほぼ一致させるための補正処理を行う。この補正処理における全体画像の補正の例を図４に示す。図４において、斜線で網掛けされた実線部分は基準対象物１０を示し、破線は検査対象物１１を示している。図４に示すように、検査対象物１１が基準対象物１０よりも小さい場合は（図４（ａ））、全体形状をδx、δyだけ拡大させるような補正処理を行う。また、検査対象物１１が基準対象物１０よりもδθだけ回転している場合は、その角度だけ回転させるような補正処理を行う。また、検査対象物１１が基準対象物１０に対して平行にずれている場合は、そのずれ量分だけ平行移動させるような補正処理を行う。これらの補正処理は、例えば、検査対象物１１がステージ上の正規の位置に固定されていない場合や、検査対象物１１の寸法上に誤差が存在する場合などに有効となる。 The correction processing unit 6 performs correction processing for making the image of the inspection object 11 imaged by the imaging unit 2 substantially coincide with the image of the reference object 10. An example of the correction of the entire image in this correction processing is shown in FIG. In FIG. 4, a solid line portion shaded with diagonal lines indicates the reference object 10, and a broken line indicates the inspection object 11. As shown in FIG. 4, when the inspection object 11 is smaller than the reference object 10 (FIG. 4A), correction processing is performed to enlarge the entire shape by δ x and δ y . Also, if the inspection object 11 is rotated by also [delta] theta than reference object 10 performs correction processing as rotated by that angle. Further, when the inspection object 11 is displaced in parallel with the reference object 10, a correction process is performed in which the inspection object 11 is translated by the amount of the displacement. These correction processes are effective when, for example, the inspection object 11 is not fixed at a regular position on the stage, or when there is an error in the dimensions of the inspection object 11.
　次に、この補正処理の別の態様を図５に示す。図５（ａ）は、基準対象物１０のある矩形領域の例を示したものであり、図５（ｂ）は、検査対象物１１の同じ位置における矩形領域を示したものである。実際の製品では、図５（ｂ）に示すように、検査対象物１１のパッドや配線パターンなどが、基準対象物１０のパッドや配線パターンなどよりも所定方向にずれている場合がある。このような場合に、検査対象物１１の矩形領域内の画像を基準対象物１０にほぼ一致させるような平行移動の補正処理を行う。これらの補正処理を行うことにより、検査対象物１１のパッドや配線パターンなどは、基準対象物１０のパッドや配線パターンなどとほぼ一致することになり、あまり探索距離を大きくしなくても許容輝度幅内の画素を見つけ出すことができる。すなわち、本来ならば、補正前のずれた画像の対応する位置まで探索距離を広げて画素を見つけ出さなければならないところを、狭い探索距離で対応する画素を見つけ出すことができるようになる。そして、このように探索距離を狭めることによって、無関係な画素でたまたま輝度が一致するものを「対応する画素」と判定してしまうことを防止することができるようになる。 Next, another aspect of this correction processing is shown in FIG. FIG. 5A shows an example of a rectangular area where the reference object 10 is located, and FIG. 5B shows a rectangular area at the same position of the inspection object 11. In an actual product, as shown in FIG. 5B, the pad or wiring pattern of the inspection object 11 may be displaced in a predetermined direction from the pad or wiring pattern of the reference object 10. In such a case, a parallel movement correction process is performed so that the image in the rectangular area of the inspection object 11 substantially matches the reference object 10. By performing these correction processes, the pad and the wiring pattern of the inspection object 11 substantially coincide with the pad and the wiring pattern of the reference object 10, and the allowable luminance can be obtained without increasing the search distance too much. Pixels within the width can be found. That is, originally, it is possible to find a corresponding pixel with a narrow search distance, where the search distance must be extended to a corresponding position in the image that has been corrected before correction. By narrowing the search distance in this way, it is possible to prevent an irrelevant pixel that happens to have the same luminance to be determined as a “corresponding pixel”.
　そして、ＲＧＢ情報取得手段３は、このように補正処理された後の検査対象物１１の画像から各画素のＲＧＢ輝度データを取得する。このとき、取得されたＲＧＢ輝度データは（Ｒ，Ｇ，Ｂ）＝（０，０，０）～（２５５，２５５，２５５）の範囲内に含まれる情報となるが、この直交座標系で表現された座標を変換手段７を用いてＲＧＢ極座標系の座標に変換する。 Then, the RGB information acquisition means 3 acquires RGB luminance data of each pixel from the image of the inspection object 11 that has been corrected in this way. At this time, the acquired RGB luminance data is information included in the range of (R, G, B) = (0, 0, 0) to (255, 255, 255), but is expressed in this orthogonal coordinate system. The converted coordinates are converted into coordinates in the RGB polar coordinate system using the conversion means 7.
　変換手段７を用いて直交座標系を極座標系に変換させる場合、この実施の形態では、図６に示すように、あらかじめ直交座標系の値（ｘ，ｙ，ｚ）を極座標系の値（θ，ρ，Ｌ）の値に変換させる変換テーブルを用意しておき、この変換テーブルを参照して極座標系のＲＧＢ輝度データに変換させる。一般に、直交座標と極座標との関係は、次のような関係を示す。
ｘ＝Ｌsinρcosθ
ｙ＝Ｌsinρsinθ
ｚ＝Ｌcosθ
ただし、ｘは直交座標系におけるＲの輝度値、ｙは直交座標系におけるＧの輝度値、ｚは直交座標系におけるＢの輝度値、θは極座標系におけるｘ軸とのなす角度、ρは極座標系におけるｚ軸とのなす角度、Ｌは極座標系における全体の輝度値を示す。 In the case where the orthogonal coordinate system is converted into the polar coordinate system using the conversion means 7, in this embodiment, as shown in FIG. 6, the values (x, y, z) of the orthogonal coordinate system are previously set to the values of the polar coordinate system (θ , Ρ, L), a conversion table to be converted is prepared, and converted to RGB luminance data of the polar coordinate system with reference to this conversion table. In general, the relationship between orthogonal coordinates and polar coordinates is as follows.
x = Lsinρcosθ
y = Lsinρsinθ
z = Lcosθ
Where x is the luminance value of R in the Cartesian coordinate system, y is the luminance value of G in the Cartesian coordinate system, z is the luminance value of B in the Cartesian coordinate system, θ is the angle made with the x axis in the polar coordinate system, and ρ is the polar coordinate The angle L formed with the z-axis in the system indicates the overall luminance value in the polar coordinate system.
　そこで、これらの関係を逆変換させて、（ｘ，ｙ，ｚ）の値を次のような極座標系の値に変換し、これらの変換値を変換テーブルとして記憶手段５に記憶させておく。
ρ＝ｔａｎ－１｛（ｘ２＋ｙ２）１／２／ｚ｝
θ＝ｔａｎ－１（ｙ／ｘ）
Ｌ＝（ｘ２＋ｙ２＋ｚ２）１／２ Therefore, these relationships are inversely converted to convert the value of (x, y, z) into the following polar coordinate system values, and these converted values are stored in the storage means 5 as a conversion table.
ρ = tan −1 {(x 2 + y 2 ) 1/2 / z}
θ = tan −1 (y / x)
L = (x 2 + y 2 + z 2 ) 1/2
　ところで、このように直交座標系の輝度値（０～２５５）を極座標系の輝度値に変換した場合、θやρについては、０≦θ≦π／２、０≦ρ≦π／２、となり、Ｌについては、０≦Ｌ≦２５５×３（１／２）となる。このため、θやρについては、１バイトよりも小さくなり、Ｌについては１バイトを超えてしまう。そこで、θやρを、ちょうど１バイトになるように変換後の輝度値を２５５×２／π倍とし、また、Ｌについては、ちょうど１バイトに収まるように変換後の輝度値を１／３（１／２）倍に圧縮する。 By the way, when the luminance values (0 to 255) in the orthogonal coordinate system are converted into the luminance values in the polar coordinate system, θ and ρ are 0 ≦ θ ≦ π / 2 and 0 ≦ ρ ≦ π / 2. , L, 0 ≦ L ≦ 255 × 3 (1/2) . Therefore, θ and ρ are smaller than 1 byte, and L exceeds 1 byte. Therefore, the converted luminance value is multiplied by 255 × 2 / π so that θ and ρ are exactly 1 byte, and for L, the converted luminance value is 1/3 so that it is exactly 1 byte. Compress to (1/2) times.
　判定手段８は、基準対象物１０の各画素に対応する画素が検査対象物１１に存在するか否かを判定するもので、次に示すような第一の画素判定手段８１と第二の画素判定手段８２からなる画素判定手段８０と、クラスタ判定手段８３とを備える。 The determination means 8 determines whether or not the inspection object 11 has a pixel corresponding to each pixel of the reference object 10, and the first pixel determination means 81 and the second pixel as described below. A pixel determination unit 80 including a determination unit 82 and a cluster determination unit 83 are provided.
　まず、第一の画素判定手段８１は、基準対象物１０を基準として、その基準対象物１０の各画素に対応する検査対象物１１の位置を特定し、この位置を中心とする探索距離内に、その画素の輝度に対する許容輝度幅内の画素が存在するか否かを判定する。この判定に際しては、探索距離内にＲＧＢ輝度基準データの許容輝度幅内の画素が一つでも存在する場合は、「良画素」と判定し、逆に、探索距離内に許容輝度幅内の画素が全く存在しない場合は「不良画素」と判定する。通常、補正処理手段６によって基準対象物１０と検査対象物１１を完全に一致させることができれば、基準対象物１０の画素位置に対応する検査対象物１１の位置の画素を検査すれば良い。しかしながら、実際には、光学的なずれや機械的なずれが存在することから、完全に一致させることが困難であり、また、分解能を上げた場合は数画素程度ずれる可能性がある。このため、探索距離内においてほぼ輝度の一致するものが存在すれば、一次的判断として「良画素」と判定する。この第一の画素判定手段８１による判定結果は、ディスプレイ装置などに可視的に表示され、例えば、「不良画素」と判定された部分には、基準対象物１０の画像上に「×」印などを示す。 First, the first pixel determination unit 81 specifies the position of the inspection object 11 corresponding to each pixel of the reference object 10 with the reference object 10 as a reference, and within a search distance centered on this position. Then, it is determined whether or not there is a pixel within an allowable luminance width with respect to the luminance of the pixel. In this determination, if even one pixel within the allowable luminance width of the RGB luminance reference data exists within the search distance, it is determined as “good pixel”, and conversely, a pixel within the allowable luminance width within the search distance. Is not determined at all, it is determined as “defective pixel”. Normally, if the correction processing means 6 can completely match the reference object 10 and the inspection object 11, the pixel at the position of the inspection object 11 corresponding to the pixel position of the reference object 10 may be inspected. However, in reality, there are optical shifts and mechanical shifts, so that it is difficult to make them completely coincide with each other. Further, when the resolution is increased, there is a possibility that the shift is about several pixels. For this reason, if there is an almost identical luminance within the search distance, it is determined as “good pixel” as a primary determination. The determination result by the first pixel determination unit 81 is visually displayed on a display device or the like. For example, in the portion determined as “defective pixel”, an “x” mark or the like is displayed on the image of the reference object 10. Indicates.
　第二の画素判定手段８２は、今度は逆に、検査対象物１１を基準として、基準対象物１０の位置を中心とする探索距離内に、その検査対象物１１の画素の輝度に対する許容輝度幅内の画素が存在するか否かを判定する。この判定に際しても、探索距離内に許容輝度幅内の画素が一つでも存在する場合は、「良画素」と判定し、逆に、探索距離内に許容輝度幅内の画素が全く存在しない場合は「不良画素」と判定する。この検査対象物１１を基準として比較処理を行う場合、前述の補正処理された後の検査対象物１１の画像を用いる。そして、補正処理された後の検査対象物１１の前記位置（前記第一の探索距離の中心位置）に対応する基準対象物１０の位置を特定し、その位置における許容輝度幅・探索距離を記憶手段５から読み出して、その探索距離内に検査対象物１１のその位置の輝度に対する許容輝度幅内の画素が基準対象物１０上に存在するか否かを判定する。この場合、本発明との関係において、第一の探索距離と第二の探索距離は一致することになり、第一の許容輝度幅と第二の許容輝度幅は一致することになる。通常、補正処理手段６によって基準対象物１０と検査対象物１１を完全に一致させることができれば、基準対象物１０の画素位置に対応する検査対象物１１の位置の画素を検査すれば良い。しかしながら、実際には、光学的なずれや機械的なずれが存在することから、完全に一致させることが困難であり、また、分解能を上げた場合は数画素程度ずれる可能性がある。このため、探索距離内においてほぼ輝度が一致するものが存在していれば、二次的判断として「良画素」と判定する。この第二の判定結果は、先の第一の判定結果と同様に、ディスプレイ装置に可視的に表示され、第一の画素判定手段８１による判定画像に上書きして、「不良画素」と判定された部分に「×」印などを示していく。 On the contrary, the second pixel determination means 82, on the contrary, uses the inspection object 11 as a reference, and within the search distance centered on the position of the reference object 10, the allowable luminance width for the luminance of the pixel of the inspection object 11 It is determined whether or not there is a pixel inside. Also in this determination, if there is even one pixel within the allowable luminance width within the search distance, it is determined as “good pixel”, and conversely, there is no pixel within the allowable luminance width within the search distance. Is determined as “defective pixel”. When the comparison process is performed using the inspection object 11 as a reference, an image of the inspection object 11 after the above correction process is used. Then, the position of the reference object 10 corresponding to the position (the center position of the first search distance) of the inspection object 11 after the correction processing is specified, and the allowable luminance width / search distance at the position is stored. It is read out from the means 5 and it is determined whether or not a pixel within the allowable luminance width with respect to the luminance at the position of the inspection object 11 exists on the reference object 10 within the search distance. In this case, in the relationship with the present invention, the first search distance and the second search distance match, and the first allowable luminance width and the second allowable luminance width match. Normally, if the correction processing means 6 can completely match the reference object 10 and the inspection object 11, the pixel at the position of the inspection object 11 corresponding to the pixel position of the reference object 10 may be inspected. However, in reality, there are optical shifts and mechanical shifts, so that it is difficult to make them completely coincide with each other. Further, when the resolution is increased, there is a possibility that the shift is about several pixels. For this reason, if there is a pixel having substantially the same brightness within the search distance, it is determined as “good pixel” as a secondary determination. Similar to the first determination result, the second determination result is visually displayed on the display device, overwritten on the determination image by the first pixel determination unit 81, and determined as a “defective pixel”. An “x” mark or the like is shown in the part.
　そして、最終的に、画素判定手段８０は、検査対象物１１の探索距離内に許容輝度幅内の画素が一つでも存在すること、及び、基準対象物１０の探索距離内に許容輝度幅内の画素が一つでも存在することを条件に、その基準対象物１０の位置に存在する画素を良画素と判定する。また、逆に、検査対象物１１の探索距離内に許容輝度幅内の画素が全く存在しない場合、もしくは、基準対象物１０の探索距離内に許容輝度幅内の画素が全く存在しない場合は、その基準対象物１０の位置に存在する画素を不良画素と判定する。 Finally, the pixel determination unit 80 determines that there is at least one pixel within the allowable luminance width within the search distance of the inspection object 11, and within the allowable luminance width within the search distance of the reference object 10. On the condition that at least one pixel exists, the pixel existing at the position of the reference object 10 is determined as a good pixel. Conversely, when there is no pixel within the allowable luminance width within the search distance of the inspection object 11, or when there are no pixels within the allowable luminance width within the search distance of the reference object 10, A pixel present at the position of the reference object 10 is determined as a defective pixel.
　クラスタ判定手段８３は、この画素判定手段８０によって「不良画素」と判定された基準対象物１０の画素群の大きさに基づいて、その検査対象物１１が全体として不良品であるか否かを判定する。この良否の判定は、「不良画素」と判定された画素が隣接して所定数以上存在する場合に、不良品であると判定する。 Based on the size of the pixel group of the reference object 10 determined as “defective pixel” by the pixel determining means 80, the cluster determining means 83 determines whether or not the inspection object 11 is a defective product as a whole. judge. This pass / fail determination is determined to be a defective product when there are a predetermined number or more of adjacent pixels determined to be “defective pixels”.
　出力手段９は、このクラスタ判定手段８３による判定結果を報知可能に出力する。その際、どの部分が不良のクラスタであるかをユーザに知らせる必要があるので、クラスタ判定手段８３によって不良クラスタと判定されたクラスタの位置をディスプレイ装置に可視的に出力する。 The output unit 9 outputs the determination result by the cluster determination unit 83 in a reportable manner. At this time, since it is necessary to inform the user which part is a defective cluster, the position of the cluster determined to be a defective cluster by the cluster determination means 83 is visually output to the display device.
　次に、このように構成された外観検査装置１を用いて検査対象物１１を検査する方法について説明する。 Next, a method for inspecting the inspection object 11 using the appearance inspection apparatus 1 configured as described above will be described.
　＜基準データの生成フロー＞
まず、検査対象物１１を検査するに際して基準データを生成する場合のフローチャートを図７に示す。基準データを生成する場合、まず、予め用意された複数の基準対象物１０からそれぞれの画像を取得する（ステップＳ１）。そして、所定枚数以上の基準対象物１０の画像が取り込まれた場合、基準対象物１０毎に、それぞれ全体領域に関するデータ、矩形領域に関するデータ、画素に関するデータを生成し（ステップＳ２）、複数の基準対象物１０について、全体領域に関するデータの平均値や、矩形領域に関するデータの平均値、画素に関するＲＧＢのデータの平均値や標準偏差値を演算する（ステップＳ３）。そして、次に、許容輝度幅の上限値や探索距離の上限値をマニュアルで入力する（ステップＳ４）。なお、この入力は、この段階ではなく、ステップＳ１の前に予め入力しておくようにしても良い。 <Standard data generation flow>
First, FIG. 7 shows a flowchart for generating reference data when inspecting the inspection object 11. When generating reference data, first, each image is acquired from a plurality of reference objects 10 prepared in advance (step S1). When a predetermined number or more of images of the reference object 10 are captured, the data relating to the entire area, the data relating to the rectangular area, and the data relating to the pixels are generated for each reference object 10 (step S2). For the object 10, an average value of data relating to the entire area, an average value of data relating to the rectangular area, an average value of RGB data relating to pixels, and a standard deviation value are calculated (step S3). Next, the upper limit value of the allowable luminance width and the upper limit value of the search distance are manually input (step S4). This input is not performed at this stage, but may be performed in advance before step S1.
　そして、ステップＳ３の平均値や標準偏差値の演算が行われた後、標準偏差値の大きい画素については、先に入力された許容輝度幅の上限値及び探索距離の上限値を設定するとともに、標準偏差値の小さい画素については、許容輝度幅や探索距離を小さく設定していく（ステップＳ５）。そして、各画素毎にＲＧＢ極座標でＲＧＢ輝度基準データを生成し、記憶手段５に格納する（ステップＳ６）。 Then, after the calculation of the average value and the standard deviation value in step S3, for the pixels having a large standard deviation value, the upper limit value of the allowable luminance width and the upper limit value of the search distance that are input previously are set, For pixels having a small standard deviation value, the allowable luminance width and the search distance are set to be small (step S5). Then, RGB luminance reference data is generated with RGB polar coordinates for each pixel and stored in the storage means 5 (step S6).
　＜検査対象物１１の検査フロー＞
次に、検査対象物１１を検査する場合のフローチャートを図８に示す。まず、検査対象物１１を検査する場合、その検査対象物１１からその表面画像を取得する（ステップＴ１）。この撮像された画像は、画像の取得方法によっては位置ずれしている可能性があり、記憶手段５に記憶されている基準対象物１０の画像の状態とは異なっている場合がある。このため、画像状態をほぼ一致させるために補正処理を行う（ステップＴ２）。この補正処理に際しては、まず、全体形状の補正処理を行う。具体的には、検査対象物１１上のコーナーの３点を抽出し、その３点から検査対象物１１の縦横の長さ、回転角度、平行移動距離などを演算する。そして、これらの縦横長さや回転角度、平行移動距離などに基づいて、検査対象物１１の全体画像を基準データの全体画像にほぼ一致させるような補正処理を行う。 <Inspection flow of inspection object 11>
Next, a flowchart for inspecting the inspection object 11 is shown in FIG. First, when inspecting the inspection object 11, the surface image is acquired from the inspection object 11 (step T1). This captured image may be misaligned depending on the image acquisition method, and may be different from the state of the image of the reference object 10 stored in the storage unit 5. Therefore, correction processing is performed to make the image states substantially coincide (step T2). In this correction process, first, the entire shape is corrected. Specifically, three corner points on the inspection object 11 are extracted, and the vertical and horizontal lengths, rotation angles, parallel movement distances, and the like of the inspection object 11 are calculated from the three points. Then, based on these vertical and horizontal lengths, rotation angles, parallel movement distances, etc., correction processing is performed so that the entire image of the inspection object 11 substantially matches the entire image of the reference data.
　次に、矩形領域の補正処理を行う。この矩形領域の補正処理を行う場合、基準対象物１０の所定の矩形領域の画像と検査対象物１１の対応する矩形領域の画像とがほぼ一致するように検査対象物１１の画像を平行移動させる。 Next, the rectangular area is corrected. When this rectangular area correction processing is performed, the image of the inspection object 11 is translated so that the image of the predetermined rectangular area of the reference object 10 and the image of the corresponding rectangular area of the inspection object 11 substantially coincide. .
　そして、これらの補正処理が終了した後、基準対象物１０の各位置に存在する画素が良画素であるか否かを判定する。この判定に際しては、まず、基準対象物１０の各画素に対する位置、ＲＧＢ輝度、許容輝度幅、探索距離を記憶手段５から読み出す（ステップＴ３）。そして、この読み出された画素に対応する検査対象物１１の位置を特定し、その位置を中心として、その探索距離内に、ＲＧＢ極座標系で設定されたＲＧＢ輝度基準データ（許容輝度幅）内の画素が存在するか否かを判定する（ステップＴ４）。このＲＧＢ極座標系で設定されたＲＧＢ輝度基準データを用いる場合、検査対象物１１から読み出された画素のＲＧＢ輝度データを変換テーブルを参照して極座標系に変換し、その極座標系におけるＲＧＢ輝度データとを比較する。そして、第一の画素判定手段８１によって、探索距離内に許容輝度幅内の画素が一つも存在しないと判定された場合は、その基準対象物１０の位置の画素を「不良画素」と判定する（ステップＴ８）。 Then, after these correction processes are completed, it is determined whether or not the pixels present at each position of the reference object 10 are good pixels. In this determination, first, the position, RGB luminance, allowable luminance width, and search distance for each pixel of the reference object 10 are read from the storage means 5 (step T3). Then, the position of the inspection object 11 corresponding to the read pixel is specified, and within the RGB luminance reference data (allowable luminance width) set in the RGB polar coordinate system within the search distance with the position as the center. It is determined whether or not there is a pixel (step T4). When using the RGB luminance reference data set in the RGB polar coordinate system, the RGB luminance data of the pixel read from the inspection object 11 is converted into the polar coordinate system with reference to the conversion table, and the RGB luminance data in the polar coordinate system is converted. And compare. When the first pixel determining unit 81 determines that no pixel within the allowable luminance width exists within the search distance, the pixel at the position of the reference object 10 is determined as a “defective pixel”. (Step T8).
　次に、この第一の画素判定が終了した後、今度は、補正処理された後の検査対象物１１の画像を基準として、その検査対象物１１の位置に対応する基準対象物１０の位置を中心とする探索距離内に、ＲＧＢ極座標で設定されたＲＧＢ輝度基準データ（許容輝度幅）内の画素が存在するか否かを判定する。但し、検査対象物１１の各画素については、許容輝度幅や探索距離などのデータを記憶していないので、その検査対象物１１の位置に対応した基準対象物１０の位置の許容輝度幅や探索距離を用いる。 Next, after the first pixel determination is completed, the position of the reference object 10 corresponding to the position of the inspection object 11 is determined based on the image of the inspection object 11 after the correction process. It is determined whether or not there is a pixel within the RGB luminance reference data (allowable luminance width) set by the RGB polar coordinates within the search distance as the center. However, since each pixel of the inspection object 11 does not store data such as an allowable luminance width and a search distance, the allowable luminance width and the search of the position of the reference object 10 corresponding to the position of the inspection object 11 are stored. Use distance.
　具体的には、まず、その検査対象物１１の位置に対応した基準対象物１０の位置の許容輝度幅、探索距離を読み出す（ステップＴ５）。そして、この読み出された許容輝度幅及び探索距離に基づき、対応する基準対象物１０の位置を中心として、その探索距離内に、極座標系で表現された検査対象物１１のＲＧＢ輝度データに対する許容輝度幅内の画素が存在するか否かを判定する（ステップＴ６）。このとき、検査対象物１１から取得されたＲＧＢ輝度データを変換テーブルを用いて極座標系のＲＧＢ輝度データに変換して判定する。そして、第二の画素判定手段８２によって探索距離内に許容輝度幅内の輝度の画素が一つも存在しないと判定された場合は、その基準対象物１０の位置の画素を「不良画素」と判定する（ステップＴ８）。 Specifically, first, an allowable luminance width and a search distance of the position of the reference object 10 corresponding to the position of the inspection object 11 are read (step T5). Then, based on the read allowable luminance width and the search distance, the tolerance for the RGB luminance data of the inspection object 11 expressed in the polar coordinate system within the search distance with the position of the corresponding reference object 10 as the center. It is determined whether or not there is a pixel within the luminance width (step T6). At this time, the determination is made by converting the RGB luminance data acquired from the inspection object 11 into the RGB luminance data of the polar coordinate system using the conversion table. If it is determined by the second pixel determining means 82 that there is no luminance pixel within the allowable luminance width within the search distance, the pixel at the position of the reference object 10 is determined as a “defective pixel”. (Step T8).
　一方、ステップＴ４で「良画素」と判定され、かつ、ステップＴ６で「良画素」と判定された場合に、その基準対象物１０の位置に対する画素を「良画素」と判定する（ステップＴ７）。 On the other hand, if it is determined as “good pixel” in step T4 and “good pixel” is determined in step T6, the pixel corresponding to the position of the reference object 10 is determined as “good pixel” (step T7). .
　そして、全ての画素の検査が完了した場合（ステップＴ９；Ｙｅｓ）、次に、この画素判定手段８０によって「不良画素」と判定された基準対象物１０の画素のうち、隣接する不良画素の数をカウントし、所定数以上の不良画素の存在する場合は（ステップＴ１０）、この検査対象物１１は不良品である旨の出力を行い（ステップＴ１１）、一方、全ての隣接する不良画素の数が所定数よりも少ない場合は良品である旨の出力を行う（ステップＴ１２）。 If all the pixels have been inspected (step T9; Yes), the number of adjacent defective pixels among the pixels of the reference object 10 determined as “defective pixels” by the pixel determination unit 80 is then determined. When there are more than a predetermined number of defective pixels (step T10), the inspection object 11 outputs that it is a defective product (step T11), while the number of all adjacent defective pixels Is less than the predetermined number, an output indicating that the product is non-defective is output (step T12).
　このように上記実施の形態によれば、検査対象物１１から取得された画像に基づいて当該検査対象物１１の形成状態を検査する外観検査装置１において、検査対象物１１からカラー画像を取得し、当該検査対象物１１の検査部分におけるＲＧＢ輝度データを取得するＲＧＢ情報取得手段３と、軸方向を輝度値としたＲＧＢ極座標系において各検査部分のＲＧＢ基準輝度データを記憶させる記憶手段５と、前記ＲＧＢ情報取得手段３から取得された各検査部分のＲＧＢ輝度データと、前記記憶手段５に記憶されたＲＧＢ極座標系におけるＲＧＢ基準輝度データとを比較し、ＲＧＢ基準輝度データ内に検査対象物１１のＲＧＢ輝度データが含まれているか否かによって当該検査領域の良否を判定する判定手段８を備えるようにしたので、取得した検査領域におけるＲＧＢの輝度値が製品ごとに大きくばらついていたとしても、ＲＧＢのバランスを保った状態で輝度のみを大きく設定することができ、輝度のばらつきを吸収して高品質に検査させることができるようになる。 As described above, according to the embodiment, in the appearance inspection apparatus 1 that inspects the formation state of the inspection object 11 based on the image acquired from the inspection object 11, a color image is acquired from the inspection object 11. RGB information acquisition means 3 for acquiring RGB luminance data in the inspection portion of the inspection object 11, storage means 5 for storing RGB reference luminance data of each inspection portion in the RGB polar coordinate system with the axial direction as the luminance value, The RGB luminance data of each inspection part acquired from the RGB information acquisition unit 3 is compared with the RGB reference luminance data in the RGB polar coordinate system stored in the storage unit 5, and the inspection object 11 is included in the RGB reference luminance data. Since the determination means 8 for determining whether the inspection area is good or not is provided depending on whether or not the RGB luminance data is included. Even if the RGB luminance values in the inspection area vary greatly from product to product, only the luminance can be set large while maintaining the RGB balance, and the luminance variation can be absorbed and high quality inspection can be performed. become able to.
　また、検査対象物１１から取得されたＲＧＢ直交座標系の輝度データをＲＧＢ極座標系に変換させる変換テーブルを記憶させておき、この変換テーブルを用いて前記取得された各検査領域のＲＧＢ座標を変換させるようにしたので、各画素を検査する都度、座標変換のための演算をする必要がなく、検査時における処理速度を早くすることができる。 Further, a conversion table for converting the luminance data of the RGB orthogonal coordinate system acquired from the inspection object 11 into the RGB polar coordinate system is stored, and the RGB coordinates of each acquired inspection area are converted using this conversion table. Since each pixel is inspected, it is not necessary to perform an operation for coordinate conversion, and the processing speed at the time of inspection can be increased.
　さらに、ＲＧＢ基準輝度データを設定する場合、基準となる検査対象物１１の隣接する所定画素数のＲＧＢ輝度データを含むようにしたので、基準データと検査対象物１１とを画素単位で位置あわせしなくても検査することができ、虚報を減らして検査することができるようになる。 Further, when setting the RGB reference luminance data, the RGB luminance data of a predetermined number of pixels adjacent to the reference inspection object 11 is included, so that the reference data and the inspection object 11 are aligned in pixel units. It can be inspected without it, and it can be inspected with fewer false alarms.
　加えて、ＲＧＢの輝度を極座標系の輝度に変換した場合に、１バイトに収まるように輝度値を圧縮もしくは拡張させるようにしたので、変換後の輝度値を１バイトの範囲内に収めてデータを圧縮することができるようになる。 In addition, when the RGB luminance is converted to the polar coordinate luminance, the luminance value is compressed or expanded to fit within 1 byte, so the converted luminance value is stored within the 1-byte range. Can be compressed.
　なお、本発明は上記実施の形態に限定されることなく、種々の態様で実施することができる。 Note that the present invention is not limited to the above-described embodiment, and can be implemented in various modes.
　例えば、上記実施の形態では、補正処理手段６を用いて検査対象物１１の画像を補正処理したが、基準対象物１０の画像を補正処理するようにしてもよい。あるいは、完全に位置合わせできるような場合は、このような補正処理を行わないようにすることもできる。 For example, in the above-described embodiment, the correction processing unit 6 is used to correct the image of the inspection object 11, but the image of the reference object 10 may be corrected. Alternatively, such a correction process may not be performed when complete alignment is possible.
　また、上記実施の形態では、極座標に変換する変換テーブルをあらかじめ用意しておき、この変換テーブルを参照して直交座標系から極座標系に変換させるようにしているが、各画素毎に座標変換を演算するようにしてもよい。 In the above embodiment, a conversion table for converting to polar coordinates is prepared in advance, and the conversion table is referred to convert from the orthogonal coordinate system to the polar coordinate system. However, coordinate conversion is performed for each pixel. You may make it calculate.
　さらに、上記実施の形態では、プリント基板を検査する場合について説明したが、これ以外の外観検査を必要とする検査対象物１１にも適用することができる。 Furthermore, although the case where the printed circuit board is inspected has been described in the above embodiment, the present invention can also be applied to an inspection object 11 that requires an appearance inspection other than this.
　加えて、上記実施の形態では、各画素ごとに検査するようにしたが、所定の領域毎にＲＧＢ輝度データを収集して検査するようにしてもよい。この場合において、各領域毎に一つのＲＧＢ輝度データを演算し、この演算結果と極座標系で表現されたＲＧＢ基準輝度データとを比較するようにする。 In addition, in the above embodiment, each pixel is inspected, but RGB luminance data may be collected and inspected for each predetermined area. In this case, one RGB luminance data is calculated for each region, and the calculation result is compared with the RGB reference luminance data expressed in the polar coordinate system.
　また、上記実施の形態では、θやρを２５５×２／π倍に拡張するようにしたが、１バイトの範囲内に収まっているため、そのままの輝度値を用いるようにしてもよい。 In the above embodiment, θ and ρ are expanded to 255 × 2 / π times. However, since they are within the range of 1 byte, the luminance value may be used as it is.
　また、上記実施の形態では、１ピクセルのＲＧＢの要素を８ビットとしたため最大値を２５５としたが、これは２の諧調ビット乗－１の値であり、諧調ビットによってこの値を用いることができる。 In the above embodiment, since the RGB element of one pixel is 8 bits, the maximum value is set to 255. However, this is a value of 2 gradation bits raised to −1, and this value can be used depending on the gradation bits. it can.
本発明の一実施の形態における検査処理方法の概要を示す図The figure which shows the outline | summary of the inspection processing method in one embodiment of this invention 同形態における外観検査装置の機能ブロック図Functional block diagram of an appearance inspection apparatus in the same form 同形態における極座標系のＲＧＢ輝度基準データを示す図The figure which shows the RGB brightness | luminance reference data of the polar coordinate system in the same form 同形態における全体補正の処理の概要を示す図The figure which shows the outline | summary of the process of the whole correction | amendment in the same form 同形態における矩形領域の補正の処理の概要を示す図The figure which shows the outline | summary of the process of correction | amendment of the rectangular area in the same form 同形態における極座標変換テーブルを示す図The figure which shows the polar coordinate conversion table in the same form 同形態における基準データの生成フローを示す図The figure which shows the production | generation flow of the reference data in the form 同形態における検査処理のフローを示す図The figure which shows the flow of the inspection process in the same form 従来例における直交系のＲＧＢ輝度基準データを示す図The figure which shows the RGB luminance reference data of the orthogonal system in a prior art example
１・・・外観検査装置
２・・・撮像手段
３・・・ＲＧＢ情報取得手段
４・・・基準データ生成手段
５・・・記憶手段
６・・・補正処理手段
７・・・変換手段
８・・・判定手段
８０・・・画素判定手段
８１・・・第一の画素判定手段
８２・・・第二の画素判定手段
８３・・・クラスタ判定手段
９・・・出力手段
１０・・・基準対象物
１１・・・検査対象物 DESCRIPTION OF SYMBOLS 1 ... Appearance inspection apparatus 2 ... Imaging means 3 ... RGB information acquisition means 4 ... Reference data generation means 5 ... Storage means 6 ... Correction processing means 7 ... Conversion means 8- ..Determination means 80: Pixel determination means 81 ... First pixel determination means 82 ... Second pixel determination means 83 ... Cluster determination means 9 ... Output means 10 ... Reference object Object 11 ... Inspection object

Claims (4)

  1. 検査対象物から取得された画像に基づいて当該検査対象物の形成状態を検査する外観検査装置において、
    検査対象物からカラー画像を取得し、当該検査対象物の検査部分におけるＲＧＢ輝度データを取得するＲＧＢ情報取得手段と、
    軸方向を輝度値としたＲＧＢ極座標系で各検査部分のＲＧＢ基準輝度データを記憶させる基準データ記憶手段と、
    前記ＲＧＢ情報取得手段から取得された各検査部分のＲＧＢ輝度データを極座標系の輝度データに変換する変換手段と、
    当該変換された極座標系の輝度データと前記基準データ記憶手段に記憶されたＲＧＢ極座標系におけるＲＧＢ基準輝度データとを比較して、ＲＧＢ基準輝度データ内に検査対象物のＲＧＢ輝度データが含まれているか否かによって当該検査領域の良否を判定する判定手段とを備えたことを特徴とする外観検査装置。     In the appearance inspection apparatus that inspects the formation state of the inspection object based on the image acquired from the inspection object,
    RGB information acquisition means for acquiring a color image from an inspection object and acquiring RGB luminance data in an inspection part of the inspection object;
    Reference data storage means for storing RGB reference luminance data of each inspection portion in an RGB polar coordinate system with the axial direction as a luminance value;
    Conversion means for converting RGB luminance data of each inspection portion acquired from the RGB information acquisition means into luminance data of a polar coordinate system;
    The converted luminance data of the polar coordinate system is compared with the RGB reference luminance data in the RGB polar coordinate system stored in the reference data storage means, and the RGB luminance data of the inspection object is included in the RGB reference luminance data. An appearance inspection apparatus comprising: a determination unit that determines whether the inspection area is good or not based on whether or not the inspection area is present.
  2. 前記変換手段が、検査対象物から取得されたＲＧＢ直交座標系の輝度データをＲＧＢ極座標系に変換させる変換テーブルを記憶させ、当該変換テーブルを参照して前記取得された各検査部分のＲＧＢ座標を変換させるものである請求項１に記載の外観検査装置。 The conversion means stores a conversion table for converting luminance data in an RGB orthogonal coordinate system acquired from an inspection object into an RGB polar coordinate system, and refers to the conversion table to obtain the RGB coordinates of each acquired inspection portion. The appearance inspection apparatus according to claim 1, which is to be converted.
  3. 前記ＲＧＢ基準輝度データが、基準となる検査対象物の隣接する所定画素数のＲＧＢ輝度データを含むように設定されたものである請求項１に記載の外観検査装置。 The visual inspection apparatus according to claim 1, wherein the RGB reference luminance data is set to include RGB luminance data of a predetermined number of pixels adjacent to a reference inspection object.
  4. 前記変換手段が、ＲＧＢの輝度を極座標系の輝度に変換した場合に、１バイトに収まるように輝度値を圧縮もしくは拡張させるものである請求項１に記載の外観検査装置。 2. The appearance inspection apparatus according to claim 1, wherein the conversion unit compresses or expands the luminance value so as to be within one byte when the luminance of RGB is converted into luminance of a polar coordinate system.
PCT/JP2009/065711 2008-09-09 2009-09-09 Visual examination apparatus WO2010029932A1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN200980134031.3A CN102138068B (en) 2008-09-09 2009-09-09 Visual examination apparatus
JP2010528728A JP5084911B2 (en) 2008-09-09 2009-09-09 Appearance inspection device

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2008231006 2008-09-09
JP2008-231006 2008-09-09

Publications (1)

Publication Number Publication Date
WO2010029932A1 true WO2010029932A1 (en) 2010-03-18

Family

ID=42005185

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2009/065711 WO2010029932A1 (en) 2008-09-09 2009-09-09 Visual examination apparatus

Country Status (4)

Country Link
JP (1) JP5084911B2 (en)
KR (1) KR20110040965A (en)
CN (1) CN102138068B (en)
WO (1) WO2010029932A1 (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102881001A (en) * 2011-07-13 2013-01-16 富士通株式会社 Device and method for converting color image into grey scale image
JP2016050875A (en) * 2014-09-01 2016-04-11 明和工業株式会社 Surface state determination program and surface state determination device

Families Citing this family (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103529041B (en) * 2013-10-31 2015-07-29 广州华工机动车检测技术有限公司 Based on circuit board newness degree decision method and the system of characteristics of image
CN104362111B (en) * 2014-11-27 2017-02-01 阳光硅峰电子科技有限公司 Silicon wafer edge breakage automatic detection method
KR101694337B1 (en) * 2015-02-05 2017-01-09 동우 화인켐 주식회사 Method for inspecting film
CN104833681B (en) * 2015-05-13 2017-10-03 中国电子科技集团公司第三十八研究所 A kind of device and method of quick measurement MCM substrate circuits dimension of picture error
TWI579557B (en) * 2015-09-18 2017-04-21 Synpower Co Ltd Image detection method for printed substrate
CN110412052B (en) * 2019-08-12 2022-02-15 艾尔玛科技股份有限公司 Curved surface hot stamping quality detection method and system
CN110514675B (en) * 2019-08-29 2020-12-11 珠海格力电器股份有限公司 Intelligent detection method and system for label
TWI721632B (en) * 2019-11-05 2021-03-11 新加坡商鴻運科股份有限公司 Device and method for setting product detection threshold and storage medium
CN112785100B (en) * 2019-11-05 2023-10-31 富联精密电子(天津)有限公司 Product detection threshold setting device, method and computer readable storage medium
KR102436786B1 (en) 2020-04-16 2022-08-26 주식회사 에이비에이치 Apparatus and method for inspecting surface quality of appearance based on artificial intelligence

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH06109653A (en) * 1992-09-25 1994-04-22 Dainippon Printing Co Ltd Image inspecting apparatus
JPH11110560A (en) * 1997-10-03 1999-04-23 Mitsubishi Electric Corp Image inspection method and image inspection device
JP2004198146A (en) * 2002-12-16 2004-07-15 Mitsubishi Heavy Ind Ltd Printed matter color tone measurement method, printed matter color tone measurement device, and its program
JP2005509342A (en) * 2001-11-07 2005-04-07 ダバー ピシュバ Image highlight correction method using image source specific HSV color coordinates, image highlight correction program, and image acquisition system
JP2005233826A (en) * 2004-02-20 2005-09-02 Nippon Steel Corp Surface inspection device
JP2007309703A (en) * 2006-05-16 2007-11-29 Mega Trade:Kk Inspection method of pixel

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH06109653A (en) * 1992-09-25 1994-04-22 Dainippon Printing Co Ltd Image inspecting apparatus
JPH11110560A (en) * 1997-10-03 1999-04-23 Mitsubishi Electric Corp Image inspection method and image inspection device
JP2005509342A (en) * 2001-11-07 2005-04-07 ダバー ピシュバ Image highlight correction method using image source specific HSV color coordinates, image highlight correction program, and image acquisition system
JP2004198146A (en) * 2002-12-16 2004-07-15 Mitsubishi Heavy Ind Ltd Printed matter color tone measurement method, printed matter color tone measurement device, and its program
JP2005233826A (en) * 2004-02-20 2005-09-02 Nippon Steel Corp Surface inspection device
JP2007309703A (en) * 2006-05-16 2007-11-29 Mega Trade:Kk Inspection method of pixel

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102881001A (en) * 2011-07-13 2013-01-16 富士通株式会社 Device and method for converting color image into grey scale image
JP2016050875A (en) * 2014-09-01 2016-04-11 明和工業株式会社 Surface state determination program and surface state determination device

Also Published As

Publication number Publication date
JP5084911B2 (en) 2012-11-28
KR20110040965A (en) 2011-04-20
JPWO2010029932A1 (en) 2012-02-02
CN102138068B (en) 2015-02-11
CN102138068A (en) 2011-07-27

Similar Documents

Publication Publication Date Title
WO2010029932A1 (en) Visual examination apparatus
WO1998059213A1 (en) Pattern inspecting method and pattern inspecting device
KR20110115752A (en) Method of three dimensional mesurement
KR20080031677A (en) Surface inspecting apparatus
US20020047098A1 (en) Substrate defect inspection method and substrate defect inspection system
JP2007155610A (en) Visual examination device and visual examination method
JP4577717B2 (en) Bump inspection apparatus and method
KR101022187B1 (en) Substrate inspection device
KR101916134B1 (en) Inspection device of conformal coation on printed circuit board
WO2012144025A1 (en) Automatic inspection device and alignment method for automatic inspection device
JP2002005850A (en) Defect inspection method and apparatus therefor, and production method of mask
JP2005172584A (en) Inspection method of printed matter, and its inspection apparatus
JP4354173B2 (en) Appearance inspection equipment for electronic circuit components
JP2007309703A (en) Inspection method of pixel
JP2004125434A (en) Appearance examining method and device for electronic circuit component and method of manufacturing electronic circuit component
JP2006284543A (en) Method and device for inspecting mounted circuit board
US20040109602A1 (en) Method and apparatus for inspecting a bump electrode
JP2017198462A (en) Method for inspecting appearance
JP4354174B2 (en) Manufacturing method for electronic circuit components
JPH10150299A (en) Method and equipment for inspecting mounted component
JP2982413B2 (en) Common defect inspection method
JP2006329679A (en) Method and device for inspecting product pattern
JP4130848B2 (en) Pixel inspection method and pixel inspection apparatus
JP2010243214A (en) Method and device for detection of flaw
TW200842342A (en) Method, device, and program of inspecting wood

Legal Events

Date Code Title Description
WWE Wipo information: entry into national phase

Ref document number: 200980134031.3

Country of ref document: CN

121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 09813078

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 20117005023

Country of ref document: KR

Kind code of ref document: A

NENP Non-entry into the national phase

Ref country code: DE

ENP Entry into the national phase

Ref document number: 2010528728

Country of ref document: JP

Kind code of ref document: A

122 Ep: pct application non-entry in european phase

Ref document number: 09813078

Country of ref document: EP

Kind code of ref document: A1