CN116580022B - Workpiece size detection method, device, computer equipment and storage medium - Google Patents
Workpiece size detection method, device, computer equipment and storage medium Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
- G06T7/001—Industrial image inspection using an image reference approach
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/12—Edge-based segmentation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30164—Workpiece; Machine component
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The embodiment of the invention discloses a workpiece size detection method, a workpiece size detection device, computer equipment and a storage medium. The method comprises the following steps: collecting an image of a workpiece to be measured; preprocessing the workpiece image to be detected to obtain a preprocessing result; extracting a region corresponding to the region of interest of the standard template by adopting a template matching algorithm according to the pretreatment result to obtain an extraction result; extracting edge points from the extraction result by using a sub-pixel edge extraction method; performing ICP matching on the edge points and pixel edge point information of the standard template to obtain feature information of the workpiece to be detected; and calculating the dimension parameter of the workpiece to be measured according to the characteristic information of the workpiece to be measured. By implementing the method provided by the embodiment of the invention, the accuracy is improved, and the robustness, the anti-interference and the noise resistance are enhanced.
Description
Technical Field
The present invention relates to image measurement methods, and more particularly to a workpiece size detection method, apparatus, computer device, and storage medium.
Background
With the rapid development of industrialization, the requirements of human beings on industrial production are gradually increased, and the requirements on product quality are also higher and higher. The traditional manufacturing industry mainly relies on a method of manual measurement and manual adjustment of a machine in workpiece size detection, the measurement accuracy of the method is limited by the skills and experience of operators, interference of human factors exists, and errors are easy to occur; the manual measurement needs to consume a great deal of time and labor cost, and the efficiency is low; furthermore, manual measurement can only be performed on a single workpiece, and rapid detection and statistics of a large number of workpieces cannot be realized.
The automatic measurement technology of the size of the industrial workpiece has great significance for industrial production, can ensure that the product meets the specification requirement, avoids damage or degradation of the product, improves the production efficiency, reduces the cost, reduces the rejection rate, realizes the exchange and the universality among different production enterprises, and improves the efficiency and the competitiveness of the whole industrial field; at present, the automatic measurement technology of the size of a workpiece can be mainly divided into a 2D image measurement method and a 3D measurement method, wherein the 2D image measurement method uses a camera or a scanner to shoot or scan the workpiece, and then uses a 2D image processing technology to acquire the size information to be detected; the 3D measurement method generally photographs or scans a workpiece using a 3D camera or a 3D laser radar, and then acquires size information to be detected using the 3D information. Compared with the 3D technology, the 2D image has the main advantages of low cost, simple and convenient operation, rapid detection, easy integration and the like.
However, the accuracy of the 2D image measurement method is affected by many factors, such as the resolution of the camera, the surface quality of the workpiece, and the illumination condition, and in order to ensure the measurement accuracy, a higher requirement is put on the 2D measurement algorithm. Generally, a 2D image measurement method is based on accurate feature points or points to be measured, and only accurate feature points or points to be measured can be extracted for the next step, and a common image feature point extraction method mainly includes Harris corner detection, SIFT (Scale-invariant feature transform), SURF (accelerated robust feature, speeded Up Robust Features) and other feature point extraction, but an actual point to be measured may not be one of the feature points, so that a method for extracting some feature points cannot accurately find a desired feature point or point to be measured. Template matching is a commonly used computer vision technique that can find the most similar region in an image to a given template. When extracting key points of the workpiece image, important features or shapes in the workpiece can be identified by using template matching, and the method for extracting the feature points by using the template matching is NCC (Normalized cross correlation), SSD (square sum difference, sum of Squared Differences), SAD (absolute sum difference, sum of Absolute Differences), but the NCC has higher computational complexity; SSD is sensitive to factors such as illumination changes; SAD is sensitive to factors such as illumination change, and the current template matching method cannot realize that the current template matching method is easily affected by noise and shielding in a complex scene, and the accuracy cannot be guaranteed when the traditional template matching algorithm is used for completing 2D image measurement.
Therefore, it is necessary to design a new method to achieve improved accuracy and enhanced robustness, interference and noise immunity.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a workpiece size detection method, a device, computer equipment and a storage medium.
In order to achieve the above purpose, the present invention adopts the following technical scheme: a method of workpiece size detection, comprising:
collecting an image of a workpiece to be measured;
preprocessing the workpiece image to be detected to obtain a preprocessing result;
extracting a region corresponding to the region of interest of the standard template by adopting a template matching algorithm according to the pretreatment result to obtain an extraction result;
extracting edge points from the extraction result by using a sub-pixel edge extraction method;
performing ICP matching on the edge points and pixel edge point information of the standard template to obtain feature information of the workpiece to be detected;
and calculating the dimension parameter of the workpiece to be measured according to the characteristic information of the workpiece to be measured.
The further technical scheme is as follows: before the image of the workpiece to be detected is collected, the method further comprises the following steps:
constructing a standard template;
the standard template comprises an interested region, pixel coordinate values of points to be detected in the template and a set file of pixel edge point information extracted from the interested region.
The further technical scheme is as follows: the building of the standard template comprises the following steps:
shooting or scanning a standard workpiece to obtain a standard workpiece image;
extracting a region of interest in the standard workpiece image to obtain a template;
determining pixel coordinates of key feature points in a template, and determining pixel coordinate values of points to be measured in a standard workpiece image according to the pixel coordinates of the key feature points;
generating scale factors according to pixel coordinate values of the to-be-measured points in the standard workpiece image and actual coordinate information of the to-be-measured points;
and extracting pixel edge point information from each template to form a set file of the pixel edge point information.
The further technical scheme is as follows: the preprocessing of the workpiece image to be detected to obtain a preprocessing result comprises the following steps:
and denoising, enhancing and binarizing the image of the workpiece to be detected to obtain a preprocessing result.
The further technical scheme is as follows: the characteristic information of the workpiece to be detected comprises pixel coordinates of two or more points to be detected of the workpiece to be detected;
performing ICP matching on the edge points and pixel edge point information of the standard template to obtain feature information of the workpiece to be detected, wherein the ICP matching comprises the following steps:
Performing ICP registration on the pixel edge point information of the edge points and the standard template to obtain a rigid body transformation relation between two point sets;
and converting pixel coordinate values of the to-be-measured point in the standard template in the region of interest according to the rigid transformation relation between the two point sets so as to obtain the feature information of the to-be-measured workpiece.
The further technical scheme is as follows: and when the pixel edge point information of the edge point and the standard template is subjected to ICP matching to obtain the feature information of the workpiece to be detected, setting a distance threshold value, and automatically filtering edge points generated by the interference objects based on the distance threshold value.
The further technical scheme is as follows: the calculating the dimension parameter of the workpiece to be measured according to the characteristic information of the workpiece to be measured comprises the following steps:
positioning to an ROI (region of interest) of the workpiece to be detected according to the characteristic information of the workpiece to be detected;
extracting sub-pixel edge information from the ROI area of the workpiece to be detected;
fitting the sub-pixel edge information to a straight line to obtain a dimension measurement reference line;
projecting the feature information of the workpiece to be measured onto the dimension measurement reference line to obtain projected pixel coordinates;
and calculating the distance between the points to be measured corresponding to the projected pixel coordinates, and multiplying the distance between the points to be measured corresponding to the projected pixel coordinates by a scale factor to obtain the size parameters of the workpiece to be measured.
The invention also provides a workpiece size detection device, which comprises:
the image acquisition unit to be measured is used for acquiring the image of the workpiece to be measured;
the preprocessing unit is used for preprocessing the workpiece image to be detected to obtain a preprocessing result;
the region extraction unit is used for extracting a region corresponding to the region of interest of the standard template by adopting a template matching algorithm according to the preprocessing result so as to obtain an extraction result;
an edge point extraction unit for extracting edge points from the extraction result by using a sub-pixel edge extraction method;
the matching unit is used for carrying out ICP matching on the edge points and the pixel edge point information of the standard template so as to obtain feature information of the workpiece to be detected;
and the calculating unit is used for calculating the dimension parameter of the workpiece to be measured according to the characteristic information of the workpiece to be measured.
The invention also provides a computer device which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the method when executing the computer program.
The present invention also provides a storage medium storing a computer program which, when executed by a processor, implements the above method.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, the template matching algorithm is adopted to extract the region corresponding to the 2D image of the workpiece to be detected and the region of interest of the standard template, the sub-pixel edge extraction method is adopted to extract the edge points of the extracted region, the ICP matching is carried out on the pixel edge point information of the edge points and the standard template, and the size parameter calculation is carried out according to the matching result, so that the improvement of the precision is realized, and the robustness, the anti-interference and the anti-noise capability is enhanced.
The invention is further described below with reference to the drawings and specific embodiments.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of an application scenario of a workpiece size detection method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for detecting a dimension of a workpiece according to an embodiment of the invention;
FIG. 3 is a schematic flow chart of a method for detecting the size of a workpiece according to an embodiment of the invention;
FIG. 4 is a schematic flow chart of a method for detecting the size of a workpiece according to an embodiment of the invention;
FIG. 5 is a flow chart of a method for detecting a dimension of a workpiece according to another embodiment of the invention;
FIG. 6 is a schematic flow chart illustrating a method for detecting a dimension of a workpiece according to another embodiment of the invention;
FIG. 7 is a schematic block diagram of a workpiece size detection device provided by an embodiment of the invention;
FIG. 8 is a schematic block diagram of a matching unit of a workpiece size detection device provided by an embodiment of the invention;
FIG. 9 is a schematic block diagram of a calculation unit of a workpiece size detection device provided by an embodiment of the invention;
FIG. 10 is a schematic block diagram of a workpiece size detection device according to another embodiment of the invention;
FIG. 11 is a schematic block diagram of a construction unit of a workpiece size detection device provided in another embodiment of the invention;
FIG. 12 is a schematic block diagram of a computer device provided by an embodiment of the present invention;
FIG. 13 is a schematic view of a master workpiece according to an embodiment of the present invention;
FIG. 14 is a schematic view of a standard workpiece image according to an embodiment of the present invention;
FIG. 15 is a schematic view of a first region of interest in a standard workpiece image according to an embodiment of the present invention;
FIG. 16 is a schematic diagram of a second region of interest in a standard workpiece image according to an embodiment of the present invention;
FIG. 17 is a diagram illustrating pixel coordinate values of a first region of interest in a standard workpiece image according to an embodiment of the present invention;
FIG. 18 is a diagram illustrating pixel coordinate values of a second region of interest in a standard workpiece image according to an embodiment of the present invention;
FIG. 19 is a schematic diagram of pixel edge point information of a first region of interest in a standard workpiece image according to an embodiment of the present invention;
FIG. 20 is a schematic diagram of pixel edge point information of a second region of interest in a standard workpiece image according to an embodiment of the present invention;
FIG. 21 is a schematic view of a region of interest of an image pair of a workpiece to be measured according to an embodiment of the present invention;
FIG. 22 is a schematic diagram of a ROI area of a workpiece to be measured after positioning according to an embodiment of the present invention;
FIG. 23 is a schematic diagram of a dimension measurement reference line provided by an embodiment of the present invention;
fig. 24 is a schematic diagram of edge points generated by an interferent according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be understood that the terms "comprises" and "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
Referring to fig. 1 and fig. 2, fig. 1 is a schematic view of an application scenario of a workpiece size detection method according to an embodiment of the invention. Fig. 2 is a schematic flow chart of a workpiece size detection method according to an embodiment of the invention. The workpiece size detection method is applied to a server. The server performs data interaction with a camera or a scanner, the workpiece to be detected is shot or scanned by the camera or the scanner to form a workpiece image to be detected, the workpiece image to be detected is preprocessed by the server, an ROI (region of interest ) area corresponding to a standard template is extracted by a template matching algorithm, edge points are extracted by a sub-pixel edge extraction method, ICP (iterative closest point ) matching is performed, workpiece size parameters are calculated according to matching results, and 2D image measurement is completed by combining a sub-pixel edge reinforced template matching algorithm.
Fig. 2 is a flow chart of a workpiece size detection method according to an embodiment of the invention. As shown in fig. 2, the method includes the following steps S110 to S160.
S110, collecting an image of the workpiece to be detected.
In this embodiment, the workpiece image to be measured is a 2D image formed by shooting or scanning the workpiece to be measured with a camera or a scanner.
S120, preprocessing the workpiece image to be detected to obtain a preprocessing result.
In this embodiment, the preprocessing result refers to an image formed after the image is processed by a means for extracting the workpiece features more accurately.
Specifically, denoising, enhancing and binarizing the workpiece image to be detected to obtain a preprocessing result.
Denoising, enhancing and binarizing the image belong to the prior art, and are not described here.
And S130, extracting a region corresponding to the region of interest of the standard template by adopting a template matching algorithm according to the preprocessing result so as to obtain an extraction result.
In this embodiment, the extraction result refers to a region corresponding to a region of interest corresponding to a standard template in the preprocessing result, as shown in fig. 21.
The region corresponding to the region of interest corresponding to the standard template in the preprocessing result is extracted by using a template matching mode, which belongs to the prior art and is not described herein.
And S140, extracting edge points from the extraction result by using a sub-pixel edge extraction method.
In this embodiment, the edge points refer to pixel edge points of the extraction result.
The manner of extracting pixel edge points by using the sub-pixel edge extraction method belongs to the prior art, and is not described here again.
And S150, carrying out ICP matching on the edge points and pixel edge point information of the standard template to obtain feature information of the workpiece to be detected.
In this embodiment, the feature information of the workpiece to be measured includes pixel coordinates of two or more points to be measured of the workpiece to be measured.
And carrying out ICP matching on the edge points and the pixel edge point information of the corresponding template, thereby extracting accurate workpiece features.
In one embodiment, referring to fig. 3, the step S150 may include steps S151 to S152.
And S151, carrying out ICP registration on the edge points and the pixel edge point information of the standard template to obtain a rigid body transformation relation between the two point sets.
In this embodiment, the rigid transformation relationship between the two point sets refers to a rigid transformation matrix between an edge point on the workpiece to be measured and pixel edge point information in the standard template after ICP registration is adopted.
Specifically, a distance threshold is set, and edge points generated by interference objects are automatically filtered based on the distance threshold.
S152, converting pixel coordinate values of the points to be measured in the standard template in the region of interest according to the rigid transformation relation between the two point sets so as to obtain feature information of the workpiece to be measured.
In this embodiment, the iterative closest point algorithm is a common technique in point cloud registration, and adopts an iterative idea, and searches for corresponding points of two point clouds and calculates a rigid transformation matrix between the point clouds in each iteration. In the iterative closest point algorithm, there are two point clouds, one of which is a target point cloud A (pixel edge point information of a standard template) and the other is a reference point cloud B (edge point of sub-pixel is extracted from the region identified by the currently acquired workpiece image to be measured), and the purpose of the ICP algorithm is to calculate an optimal rigidity transformationAnd->So that the transformed point cloud A can be matched with B most accurately, wherein +.>Representing a rotation matrix>Representing translation vector, R and t are when the right value of the formula reaches minimumThe->And->。；/>The method comprises the steps of carrying out a first treatment on the surface of the ICP needs to repeatedly perform the following two steps until convergence: step one, calculating matching point pairs between an A point set and a B point set; and step two, calculating a conversion matrix between the A point set and the B point set according to the matching pair obtained in the previous step, and transforming the A point set according to the calculated conversion matrix.
And detecting and collecting pixel coordinates of two or more to-be-measured points in the image of the workpiece to be measured according to the mode, namely finishing corresponding dimension measurement according to the specific condition of the workpiece and the scale factor lambda.
S160, calculating the dimension parameter of the workpiece to be measured according to the characteristic information of the workpiece to be measured.
In one embodiment, referring to fig. 4, the step S160 may include steps S161 to S165.
S161, positioning the ROI of the workpiece to be detected according to the characteristic information of the workpiece to be detected.
In this embodiment, the ROI area of the workpiece to be measured can be constructed by two coordinates of points to be measured, a reference area is selected according to the coordinates of the two points to be measured, the top surface of the reference area is used as a reference line, and the two points are projected onto the line to calculate the size, as shown in fig. 22. .
S162, extracting sub-pixel edge information from the ROI area of the workpiece to be detected.
In this embodiment, a subpixel edge point extraction technique is used to extract subpixel edge information from the ROI area of the workpiece to be measured.
S163, fitting the sub-pixel edge information to a straight line to obtain a dimension measurement reference line.
In this embodiment, a straight line is fitted according to the edge point corresponding to the sub-pixel edge information, and the straight line is used as a dimension measurement reference line, as shown in fig. 23.
S164, projecting the feature information of the workpiece to be measured onto the dimension measurement reference line to obtain projected pixel coordinates;
s165, calculating the distance between the points to be measured corresponding to the projected pixel coordinates, and multiplying the distance between the points to be measured corresponding to the projected pixel coordinates by a scale factor to obtain the size parameter of the workpiece to be measured.
In this embodiment, the extracted pixel coordinates of two points to be measured are projected onto the dimension measurement reference line to obtain two projected pixel coordinates, a distance value distance_1 (under the pixel coordinate system) between the two projected points is calculated, and a scale factor λ is multiplied by the distance value distance_pixel to obtain a distance value distance_2 under the euclidean space, where the distance_2 is dimension information to be measured, that is, dimension parameters of the workpiece to be measured.
In the actual measurement process, because some flocks or interferents possibly adsorbed on the workpiece to be measured can be displayed in the image, if the sundries just appear near the area to be detected, pixels of the interferents in the traditional template matching algorithm can participate in the algorithm matching under the condition, and the recognition accuracy is obviously affected. According to the method, sub-pixel edge information is further extracted from the identified ROI area on the basis of identification of a traditional template matching algorithm, ICP registration is conducted on the sub-pixel edge information and an edge point set file of a template database, ICP registration is conducted on edge points with more obvious features, the edge points generated by the interference are automatically filtered by a distance threshold when the nearest matching point is sought in ICP registration, the distance threshold is because the edge points generated by the interference are far away from the edge points of a real template in general, the edge points actually participating in final matching are not affected, and matching accuracy is not affected, so that overall identification accuracy is improved, and the edge points generated by the interference are shown in fig. 24.
According to the workpiece size detection method, the template matching algorithm is adopted to extract the region, corresponding to the region of interest, of the 2D image of the workpiece to be detected and the standard template, the sub-pixel edge extraction method is adopted to extract the edge points of the extracted region, the ICP matching is carried out on the pixel edge point information of the edge points and the standard template, and the size parameter calculation is carried out according to the matching result, so that the effects of improving the accuracy, and enhancing the robustness, the anti-interference and the anti-noise capability are achieved.
Fig. 5 is a flowchart of a workpiece size detection method according to another embodiment of the invention. As shown in fig. 5, the workpiece size detection method of the present embodiment includes steps S210 to S270. Steps S220 to S270 are similar to steps S110 to S160 in the above embodiment, and are not described herein. Step S210 added in the present embodiment is described in detail below.
S210, constructing a standard template.
In this embodiment, the standard template includes an interested region, pixel coordinate values of the point to be detected in the template, and a set file of pixel edge point information extracted from the interested region.
In one embodiment, referring to fig. 6, the step S210 may include steps S211 to S215.
S211, shooting or scanning the standard workpiece to obtain a standard workpiece image.
In this embodiment, a good workpiece is selected, as shown in fig. 13, to ensure that the outer surface of the good workpiece is free from dirt, and the workpiece is placed in a measurement scene, that is, the environment configuration is ensured to be consistent with that of the actual work, so that a clear photo I of the workpiece is obtained, as shown in fig. 14, and the photo I is a standard workpiece image.
S212, extracting the region of interest in the standard workpiece image to obtain a template.
In this embodiment, one or more regions of interest including points to be measured of the standard workpiece are manually cut from the photograph I, in this embodiment, only two regions of interest are selected, and in other embodiments, not limited to two, there may be any number, as shown in fig. 15 and 16.
S213, determining pixel coordinates of the key feature points in the template, and determining pixel coordinate values of the to-be-measured points in the standard workpiece image according to the pixel coordinates of the key feature points.
In the present embodiment, the pixel coordinates of the point to be measured in the region of interest are found from each region of interest by manual scaling or the like, and the pixel coordinates of the point to be measured in the whole photo are calculated in combination with the position of the region of interest in the whole photo, as shown in fig. 17 and 18.
S214, generating scale factors according to pixel coordinate values of the to-be-measured points in the standard workpiece image and actual coordinate information of the to-be-measured points.
In this embodiment, there are two or more pixel coordinates of the point to be measured on the whole image, and the coordinate information of the point to be measured on the workpiece is measured by combining with a precise measuring tool, so that the scale factor λ of the conversion between the pixel coordinates and the actual size information can be completed, thereby completing the calibration between the two sizes.
S215, extracting pixel edge point information for each template to form a collection file of the pixel edge point information.
In this embodiment, the sub-pixel edge point extraction technique may be used to extract sub-pixel edge information for each region of interest as shown in fig. 19 and 20.
Fig. 7 is a schematic block diagram of a workpiece size detection device 300 according to an embodiment of the invention. As shown in fig. 7, the present invention also provides a workpiece size detecting apparatus 300 corresponding to the above workpiece size detecting method. The workpiece size detection apparatus 300 includes means for performing the workpiece size detection method described above, and may be configured in a server. Specifically, referring to fig. 7, the workpiece size detection device 300 includes a to-be-detected image acquisition unit 302, a preprocessing unit 303, a region extraction unit 304, an edge point extraction unit 305, a matching unit 306, and a calculation unit 307.
The image to be measured acquisition unit 302 is used for acquiring an image of the workpiece to be measured; a preprocessing unit 303, configured to preprocess the workpiece image to be detected to obtain a preprocessing result; the region extraction unit 304 is configured to extract a region corresponding to the region of interest of the standard template by using a template matching algorithm according to the preprocessing result, so as to obtain an extraction result; an edge point extraction unit 305 for extracting edge points using a sub-pixel edge extraction method for the extraction result; the matching unit 306 is configured to perform ICP matching on the edge point and pixel edge point information of the standard template to obtain feature information of the workpiece to be detected, specifically, set a distance threshold, and automatically filter edge points generated by the interference object based on the distance threshold; and a calculating unit 307, configured to calculate a dimension parameter of the workpiece to be measured according to the feature information of the workpiece to be measured.
In an embodiment, the preprocessing unit 303 is configured to perform denoising, enhancement, and binarization processing on the workpiece image to be detected, so as to obtain a preprocessing result.
In one embodiment, as shown in fig. 8, the matching unit 306 includes a registration subunit 3061 and a conversion subunit 3062.
A registration subunit 3061, configured to perform ICP registration on the edge points and pixel edge point information of the standard template, so as to obtain a rigid transformation relationship between two point sets; and the conversion subunit 3062 is used for converting pixel coordinate values of the to-be-measured point in the region of interest in the standard template according to the rigid transformation relation between the two point sets so as to obtain the feature information of the to-be-measured workpiece.
In one embodiment, as shown in fig. 9, the calculating unit 307 includes a positioning subunit 3071, an edge information extracting subunit 3072, a fitting subunit 3073, a projecting subunit 3074, and a distance calculating subunit 3075.
A positioning subunit 3071, configured to position the ROI area of the workpiece to be measured according to the feature information of the workpiece to be measured; an edge information extraction subunit 3072, configured to extract sub-pixel edge information from the ROI area of the workpiece to be measured; a fitting subunit 3073, configured to fit the subpixel edge information to a straight line, so as to obtain a dimension measurement reference line; a projection subunit 3074, configured to project the feature information of the workpiece to be measured onto the dimension measurement reference line, so as to obtain a projected pixel coordinate; the distance calculating subunit 3075 is configured to calculate a distance between the points to be measured corresponding to the projected pixel coordinates, and multiply the distance between the points to be measured corresponding to the projected pixel coordinates by the scale factor to obtain the size parameter of the workpiece to be measured.
Fig. 10 is a schematic block diagram of a workpiece size detection device 300 according to another embodiment of the invention. As shown in fig. 10, the workpiece size detecting apparatus 300 of the present embodiment is an addition of the construction unit 301 to the above-described embodiment.
A construction unit 301 for constructing a standard template.
In one embodiment, as shown in fig. 11, the construction unit 301 includes a standard workpiece scanning subunit 3011, an area extraction subunit 3012, a coordinate determination subunit 3013, a factor generation subunit 3014, and a file formation subunit 3015.
A standard workpiece scanning subunit 3011, configured to capture or scan a standard workpiece to obtain a standard workpiece image; a region extraction subunit 3012, configured to extract a region of interest in the standard workpiece image, so as to obtain a template; the coordinate determination subunit 3013 is configured to determine pixel coordinates of the key feature points in the template, and determine pixel coordinate values of the to-be-measured points in the standard workpiece image according to the pixel coordinates of the key feature points; the factor generation subunit 3014 is used for generating scale factors according to pixel coordinate values of the to-be-measured point in the standard workpiece image and actual coordinate information of the to-be-measured point; a file forming subunit 3015, configured to extract pixel edge point information for each template, and form a set file of pixel edge point information.
It should be noted that, as will be clearly understood by those skilled in the art, the specific implementation process of the workpiece size detection device 300 and each unit may refer to the corresponding description in the foregoing method embodiments, and for convenience and brevity of description, the description is omitted here.
The workpiece size detection device 300 described above may be implemented in the form of a computer program that is executable on a computer apparatus as shown in fig. 12.
Referring to fig. 12, fig. 12 is a schematic block diagram of a computer device according to an embodiment of the present application. The computer device 500 may be a server, where the server may be a stand-alone server or may be a server cluster formed by a plurality of servers.
With reference to FIG. 12, the computer device 500 includes a processor 502, memory, and a network interface 505 connected by a system bus 501, where the memory may include a non-volatile storage medium 503 and an internal memory 504.
The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions that, when executed, cause the processor 502 to perform a workpiece size detection method.
The processor 502 is used to provide computing and control capabilities to support the operation of the overall computer device 500.
The internal memory 504 provides an environment for the execution of a computer program 5032 in the non-volatile storage medium 503, which computer program 5032, when executed by the processor 502, causes the processor 502 to perform a method of workpiece size detection.
The network interface 505 is used for network communication with other devices. It will be appreciated by those skilled in the art that the structure shown in FIG. 12 is merely a block diagram of some of the structures associated with the present inventive arrangements and does not constitute a limitation of the computer device 500 to which the present inventive arrangements may be applied, and that a particular computer device 500 may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
Wherein the processor 502 is configured to execute a computer program 5032 stored in a memory to implement the steps of:
collecting an image of a workpiece to be measured; preprocessing the workpiece image to be detected to obtain a preprocessing result; extracting a region corresponding to the region of interest of the standard template by adopting a template matching algorithm according to the pretreatment result to obtain an extraction result; extracting edge points from the extraction result by using a sub-pixel edge extraction method; performing ICP matching on the edge points and pixel edge point information of the standard template to obtain feature information of the workpiece to be detected; and calculating the dimension parameter of the workpiece to be measured according to the characteristic information of the workpiece to be measured.
The characteristic information of the workpiece to be measured comprises pixel coordinates of two or more points to be measured of the workpiece to be measured.
In one embodiment, before implementing the step of capturing an image of the workpiece to be measured, the processor 502 further implements the following steps:
and constructing a standard template.
The standard template comprises an interested region, pixel coordinate values of points to be detected in the template and a set file of pixel edge point information extracted from the interested region.
In one embodiment, when implementing the step of building a standard template, the processor 502 specifically implements the following steps:
shooting or scanning a standard workpiece to obtain a standard workpiece image; extracting a region of interest in the standard workpiece image to obtain a template; determining pixel coordinates of key feature points in a template, and determining pixel coordinate values of points to be measured in a standard workpiece image according to the pixel coordinates of the key feature points; generating scale factors according to pixel coordinate values of the to-be-measured points in the standard workpiece image and actual coordinate information of the to-be-measured points; and extracting pixel edge point information from each template to form a set file of the pixel edge point information.
In an embodiment, when the step of preprocessing the image of the workpiece to be detected to obtain a preprocessing result is implemented by the processor 502, the following steps are specifically implemented:
And denoising, enhancing and binarizing the image of the workpiece to be detected to obtain a preprocessing result.
In an embodiment, when the step of performing ICP matching on the edge point and the pixel edge point information of the standard template to obtain feature information of the workpiece to be measured, the processor 502 specifically performs the following steps:
performing ICP registration on the pixel edge point information of the edge points and the standard template to obtain a rigid body transformation relation between two point sets; and converting pixel coordinate values of the to-be-measured point in the standard template in the region of interest according to the rigid transformation relation between the two point sets so as to obtain the feature information of the to-be-measured workpiece.
In an embodiment, when the step of performing ICP matching on the edge point and the pixel edge point information of the standard template to obtain feature information of the workpiece to be measured, the processor 502 specifically performs the following steps:
and setting a distance threshold value, and automatically filtering out edge points generated by the interference objects based on the distance threshold value.
In one embodiment, the processor 502 performs the following steps when performing the step of calculating the dimension parameter of the workpiece to be measured according to the feature information of the workpiece to be measured:
Positioning to an ROI (region of interest) of the workpiece to be detected according to the characteristic information of the workpiece to be detected; extracting sub-pixel edge information from the ROI area of the workpiece to be detected; fitting the sub-pixel edge information to a straight line to obtain a dimension measurement reference line; projecting the feature information of the workpiece to be measured onto the dimension measurement reference line to obtain projected pixel coordinates; and calculating the distance between the points to be measured corresponding to the projected pixel coordinates, and multiplying the distance between the points to be measured corresponding to the projected pixel coordinates by a scale factor to obtain the size parameters of the workpiece to be measured.
It should be appreciated that in an embodiment of the application, the processor 502 may be a central processing unit (Central Processing Unit, CPU), the processor 502 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSPs), application specific integrated circuits (Application Specific Integrated Circuit, ASICs), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Those skilled in the art will appreciate that all or part of the flow in a method embodying the above described embodiments may be accomplished by computer programs instructing the relevant hardware. The computer program comprises program instructions, and the computer program can be stored in a storage medium, which is a computer readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the flow steps of the embodiments of the method described above.
Accordingly, the present invention also provides a storage medium. The storage medium may be a computer readable storage medium. The storage medium stores a computer program which, when executed by a processor, causes the processor to perform the steps of:
collecting an image of a workpiece to be measured; preprocessing the workpiece image to be detected to obtain a preprocessing result; extracting a region corresponding to the region of interest of the standard template by adopting a template matching algorithm according to the pretreatment result to obtain an extraction result; extracting edge points from the extraction result by using a sub-pixel edge extraction method; performing ICP matching on the edge points and pixel edge point information of the standard template to obtain feature information of the workpiece to be detected; and calculating the dimension parameter of the workpiece to be measured according to the characteristic information of the workpiece to be measured.
The characteristic information of the workpiece to be measured comprises pixel coordinates of two or more points to be measured of the workpiece to be measured.
In one embodiment, before the step of capturing the image of the workpiece to be measured is implemented by the processor executing the computer program, the following steps are further implemented:
and constructing a standard template.
The standard template comprises an interested region, pixel coordinate values of points to be detected in the template and a set file of pixel edge point information extracted from the interested region.
In one embodiment, the processor, when executing the computer program to implement the step of building the standard template, specifically implements the following steps:
shooting or scanning a standard workpiece to obtain a standard workpiece image; extracting a region of interest in the standard workpiece image to obtain a template; determining pixel coordinates of key feature points in a template, and determining pixel coordinate values of points to be measured in a standard workpiece image according to the pixel coordinates of the key feature points; generating scale factors according to pixel coordinate values of the to-be-measured points in the standard workpiece image and actual coordinate information of the to-be-measured points; and extracting pixel edge point information from each template to form a set file of the pixel edge point information.
In one embodiment, when the processor executes the computer program to perform the preprocessing on the image of the workpiece to be detected to obtain a preprocessing result, the following steps are specifically implemented:
and denoising, enhancing and binarizing the image of the workpiece to be detected to obtain a preprocessing result.
In an embodiment, when the processor executes the computer program to perform the step of performing ICP matching on the edge point and pixel edge point information of the standard template to obtain feature information of the workpiece to be measured, the processor specifically performs the following steps:
performing ICP registration on the pixel edge point information of the edge points and the standard template to obtain a rigid body transformation relation between two point sets; and converting pixel coordinate values of the to-be-measured point in the standard template in the region of interest according to the rigid transformation relation between the two point sets so as to obtain the feature information of the to-be-measured workpiece.
In an embodiment, when the processor executes the computer program to perform the step of performing ICP matching on the edge point and pixel edge point information of the standard template to obtain feature information of the workpiece to be measured, the processor specifically performs the following steps:
And setting a distance threshold value, and automatically filtering out edge points generated by the interference objects based on the distance threshold value.
In one embodiment, when the processor executes the computer program to implement the step of calculating the dimension parameter of the workpiece to be measured according to the characteristic information of the workpiece to be measured, the processor specifically implements the following steps:
positioning to an ROI (region of interest) of the workpiece to be detected according to the characteristic information of the workpiece to be detected; extracting sub-pixel edge information from the ROI area of the workpiece to be detected; fitting the sub-pixel edge information to a straight line to obtain a dimension measurement reference line; projecting the feature information of the workpiece to be measured onto the dimension measurement reference line to obtain projected pixel coordinates; and calculating the distance between the points to be measured corresponding to the projected pixel coordinates, and multiplying the distance between the points to be measured corresponding to the projected pixel coordinates by a scale factor to obtain the size parameters of the workpiece to be measured.
The storage medium may be a U-disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk, or other various computer-readable storage media that can store program codes.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of each unit is only one logic function division, and there may be another division manner in actual implementation. For example, multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed.
The steps in the method of the embodiment of the invention can be sequentially adjusted, combined and deleted according to actual needs. The units in the device of the embodiment of the invention can be combined, divided and deleted according to actual needs. In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The integrated unit may be stored in a storage medium if implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention is essentially or a part contributing to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a terminal, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention.
While the invention has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (6)
1. A method of workpiece size detection, comprising:
collecting an image of a workpiece to be measured;
preprocessing the workpiece image to be detected to obtain a preprocessing result;
extracting a region corresponding to the region of interest of the standard template by adopting a template matching algorithm according to the pretreatment result to obtain an extraction result;
extracting edge points from the extraction result by using a sub-pixel edge extraction method;
performing ICP matching on the edge points and pixel edge point information of the standard template to obtain feature information of the workpiece to be detected;
calculating the dimension parameter of the workpiece to be measured according to the characteristic information of the workpiece to be measured;
the preprocessing of the workpiece image to be detected to obtain a preprocessing result comprises the following steps:
denoising, enhancing and binarizing the image of the workpiece to be detected to obtain a preprocessing result;
The characteristic information of the workpiece to be detected comprises pixel coordinates of two or more points to be detected of the workpiece to be detected;
performing ICP matching on the edge points and pixel edge point information of the standard template to obtain feature information of the workpiece to be detected, wherein the ICP matching comprises the following steps:
performing ICP registration on the pixel edge point information of the edge points and the standard template to obtain a rigid body transformation relation between two point sets;
converting pixel coordinate values of points to be measured in the standard template in the region of interest according to the rigid transformation relationship between the two point sets to obtain feature information of the workpiece to be measured;
performing ICP matching on the edge points and pixel edge point information of the standard template to obtain feature information of the workpiece to be detected, setting a distance threshold, and automatically filtering edge points generated by interference objects based on the distance threshold;
the calculating the dimension parameter of the workpiece to be measured according to the characteristic information of the workpiece to be measured comprises the following steps:
positioning to an ROI (region of interest) of the workpiece to be detected according to the characteristic information of the workpiece to be detected;
extracting sub-pixel edge information from the ROI area of the workpiece to be detected;
fitting the sub-pixel edge information to a straight line to obtain a dimension measurement reference line;
Projecting the feature information of the workpiece to be measured onto the dimension measurement reference line to obtain projected pixel coordinates;
and calculating the distance between the points to be measured corresponding to the projected pixel coordinates, and multiplying the distance between the points to be measured corresponding to the projected pixel coordinates by a scale factor to obtain the size parameters of the workpiece to be measured.
2. The method of claim 1, wherein before capturing the image of the workpiece to be measured, further comprising:
constructing a standard template; the standard template comprises an interested region, pixel coordinate values of points to be detected in the template and a set file of pixel edge point information extracted from the interested region.
3. The method of claim 2, wherein constructing the standard template comprises:
shooting or scanning a standard workpiece to obtain a standard workpiece image;
extracting a region of interest in the standard workpiece image to obtain a template;
determining pixel coordinates of key feature points in a template, and determining pixel coordinate values of points to be measured in a standard workpiece image according to the pixel coordinates of the key feature points;
generating scale factors according to pixel coordinate values of the to-be-measured points in the standard workpiece image and actual coordinate information of the to-be-measured points;
And extracting pixel edge point information from each template to form a set file of the pixel edge point information.
4. Workpiece size detection device, its characterized in that includes:
the image acquisition unit to be measured is used for acquiring the image of the workpiece to be measured;
the preprocessing unit is used for preprocessing the workpiece image to be detected to obtain a preprocessing result;
the region extraction unit is used for extracting a region corresponding to the region of interest of the standard template by adopting a template matching algorithm according to the preprocessing result so as to obtain an extraction result;
an edge point extraction unit for extracting edge points from the extraction result by using a sub-pixel edge extraction method;
the matching unit is used for carrying out ICP matching on the edge points and the pixel edge point information of the standard template so as to obtain feature information of the workpiece to be detected; setting a distance threshold value, and automatically filtering edge points generated by the interference objects based on the distance threshold value;
the calculating unit is used for calculating the dimension parameter of the workpiece to be measured according to the characteristic information of the workpiece to be measured; the characteristic information of the workpiece to be detected comprises pixel coordinates of two or more points to be detected of the workpiece to be detected;
the preprocessing unit is used for denoising, enhancing and binarizing the workpiece image to be detected to obtain a preprocessing result;
The matching unit comprises a registration subunit and a conversion subunit;
the registration subunit is used for carrying out ICP registration on the pixel edge point information of the edge point and the standard template to obtain a rigid body transformation relation between the two point sets; the conversion subunit is used for converting pixel coordinate values of the points to be measured in the standard template in the region of interest according to the rigid transformation relation between the two point sets so as to obtain feature information of the workpiece to be measured;
the computing unit comprises a positioning subunit, an edge information extracting subunit, a fitting subunit, a projection subunit and a distance computing subunit;
the positioning subunit is used for positioning the ROI of the workpiece to be detected according to the characteristic information of the workpiece to be detected; an edge information extraction subunit, configured to extract sub-pixel edge information from an ROI area of a workpiece to be measured; a fitting subunit, configured to fit the subpixel edge information to a straight line, so as to obtain a dimension measurement reference line; the projection subunit is used for projecting the characteristic information of the workpiece to be measured onto the dimension measurement reference line so as to obtain projected pixel coordinates; and the distance calculating subunit is used for calculating the distance between the points to be measured corresponding to the projected pixel coordinates, and multiplying the distance between the points to be measured corresponding to the projected pixel coordinates by the scale factor to obtain the dimension parameter of the workpiece to be measured.
5. A computer device, characterized in that it comprises a memory on which a computer program is stored and a processor which, when executing the computer program, implements the method according to any of claims 1-3.
6. A storage medium storing a computer program which, when executed by a processor, implements the method of any one of claims 1 to 3.
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