CN113670443B - Color difference measurement method and system based on device-independent color space and intelligent terminal - Google Patents

Color difference measurement method and system based on device-independent color space and intelligent terminal Download PDF

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CN113670443B
CN113670443B CN202110779102.8A CN202110779102A CN113670443B CN 113670443 B CN113670443 B CN 113670443B CN 202110779102 A CN202110779102 A CN 202110779102A CN 113670443 B CN113670443 B CN 113670443B
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color
coordinate system
sample
product
coordinates
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CN113670443A (en
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孟然
柴华
王哲
贾勇
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Beijing Smarter Eye Technology Co Ltd
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    • G—PHYSICS
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    • 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
    • G01J3/50—Measurement of colour; Colour measuring devices, e.g. colorimeters using electric radiation detectors
    • 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
    • G01N21/01—Arrangements or apparatus for facilitating the optical investigation
    • 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
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/251—Colorimeters; Construction thereof
    • 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
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/27—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands using photo-electric detection ; circuits for computing concentration
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

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Abstract

The invention discloses a device-independent color space-based color difference measurement method, a device-independent color space-based color difference measurement system and an intelligent terminal, wherein the device-independent color space-based color difference measurement method comprises the following steps: determining a measured imaging environment, and performing color calibration under the imaging environment; converting the coordinates of an RGB coordinate system output by the imaging device into coordinates of a color system coordinate system based on a preset strategy; imaging the sample and the product respectively, and obtaining coordinates of the sample and the product in a color system coordinate system respectively; and calculating the color difference of the sample and the product based on the coordinates of the sample and the product in a color system coordinate system. The method calculates the chromatic aberration by using color calibration and coordinate conversion, and improves the measurement accuracy of the chromatic aberration, thereby solving the problem of poor product color description accuracy caused by difficult chromatic aberration measurement in the prior art.

Description

Color difference measurement method and system based on device-independent color space and intelligent terminal
Technical Field
The invention relates to the technical field of color difference measurement methods, in particular to a color difference measurement method, a system and an intelligent terminal based on a device-independent color space.
Background
In industrial production, manufacturers often wish to produce products that meet certain color requirements. In describing the color of a product, if there is no specific sample based on only human perception characteristics, the description of the color will be inaccurate. The perceived characteristics of color are determined by the light source, the reflective properties of the object, and the observer. The same object can be observed by different observers under different light source conditions to obtain different color perception characteristics. Thus, to solve this problem, manufacturers provide acceptable samples, requiring that the color values observed by standard observers of the produced product under a specific light source match the sample, i.e., converting the color description problem to a color matching problem.
The matching degree between two color values can be measured by color difference, so providing a color difference measuring method for improving the accuracy of product color description is a problem to be solved by those skilled in the art.
Disclosure of Invention
Therefore, the embodiment of the invention provides a device-independent color space-based color difference measurement method, a device-independent color space-based color difference measurement system and an intelligent terminal, so as to solve the problem of poor product color description accuracy caused by difficulty in color difference measurement in the prior art.
In order to achieve the above object, the embodiment of the present invention provides the following technical solutions:
a method of device independent color space based color difference measurement, the method comprising:
determining a measured imaging environment, and performing color calibration under the imaging environment;
converting the coordinates of an RGB coordinate system output by the imaging device into coordinates of a color system coordinate system based on a preset strategy;
imaging the sample and the product respectively, and obtaining coordinates of the sample and the product in a color system coordinate system respectively;
and calculating the color difference of the sample and the product based on the coordinates of the sample and the product in a color system coordinate system.
Further, the converting, based on a preset strategy, the coordinates of the RGB coordinate system output by the imaging device into the coordinates of the color system coordinate system specifically includes:
obtaining a conversion matrix of coordinate conversion from the RGB coordinate system output by the imaging device to the color system coordinate system;
obtaining a lookup table for converting coordinates of the RGB coordinate system into coordinates of the color system coordinate system through the conversion matrix;
imaging the sample and the product respectively, and obtaining the coordinates of the sample and the product in a color system coordinate system respectively through the lookup table;
and calculating the color difference of the sample and the product based on the coordinates of the sample and the product in a color system coordinate system.
Further, performing color calibration in the imaging environment to obtain a conversion matrix of coordinate conversion from the RGB coordinate system output by the imaging device to the color system coordinate system, which specifically includes:
extracting color data of a color card;
establishing a color calibration model based on the extracted color card color data;
and acquiring a conversion matrix of coordinate conversion from the RGB coordinate system to the color system coordinate system based on the parameters of the color calibration model.
Further, the extracting color card color data specifically includes:
and extracting CIE color data and RGB data of the color card image.
Further, the color calibration model is:
O＝LUT(i,j,k)＝LUT(P)
wherein,
p is the input color space color value, p= [ ijk ] is the color value representation of the input color space;
o is the output color space color value;
LUT () is a color space conversion lookup table.
Further, the converting, based on a preset strategy, the coordinates of the RGB coordinate system output by the imaging device into the coordinates of the color system coordinate system specifically includes:
calculating the RGB image color mean value of a product or a sample output by imaging equipment;
and performing color space conversion on the RGB color mean value to obtain a corresponding color value of the color system coordinate system.
Further, the converting, based on a preset strategy, the coordinates of the RGB coordinate system output by the imaging device into the coordinates of the color system coordinate system specifically includes:
performing point-by-point color space conversion on an RGB image of a product or a sample output by imaging equipment;
and (5) calculating a color mean value of the converted color system format image.
Further, calculating the color difference of the sample and the product based on the coordinates of the sample and the product in a color system coordinate system specifically comprises:
given the color value of the sampleColor value of the product->The calculation formula of the corresponding color difference is:
wherein,according to the color of the sample->According to the color of the product>Is calculated by the following formula:
wherein DeltaL * The difference in brightness is indicated and,representing chrominance differences and +_>Representing the hue difference.
The invention also provides a device independent color space-based color difference measurement system, which comprises:
the color calibration unit is used for determining a measured imaging environment and performing color calibration under the imaging environment;
the system conversion unit is used for converting the coordinates of the RGB coordinate system output by the imaging device into the coordinates of the color system coordinate system based on a preset strategy;
the coordinate acquisition unit is used for respectively imaging the sample and the product and respectively obtaining the coordinates of the sample and the product in a color system coordinate system;
and the color difference calculating unit is used for calculating the color difference of the sample and the product based on the coordinates of the sample and the product in the color system coordinate system.
The invention also provides an intelligent terminal, which comprises: the device comprises a data acquisition device, a processor and a memory;
the data acquisition device is used for acquiring data; the memory is used for storing one or more program instructions; the processor is configured to execute one or more program instructions to perform the method as described above.
According to the device-independent color space-based color difference measurement method, through determining a measured imaging environment, performing color calibration in the imaging environment, converting the coordinates of an RGB coordinate system output by imaging equipment into the coordinates of a color system coordinate system based on a preset strategy, respectively imaging a sample and a product, respectively obtaining the coordinates of the sample and the product in the color system coordinate system, and calculating the color difference of the sample and the product based on the coordinates of the sample and the product in the color system coordinate system. According to the method, color calibration and coordinate conversion are utilized to calculate color difference, colors are converted into a device-independent color system from RGB space, so that the color system is utilized as a color space for color difference measurement, a color difference measured value is more similar to human eyes, the color difference measurement accuracy is improved, and the problem that the product color description accuracy is poor due to difficulty in color difference measurement in the prior art is solved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It will be apparent to those of ordinary skill in the art that the drawings in the following description are exemplary only and that other implementations can be obtained from the extensions of the drawings provided without inventive effort.
The structures, proportions, sizes, etc. shown in the present specification are shown only for the purposes of illustration and description, and are not intended to limit the scope of the invention, which is defined by the claims, so that any structural modifications, changes in proportions, or adjustments of sizes, which do not affect the efficacy or the achievement of the present invention, should fall within the ambit of the technical disclosure.
FIG. 1 is a flow chart of an embodiment of a device independent color space based color difference measurement method provided by the present invention;
FIG. 2 is a schematic diagram of the coordinate system conversion method shown in FIG. 1;
FIG. 3 is a schematic block diagram of color calibration;
FIG. 4 is a functional block diagram of color space conversion under a speed priority strategy;
FIG. 5 is a functional block diagram of color space conversion under a precision first strategy;
fig. 6 is a block diagram of a color difference measurement system according to an embodiment of the present invention.
Detailed Description
Other advantages and advantages of the present invention will become apparent to those skilled in the art from the following detailed description, which, by way of illustration, is to be read in connection with certain specific embodiments, but not all embodiments. 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.
In a specific embodiment, as shown in fig. 1, the method for measuring chromatic aberration based on device-independent color space provided by the invention comprises the following steps:
s1: and determining a measured imaging environment, and performing color calibration under the imaging environment. When determining the imaging environment, a standard light source (such as D65), imaging equipment and imaging environment used in measurement are selected, each standard is kept unchanged in the measurement process, and a standard color card is adopted for color calibration in color calibration. That is, when the color difference between the sample and the product is measured, the imaging conditions such as the light source, the camera, the lighting mode and the like need to be selected and determined, and the imaging conditions are kept unchanged, so that the color calibration and the color difference measurement process are ensured to be completely consistent.
S2: converting the coordinates of an RGB coordinate system output by the imaging device into coordinates of a color system coordinate system based on a preset strategy;
s3: imaging the sample and the product respectively, and obtaining coordinates of the sample and the product in a color system coordinate system respectively;
s4: and calculating the color difference of the sample and the product based on the coordinates of the sample and the product in a color system coordinate system.
Specifically, in step S2, the converting, based on the preset policy, the coordinates of the RGB coordinate system output by the imaging device into the coordinates of the color system coordinate system, as shown in fig. 2, specifically includes:
s21: obtaining a conversion matrix of coordinate conversion from the RGB coordinate system output by the imaging device to the color system coordinate system; specifically, color card color data are firstly extracted, a color calibration model is established based on the extracted color card color data, and a conversion matrix for converting coordinates of an RGB coordinate system into coordinates of a color table system is obtained based on parameters of the color calibration model. The color card color data extraction method comprises the steps of extracting color card CIE color data and color card image RGB data.
S22: obtaining a lookup table for converting coordinates of the RGB coordinate system into coordinates of the color system coordinate system through the conversion matrix;
s23: imaging the sample and the product respectively, and obtaining the coordinates of the sample and the product in a color system coordinate system respectively through the lookup table;
s24: and calculating the color difference of the sample and the product based on the coordinates of the sample and the product in a color system coordinate system.
The task of color calibration is to solve the conversion matrix T from the RGB color space output by the imaging device to the device independent CIE LAB color space, and further to obtain the conversion look-up table LUT. In a specific usage scenario, as shown in fig. 3, a schematic block diagram of color calibration is shown, where the color calibration is composed of two parts: 1) The extraction of color data of the color chip includes the extraction of CIE color data of the color chip (i.e.: l, a, b) and extracting RGB data of the color card image; 2) And (5) selecting a color calibration model and solving the color calibration model. Finally, the conversion matrix T of the two color spaces can be obtained through the calculated parameters of the calibration model, and then the conversion lookup table LUT is obtained.
Further, according to the model parameters obtained by color calibration, we can obtain a mapping model from the RGB color space to the CIE LAB color space, thereby obtaining a conversion matrix T of the two color spaces. If a conversion matrix is used for direct calculation of the conversion of the color values between the two color spaces, the method is visual in realization and high in precision, but is very low in realization efficiency and is not suitable for a real-time measurement system. The conversion efficiency of color values can be greatly improved by establishing a conversion lookup table LUT of two color spaces through a conversion matrix T in a preparation link before color difference measurement.
Specifically, the color calibration model is:
O＝LUT(i,j,k)＝LUT(P)
wherein,
p is the input color space color value, p= [ ijk ] is the color value representation of the input color space;
o is the output color space color value;
LUT () is a color space conversion lookup table.
The method has high precision and efficiency, but requires a certain storage space. For example, when the input and output colors are all 8-bit data,it is required to be 3×2 24 =48mmemory space.
There are two alternative methods for converting from RGB space to CIE LAB space, based on a speed first strategy and a precision first strategy, respectively. The difference between these two strategies is mainly reflected in the process of deriving their corresponding CIE LAB color values from RGB images of the product or sample.
For the speed priority strategy, as shown in fig. 4, the color difference measurement firstly calculates a color mean value of an RGB image of a product or a sample output by the imaging device, and then performs color space conversion on the RGB color mean value to obtain a corresponding CIE LAB space color value. As shown in fig. 5, for the precision-first strategy, the color difference measurement firstly performs point-by-point color space conversion on the RGB image of the product or sample output by the imaging device, and then calculates the color mean value of the CIE LAB format image obtained by the conversion.
Further, calculating the color difference of the sample and the product based on the coordinates of the sample and the product in a color system coordinate system specifically comprises:
given the color value of the sampleColor value of the product->The calculation formula of the corresponding color difference is:
wherein DeltaL * Indicating the brightness difference, Δa * Representing the difference in red and green, Δb * Yellow Lan Du difference, Δe color difference.
In general, since the total color difference Δe can only provide information of the color difference magnitude, but cannot provide information of the color difference direction, it is necessary to provide not only the color difference Δe but also Δl to the user * ，ΔA * ，Δb * ，And +.>Information.
Preferably, the color difference is also determined by the brightness difference DeltaL of CIE LCH space * Difference in chromaColor tone differenceIs defined as the formula:
wherein,according to the color of the sample->According to the color of the product>Is calculated by the following formula:
in the specific embodiment, the device-independent color space-based color difference measurement method provided by the invention is characterized in that the measured imaging environment is determined, color calibration is carried out in the imaging environment, the coordinates of the RGB coordinate system output by the imaging device are converted into the coordinates of the color system coordinate system based on a preset strategy, the sample and the product are respectively imaged, the coordinates of the sample and the product in the color system coordinate system are respectively obtained, and the color difference of the sample and the product is calculated based on the coordinates of the sample and the product in the color system coordinate system. According to the method, color calibration and coordinate conversion are utilized to calculate color difference, colors are converted into a device-independent color system from RGB space, so that the color system is utilized as a color space for color difference measurement, a color difference measured value is more similar to human eyes, the color difference measurement accuracy is improved, and the problem that the product color description accuracy is poor due to difficulty in color difference measurement in the prior art is solved.
In addition to the above method, the present invention also provides a color difference measurement system based on a device independent color space, as shown in fig. 6, the system comprising:
a color calibration unit 100 for determining a measured imaging environment in which color calibration is performed;
a system conversion unit 200 for converting coordinates of an RGB coordinate system output from the imaging apparatus into coordinates of a color system coordinate system based on a preset strategy;
a coordinate acquiring unit 300, configured to image the sample and the product respectively, and obtain coordinates of the sample and the product in a color system coordinate system respectively;
and a color difference calculating unit 400 for calculating the color difference of the sample and the product based on the coordinates of the sample and the product in the color system coordinate system.
The architecture conversion unit 200 is specifically configured to:
obtaining a conversion matrix of coordinate conversion from the RGB coordinate system output by the imaging device to the color system coordinate system; specifically, color card color data are firstly extracted, a color calibration model is established based on the extracted color card color data, and a conversion matrix for converting coordinates of an RGB coordinate system into coordinates of a color table system is obtained based on parameters of the color calibration model. The color card color data extraction method comprises the steps of extracting color card CIE color data and color card image RGB data.
Obtaining a lookup table for converting coordinates of the RGB coordinate system into coordinates of the color system coordinate system through the conversion matrix;
imaging the sample and the product respectively, and obtaining the coordinates of the sample and the product in a color system coordinate system respectively through the lookup table;
and calculating the color difference of the sample and the product based on the coordinates of the sample and the product in a color system coordinate system.
The task of color calibration is to solve the conversion matrix T from the RGB color space output by the imaging device to the device independent CIE LAB color space, and further to obtain the conversion look-up table LUT. In a specific usage scenario, as shown in fig. 3, a schematic block diagram of color calibration is shown, where the color calibration is composed of two parts: 1) The extraction of color data of the color chip includes the extraction of CIE color data of the color chip (i.e.: l, a, b) and extracting RGB data of the color card image; 2) And (5) selecting a color calibration model and solving the color calibration model. Finally, the conversion matrix T of the two color spaces can be obtained through the calculated parameters of the calibration model, and then the conversion lookup table LUT is obtained.
Further, according to the model parameters obtained by color calibration, we can obtain a mapping model from the RGB color space to the CIE LAB color space, thereby obtaining a conversion matrix T of the two color spaces. If a conversion matrix is used for direct calculation of the conversion of the color values between the two color spaces, the method is visual in realization and high in precision, but is very low in realization efficiency and is not suitable for a real-time measurement system. The conversion efficiency of color values can be greatly improved by establishing a conversion lookup table LUT of two color spaces through a conversion matrix T in a preparation link before color difference measurement.
Specifically, the color calibration model is:
O＝LUT(i,j,k)＝LUT(P)
wherein,
p is the input color space color value, p= [ ijk ] is the color value representation of the input color space;
o is the output color space color value;
LUT () is a color space conversion lookup table.
The method has high precision and efficiency, but requires a certain storage space. For example, when the input/output colors are 8-bit data, 3×2 is required 24 =48mmemory space.
There are two alternative methods for converting from RGB space to CIE LAB space, based on a speed first strategy and a precision first strategy, respectively. The difference between these two strategies is mainly reflected in the process of deriving their corresponding CIE LAB color values from RGB images of the product or sample.
For the speed priority strategy, as shown in fig. 4, the color difference measurement firstly calculates a color mean value of an RGB image of a product or a sample output by the imaging device, and then performs color space conversion on the RGB color mean value to obtain a corresponding CIE LAB space color value. As shown in fig. 5, for the precision-first strategy, the color difference measurement firstly performs point-by-point color space conversion on the RGB image of the product or sample output by the imaging device, and then calculates the color mean value of the CIE LAB format image obtained by the conversion.
Further, calculating the color difference of the sample and the product based on the coordinates of the sample and the product in a color system coordinate system specifically comprises:
given the color value of the sampleColor value of the product->The calculation formula of the corresponding color difference is:
wherein DeltaL * Indicating the brightness difference, Δa * Representing the difference in red and green, Δb * Yellow Lan Du difference, Δe color difference.
Indeed, as an alternative, the color difference may also be defined by the brightness difference Δl of the CIE LCH space * Difference in chromaTone difference +.>Is defined as the formula:
wherein,according to the color of the sample->According to the color of the product>Is calculated by the following formula:
in general, since the total color difference Δe can only provide information of the color difference magnitude, but cannot provide information of the color difference direction, it is necessary to provide not only the color difference Δe but also Δl to the user * ，ΔA * ，Δb * ，And +.>Information.
In the specific embodiment, the color difference measurement system based on the device-independent color space provided by the invention performs color calibration in the imaging environment by determining the measured imaging environment, converts the coordinates of the RGB coordinate system output by the imaging device into the coordinates of the color system coordinate system based on a preset strategy, images the sample and the product respectively, obtains the coordinates of the sample and the product in the color system coordinate system respectively, and calculates the color difference of the sample and the product based on the coordinates of the sample and the product in the color system coordinate system. The method calculates the chromatic aberration by using color calibration and coordinate conversion, and converts the color from RGB space to a device-independent color system, so that the color system is used as the color space for chromatic aberration measurement, the measured value of chromatic aberration is more similar to human eyes, the measurement accuracy of chromatic aberration is improved, and the problem of poor product color description accuracy caused by difficult chromatic aberration measurement in the prior art is solved.
The invention also provides an intelligent terminal, which comprises: the device comprises a data acquisition device, a processor and a memory;
the data acquisition device is used for acquiring data; the memory is used for storing one or more program instructions; the processor is configured to execute one or more program instructions to perform the method as described above.
Corresponding to the above embodiments, the present invention further provides a computer storage medium, which contains one or more program instructions. Wherein the one or more program instructions are for performing the method as described above by a binocular camera depth calibration system.
In the embodiment of the invention, the processor may be an integrated circuit chip with signal processing capability. The processor may be a general purpose processor, a digital signal processor (Digital Signal Processor, DSP for short), an application specific integrated circuit (Application Specific f ntegrated Circuit ASIC for short), a field programmable gate array (FieldProgrammable Gate Array FPGA for short), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components.
The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The processor reads the information in the storage medium and, in combination with its hardware, performs the steps of the above method.
The storage medium may be memory, for example, may be volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory.
The nonvolatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an electrically Erasable ROM (Electrically EPROM, EEPROM), or a flash Memory.
The volatile memory may be a random access memory (Random Access Memory, RAM for short) which acts as an external cache. By way of example, and not limitation, many forms of RAM are available, such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (Double Data RateSDRAM), enhanced SDRAM (ESDRAM), synchronous DRAM (SLDRAM), and direct memory bus RAM (directracram, DRRAM).
The storage media described in embodiments of the present invention are intended to comprise, without being limited to, these and any other suitable types of memory.
Those skilled in the art will appreciate that in one or more of the examples described above, the functions described in the present invention may be implemented in a combination of hardware and software. When the software is applied, the corresponding functions may be stored in a computer-readable medium or transmitted as one or more instructions or code on the computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
The foregoing detailed description of the invention has been presented for purposes of illustration and description, and it should be understood that the foregoing is by way of illustration and description only, and is not intended to limit the scope of the invention.

Claims (5)

1. A method for device independent color space based color difference measurement, the method comprising:
determining a measured imaging environment, and performing color calibration under the imaging environment;
converting the coordinates of an RGB coordinate system output by the imaging device into coordinates of a color system coordinate system based on a preset strategy;
imaging the sample and the product respectively, and obtaining coordinates of the sample and the product in a color system coordinate system respectively;
calculating the color difference of the sample and the product based on the coordinates of the sample and the product in a color system coordinate system;
converting from RGB space to CIE LAB space, and adopting a speed-based priority strategy or an accuracy priority strategy;
for a speed priority strategy, color difference measurement firstly obtains a color mean value of RGB images of a product or a sample output by imaging equipment, and then performs color space conversion on the RGB color mean value to obtain a corresponding CIE LAB space color value;
for the precision priority strategy, color difference measurement firstly carries out point-by-point color space conversion on RGB images of products or samples output by imaging equipment, and then calculates color average values of CIE LAB format images obtained by conversion;
the method specifically comprises the steps of converting the coordinates of an RGB coordinate system output by imaging equipment into coordinates of a color system coordinate system based on a preset strategy, respectively imaging a sample and a product, respectively obtaining the coordinates of the sample and the product in the color system coordinate system, and specifically comprises the following steps:
obtaining a conversion matrix of coordinate conversion from the RGB coordinate system output by the imaging device to the color system coordinate system;
obtaining a lookup table for converting coordinates of the RGB coordinate system into coordinates of the color system coordinate system through the conversion matrix;
imaging the sample and the product respectively, and obtaining the coordinates of the sample and the product in a color system coordinate system respectively through the lookup table;
the method for performing color calibration in the imaging environment to obtain a conversion matrix of coordinate conversion from the RGB coordinate system output by the imaging device to the surface color system coordinate system specifically comprises the following steps:
extracting color data of a color card;
establishing a color calibration model based on the extracted color card color data;
based on the parameters of the color calibration model, a conversion matrix of coordinate conversion from the RGB coordinate system to the color system coordinate system is obtained;
wherein, the color calibration model is:
O＝LUT(i,j,k)＝LUT(P)
wherein,
p is the input color space color value, p= [ ijk ] is the color value representation of the input color space;
o is the output color space color value;
the LUT (P) is a color space conversion look-up table.
2. The color difference measurement method according to claim 1, wherein the calculating the color difference of the sample and the product based on the coordinates of the sample and the product in the color appearance system coordinate system specifically comprises:
given the color value of the sampleColor value of the product->The calculation formula of the corresponding color difference is:
wherein,according to the color of the sample-> According to the color of the product>Is calculated by the following formula:
wherein DeltaL * The difference in brightness is indicated and,representing chrominance differences and +_>Represents the hue difference, Δe represents the color difference.
3. The color difference measurement method according to claim 1, wherein the extracting color card color data specifically includes:
and extracting CIE color data and RGB data of the color card image.
4. A device independent color space based color difference measurement system, the system comprising:
the color calibration unit is used for determining a measured imaging environment and performing color calibration under the imaging environment;
the system conversion unit is used for converting the coordinates of the RGB coordinate system output by the imaging device into the coordinates of the color system coordinate system based on a preset strategy;
the coordinate acquisition unit is used for respectively imaging the sample and the product and respectively obtaining the coordinates of the sample and the product in a color system coordinate system;
a color difference calculating unit for calculating the color difference of the sample and the product based on the coordinates of the sample and the product in the color system coordinate system;
the method specifically comprises the steps of converting the coordinates of an RGB coordinate system output by imaging equipment into coordinates of a color system coordinate system based on a preset strategy, respectively imaging a sample and a product, respectively obtaining the coordinates of the sample and the product in the color system coordinate system, and specifically comprises the following steps:
obtaining a conversion matrix of coordinate conversion from the RGB coordinate system output by the imaging device to the color system coordinate system;
obtaining a lookup table for converting coordinates of the RGB coordinate system into coordinates of the color system coordinate system through the conversion matrix;
imaging the sample and the product respectively, and obtaining the coordinates of the sample and the product in a color system coordinate system respectively through the lookup table;
the method for performing color calibration in the imaging environment to obtain a conversion matrix of coordinate conversion from the RGB coordinate system output by the imaging device to the surface color system coordinate system specifically comprises the following steps:
extracting color data of a color card;
establishing a color calibration model based on the extracted color card color data;
based on the parameters of the color calibration model, a conversion matrix of coordinate conversion from the RGB coordinate system to the color system coordinate system is obtained;
wherein, the color calibration model is:
O＝LUT(i,j,k)＝LUT(P)
wherein,
p is the input color space color value, p= [ ijk ] is the color value representation of the input color space;
o is the output color space color value;
the LUT (P) is a color space conversion look-up table.
5. An intelligent terminal, characterized in that, the intelligent terminal includes: the device comprises a data acquisition device, a processor and a memory;
the data acquisition device is used for acquiring data; the memory is used for storing one or more program instructions; the processor being configured to execute one or more program instructions for performing the method of any of claims 1-2.
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