CN113670443A - Color difference measuring method and system based on device-independent color space and intelligent terminal - Google Patents

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

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CN113670443A
CN113670443A CN202110779102.8A CN202110779102A CN113670443A CN 113670443 A CN113670443 A CN 113670443A CN 202110779102 A CN202110779102 A CN 202110779102A CN 113670443 A CN113670443 A CN 113670443A
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color
coordinates
coordinate system
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product
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CN113670443B (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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    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
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Abstract

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

Description

Color difference measuring 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 and system based on an equipment-independent color space and an intelligent terminal.
Background
In industrial production, manufacturers often wish to produce products that meet certain color requirements. In describing the color of a product, if only the human perception features are used without a specific sample, the description about the color may not be accurate enough. The perceived characteristics of the color are determined by the light source, the reflective properties of the object and the viewer. Different color perception characteristics can be obtained when the same object is observed by different observers under different light source conditions. Therefore, in order to solve this problem, manufacturers provide qualified samples, and require that the color values of the produced products observed by standard observers under specific light sources be matched with the samples, i.e. the color description problem is converted into the color matching problem.
The matching degree between two color values can be measured by color difference, so that providing a color difference measurement method to improve the accuracy of product color description becomes a problem to be solved by those skilled in the art.
Disclosure of Invention
Therefore, the embodiment of the invention provides a color difference measuring method and system based on an equipment-independent color space 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 embodiments of the present invention provide the following technical solutions:
a method of color difference measurement based on a device-independent color space, the method comprising:
determining a measured imaging environment, and performing color calibration in the imaging environment;
converting coordinates of an RGB coordinate system output by the imaging equipment into coordinates of a coordinate system of a color system based on a preset strategy;
respectively imaging the sample and the product, and respectively obtaining the coordinates of the sample and the product in a coordinate system of a color system;
and calculating the color difference of the sample and the product based on the coordinates of the sample and the product in the coordinate system of the color system.
Further, the converting the coordinates of the RGB coordinate system output by the imaging device into the coordinates of the coordinate system of the color system based on the preset policy specifically includes:
obtaining a transformation matrix for transforming the coordinates of the RGB coordinate system output by the imaging equipment into the coordinates of the coordinate system of the color system;
obtaining a lookup table for converting the coordinates of the RGB coordinate system to the coordinates of the color system coordinate system through the conversion matrix;
respectively imaging the sample and the product, and respectively obtaining the coordinates of the sample and the product in a coordinate system of a color system 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 the coordinate system of the color system.
Further, the color calibration in the imaging environment to obtain a conversion matrix for converting coordinates of an RGB coordinate system output by the imaging device into coordinates of a color system coordinate system specifically includes:
extracting color data of the color card;
establishing a color calibration model based on the extracted color data of the color chart;
and acquiring a conversion matrix for converting the coordinates of the RGB coordinate system to the coordinates of the color system coordinate system based on the parameters of the color calibration model.
Further, the extracting of the color data of the color chart specifically includes:
extracting color card CIE color data and color card image RGB data.
Further, the color calibration model is as follows:
O＝LUT(i,j,k)＝LUT(P)
wherein the content of the first and second substances,
p is an input color space color value, and P ═ ijk is a representation of the color value of the input color space;
o is an output color space color value;
LUT () is a color space conversion look-up table.
Further, the converting the coordinates of the RGB coordinate system output by the imaging device into the coordinates of the coordinate system of the color system based on the preset policy specifically includes:
calculating the RGB image color mean value of the product or sample output by the imaging equipment;
and carrying out color space conversion on the RGB color mean value to obtain a color value of a color system coordinate system corresponding to the RGB color mean value.
Further, the converting the coordinates of the RGB coordinate system output by the imaging device into the coordinates of the coordinate system of the color system based on the preset policy specifically includes:
performing point-by-point color space conversion on the RGB image of the product or the sample output by the imaging equipment;
and solving a color mean value of the image in the form of the color system obtained by conversion.
Further, the calculating the color difference between the sample and the product based on the coordinates of the sample and the product in the coordinate system of the color system specifically comprises:
if a given sample color value
Figure BDA0003155482620000031
Color value of product
Figure BDA0003155482620000032
The calculation formula of the corresponding color difference is as follows:
Figure BDA0003155482620000033
Figure BDA0003155482620000034
Figure BDA0003155482620000035
wherein the content of the first and second substances,
Figure BDA0003155482620000036
according to the color of the sample
Figure BDA0003155482620000037
According to the color of the product
Figure BDA0003155482620000038
All are calculated by the following formula:
Figure BDA0003155482620000039
wherein, Δ L*The difference in brightness is represented by the difference in brightness,
Figure BDA00031554826200000310
the difference in chroma is indicated and,
Figure BDA00031554826200000311
indicating a hue difference.
The present invention also provides a color difference measurement system based on an apparatus-independent color space, the system comprising:
the color calibration unit is used for determining a measured imaging environment and performing color calibration in the imaging environment;
the system conversion unit is used for converting the coordinates of the RGB coordinate system output by the imaging equipment into the coordinates of the coordinate system of the color 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 coordinate system of a color 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 coordinate system of the color system.
The present invention also provides an intelligent terminal, including: the device comprises a data acquisition device, a processor and a memory;
the data acquisition device is used for acquiring data; the memory is to store one or more program instructions; the processor is configured to execute one or more program instructions to perform the method as described above.
The color difference measuring method based on the device-independent color space comprises the steps of determining a measured imaging environment, calibrating colors in the imaging environment, converting coordinates of an RGB coordinate system output by imaging equipment into coordinates of a coordinate system of a color system based on a preset strategy, imaging a sample and a product respectively, obtaining coordinates of the sample and the product in the coordinate system of the color system respectively, and calculating the color difference of the sample and the product based on the coordinates of the sample and the product in the coordinate system of the color system. The method utilizes color calibration and coordinate conversion to calculate color difference, converts the color from RGB space to an equipment-independent color system, thereby utilizing the color system as the color space for color difference measurement, leading the color difference measurement value to be closer to the feeling of human eyes, improving the measurement accuracy of the color difference, and further solving the problem of poor product color description accuracy caused by difficult color difference measurement in the prior art.
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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 should be apparent that the drawings in the following description are merely exemplary, and that other embodiments can be derived from the drawings provided by those of ordinary skill in the art without inventive effort.
The structures, ratios, sizes, and the like shown in the present specification are only used for matching with the contents disclosed in the specification, so as to be understood and read by those skilled in the art, and are not used to limit the conditions that the present invention can be implemented, so that the present invention has no technical significance, and any structural modifications, changes in the ratio relationship, or adjustments of the sizes, without affecting the effects and the achievable by the present invention, should still fall within the range that the technical contents disclosed in the present invention can cover.
FIG. 1 is a flowchart of an embodiment of a method for measuring chromatic aberration based on device-independent color space according to the present invention;
FIG. 2 is a schematic diagram of a coordinate system transformation method shown in FIG. 1;
FIG. 3 is a functional block diagram of color calibration;
FIG. 4 is a schematic block diagram of color space conversion under a speed-first strategy;
FIG. 5 is a schematic block diagram of color space conversion under a precision-first strategy;
fig. 6 is a block diagram of an embodiment of a color difference measurement system according to the present invention.
Detailed Description
The present invention is described in terms of particular embodiments, other advantages and features of the invention will become apparent to those skilled in the art from the following disclosure, and it is to be understood that the described embodiments are merely exemplary of the invention and that it is not intended to limit the invention to the particular embodiments disclosed. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In one embodiment, as shown in fig. 1, the method for measuring color difference based on device-independent color space provided by the present invention includes the following steps:
s1: determining a measured imaging environment, and performing color calibration in the imaging environment. When the imaging environment is determined, a standard light source (such as D65), an imaging device and the imaging environment used in measurement are selected, standards are kept constant in the measurement process, and color calibration is carried out by using a standard color card in color calibration. That is to say, when measuring the chromatic aberration of a sample and a product, it is first necessary to select and determine the imaging conditions such as a light source, a camera, a lighting mode, etc., and keep the imaging conditions unchanged, so as to ensure that the imaging conditions in the color calibration and chromatic aberration measurement processes are completely consistent.
S2: converting coordinates of an RGB coordinate system output by the imaging equipment into coordinates of a coordinate system of a color system based on a preset strategy;
s3: respectively imaging the sample and the product, and respectively obtaining the coordinates of the sample and the product in a coordinate system of a color system;
s4: and calculating the color difference of the sample and the product based on the coordinates of the sample and the product in the coordinate system of the color system.
Specifically, in step S2, the converting coordinates of the RGB coordinate system output by the imaging device into coordinates of a coordinate system of a color system based on a preset policy specifically includes, as shown in fig. 2:
s21: obtaining a transformation matrix for transforming the coordinates of the RGB coordinate system output by the imaging equipment into the coordinates of the coordinate system of the color system; specifically, color data of a color chart is extracted, a color calibration model is established based on the extracted color data of the color chart, and a conversion matrix for converting coordinates of an RGB coordinate system to coordinates of a coordinate system of a color table system is obtained based on parameters of the color calibration model. The extracting of the color card color data comprises extracting color card CIE color data and color card image RGB data.
S22: obtaining a lookup table for converting the coordinates of the RGB coordinate system to the coordinates of the color system coordinate system through the conversion matrix;
s23: respectively imaging the sample and the product, and respectively obtaining the coordinates of the sample and the product in a coordinate system of a color system 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 the coordinate system of the color system.
The task of color calibration is to solve a conversion matrix T from the RGB color space output by the imaging device to the device-independent CIE LAB color space, and then to obtain a conversion look-up table LUT. In a specific usage scenario, as shown in fig. 3, a schematic block diagram of color calibration is shown, and the color calibration is composed of two parts: 1) extraction of color target color data, including color target CIE color data (i.e.: l, a, b) and extracting RGB data of the color card image; 2) and 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 parameters of the calibration model obtained through calculation, 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 transformation matrix T of the two color spaces. If the conversion matrix is used for directly calculating the color value between the two color spaces, the method is intuitive to realize and high in precision, but the realization efficiency is very low, and the method is not suitable for a real-time measurement system. In a preparation link before color difference measurement, conversion lookup tables LUT of two color spaces are established through a conversion matrix T, so that the conversion efficiency of color values is greatly improved.
Specifically, the color calibration model is as follows:
O＝LUT(i,j,k)＝LUT(P)
wherein the content of the first and second substances,
p is an input color space color value, and P ═ ijk is a representation of the color value of the input color space;
o is an output color space color value;
LUT () is a color space conversion look-up table.
The method has high precision and high efficiency, but needs a certain storage space. For example, when the input and output colors are all 8-bit data, 3 × 2 is required2448M storage space.
There are two methods to switch from RGB space to CIE LAB space, which can be chosen, respectively based on a speed-first strategy and a precision-first strategy. The difference between these two strategies is mainly reflected in the process of obtaining their corresponding CIE LAB color values from RGB images of the product or sample.
For the speed priority strategy, as shown in fig. 4, color difference measurement firstly calculates a color mean value of an RGB image of a product or a sample output by an 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 priority strategy, the color difference measurement firstly performs point-by-point color space conversion on RGB images of products or samples output by the imaging device, and then calculates a color mean value of the converted CIE LAB format images.
Further, the calculating the color difference between the sample and the product based on the coordinates of the sample and the product in the coordinate system of the color system specifically comprises:
if a given sample color value
Figure BDA0003155482620000071
Product colorColour value
Figure BDA0003155482620000072
The calculation formula of the corresponding color difference is as follows:
Figure BDA0003155482620000073
Figure BDA0003155482620000074
Figure BDA0003155482620000075
Figure BDA0003155482620000076
wherein, Δ L*Denotes the lightness difference,. DELTA.a*Representing a difference in red-green degree, Δ b*Denotes a yellow-blue difference, and Δ E denotes a color difference.
In general, since the total color difference Δ E can only provide information about the size of the color difference and cannot provide information about the direction of the color difference, it is necessary to provide Δ L as well as Δ E to the user*，ΔA*，Δb*，
Figure BDA0003155482620000077
And
Figure BDA0003155482620000078
and (4) information.
Preferably, the color difference may be defined by a difference Δ L in the CIE LCH space*Poor chroma
Figure BDA0003155482620000081
And difference in hue
Figure BDA0003155482620000082
Is defined as the formula:
Figure BDA0003155482620000083
Figure BDA0003155482620000084
Figure BDA0003155482620000085
wherein the content of the first and second substances,
Figure BDA0003155482620000086
according to the color of the sample
Figure BDA0003155482620000087
According to the color of the product
Figure BDA0003155482620000088
All are calculated by the following formula:
Figure BDA0003155482620000089
in the foregoing embodiment, the method for measuring chromatic aberration based on an equipment-independent color space provided by the present invention includes determining a measured imaging environment, calibrating color in the imaging environment, converting coordinates of an RGB coordinate system output by an imaging device into coordinates of a coordinate system of a color system based on a preset strategy, imaging a sample and a product respectively, obtaining coordinates of the sample and the product in the coordinate system of the color system, and calculating chromatic aberration of the sample and the product based on the coordinates of the sample and the product in the coordinate system of the color system. The method utilizes color calibration and coordinate conversion to calculate color difference, converts the color from RGB space to an equipment-independent color system, thereby utilizing the color system as the color space for color difference measurement, leading the color difference measurement value to be closer to the feeling of human eyes, improving the measurement accuracy of the color difference, and solving the problem of poor product color description accuracy caused by difficult color difference measurement in the prior art.
In addition to the above method, the present invention further provides a color difference measuring 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 to perform color calibration;
the system conversion unit 200 is configured to convert coordinates of an RGB coordinate system output by the imaging device into coordinates of a color system coordinate system based on a preset policy;
the coordinate acquisition unit 300 is configured to image the sample and the product respectively, and obtain coordinates of the sample and the product in a coordinate system of a color system respectively;
and the color difference calculating unit 400 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 coordinate system of the color system.
The system conversion unit 200 is specifically configured to:
obtaining a transformation matrix for transforming the coordinates of the RGB coordinate system output by the imaging equipment into the coordinates of the coordinate system of the color system; specifically, color data of a color chart is extracted, a color calibration model is established based on the extracted color data of the color chart, and a conversion matrix for converting coordinates of an RGB coordinate system to coordinates of a coordinate system of a color table system is obtained based on parameters of the color calibration model. The extracting of the color card color data comprises extracting color card CIE color data and color card image RGB data.
Obtaining a lookup table for converting the coordinates of the RGB coordinate system to the coordinates of the color system coordinate system through the conversion matrix;
respectively imaging the sample and the product, and respectively obtaining the coordinates of the sample and the product in a coordinate system of a color system 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 the coordinate system of the color system.
The task of color calibration is to solve a conversion matrix T from the RGB color space output by the imaging device to the device-independent CIE LAB color space, and then to obtain a conversion look-up table LUT. In a specific usage scenario, as shown in fig. 3, a schematic block diagram of color calibration is shown, and the color calibration is composed of two parts: 1) extraction of color target color data, including color target CIE color data (i.e.: l, a, b) and extracting RGB data of the color card image; 2) and 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 parameters of the calibration model obtained through calculation, 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 transformation matrix T of the two color spaces. If the conversion matrix is used for directly calculating the color value between the two color spaces, the method is intuitive to realize and high in precision, but the realization efficiency is very low, and the method is not suitable for a real-time measurement system. In a preparation link before color difference measurement, conversion lookup tables LUT of two color spaces are established through a conversion matrix T, so that the conversion efficiency of color values is greatly improved.
Specifically, the color calibration model is as follows:
O＝LUT(i,j,k)＝LUT(P)
wherein the content of the first and second substances,
p is an input color space color value, and P ═ ijk is a representation of the color value of the input color space;
o is an output color space color value;
LUT () is a color space conversion look-up table.
The method has high precision and high efficiency, but needs a certain storage space. For example, when the input and output colors are all 8-bit data, 3 × 2 is required2448M storage space.
There are two methods to switch from RGB space to CIE LAB space, which can be chosen, respectively based on a speed-first strategy and a precision-first strategy. The difference between these two strategies is mainly reflected in the process of obtaining their corresponding CIE LAB color values from RGB images of the product or sample.
For the speed priority strategy, as shown in fig. 4, color difference measurement firstly calculates a color mean value of an RGB image of a product or a sample output by an 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 priority strategy, the color difference measurement firstly performs point-by-point color space conversion on RGB images of products or samples output by the imaging device, and then calculates a color mean value of the converted CIE LAB format images.
Further, the calculating the color difference between the sample and the product based on the coordinates of the sample and the product in the coordinate system of the color system specifically comprises:
if a given sample color value
Figure BDA0003155482620000101
Color value of product
Figure BDA0003155482620000102
The calculation formula of the corresponding color difference is as follows:
Figure BDA0003155482620000103
Figure BDA0003155482620000104
Figure BDA0003155482620000105
Figure BDA0003155482620000106
wherein, Δ L*Denotes the lightness difference,. DELTA.a*Representing a difference in red-green degree, Δ b*Denotes a yellow-blue difference, and Δ E denotes a color difference.
In fact, as an alternative, the color difference can also be determined by the difference in brightness Δ L in the CIE LCH space*Poor chroma
Figure BDA0003155482620000107
And difference in hue
Figure BDA0003155482620000108
Is defined as the formula:
Figure BDA0003155482620000109
Figure BDA00031554826200001010
Figure BDA00031554826200001011
wherein the content of the first and second substances,
Figure BDA0003155482620000111
according to the color of the sample
Figure BDA0003155482620000112
According to the color of the product
Figure BDA0003155482620000113
All are calculated by the following formula:
Figure BDA0003155482620000114
in general, since the total color difference Δ E can only provide information about the size of the color difference and cannot provide information about the direction of the color difference, it is necessary to provide Δ L as well as Δ E to the user*，ΔA*，Δb*，
Figure BDA0003155482620000115
And
Figure BDA0003155482620000116
and (4) information.
In the foregoing embodiment, the color difference measuring system based on the device-independent color space provided by the present invention performs color calibration in a measured imaging environment by determining the imaging environment, converts coordinates of an RGB coordinate system output by the imaging device into coordinates of a coordinate system of a color system based on a preset policy, images the sample and the product respectively, obtains coordinates of the sample and the product in the coordinate system of the color system, and calculates the color difference between the sample and the product based on the coordinates of the sample and the product in the coordinate system of the color system. The method utilizes color calibration and coordinate conversion to calculate color difference, converts the color from RGB space to an equipment-independent color system, thereby utilizing the color system as the color space for color difference measurement, leading the color difference measurement value to be closer to the feeling of human eyes, improving the measurement accuracy of the color difference, and solving the problem of poor product color description accuracy caused by the difficulty in color difference measurement in the prior art.
The present invention also provides an intelligent terminal, including: the device comprises a data acquisition device, a processor and a memory;
the data acquisition device is used for acquiring data; the memory is to store one or more program instructions; the processor is configured to execute one or more program instructions to perform the method as described above.
In correspondence with the above embodiments, embodiments of the present invention also provide a computer storage medium containing one or more program instructions therein. Wherein the one or more program instructions are for executing the method as described above by a binocular camera depth calibration system.
In an embodiment of the invention, the processor may be an integrated circuit chip having signal processing capability. The Processor may be a general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete Gate or transistor logic device, discrete hardware component.
The various methods, steps and logic blocks disclosed 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 directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The processor reads the information in the storage medium and completes the steps of the method in combination with the hardware.
The storage medium may be a memory, for example, which may be volatile memory or nonvolatile memory, or which 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 PROM (EEPROM), or a flash Memory.
The volatile Memory may be a Random Access Memory (RAM) which serves as an external cache. By way of example and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), SLDRAM (SLDRAM), and Direct Rambus RAM (DRRAM).
The storage media described in connection with the embodiments of the 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 the functionality described in the present invention may be implemented in a combination of hardware and software in one or more of the examples described above. When software is applied, the corresponding functionality may be stored on or transmitted over as one or more instructions or code on a 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 above embodiments are only for illustrating the embodiments of the present invention and are not to be construed as limiting the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made on the basis of the embodiments of the present invention shall be included in the scope of the present invention.

Claims (10)

1. A method for measuring color difference based on a device-independent color space, the method comprising:
determining a measured imaging environment, and performing color calibration in the imaging environment;
converting coordinates of an RGB coordinate system output by the imaging equipment into coordinates of a coordinate system of a color system based on a preset strategy;
respectively imaging the sample and the product, and respectively obtaining the coordinates of the sample and the product in a coordinate system of a color system;
and calculating the color difference of the sample and the product based on the coordinates of the sample and the product in the coordinate system of the color system.
2. The method for measuring color difference according to claim 1, wherein the converting coordinates of the RGB coordinate system output by the imaging device into coordinates of a coordinate system of a color system based on a preset policy specifically comprises:
calculating the RGB image color mean value of the product or sample output by the imaging equipment;
and carrying out color space conversion on the RGB color mean value to obtain a color value of a color system coordinate system corresponding to the RGB color mean value.
3. The method for measuring color difference according to claim 1, wherein the converting coordinates of the RGB coordinate system output by the imaging device into coordinates of a coordinate system of a color system based on a preset policy specifically comprises:
performing point-by-point color space conversion on the RGB image of the product or the sample output by the imaging equipment;
and solving a color mean value of the image in the form of the color system obtained by conversion.
4. The method for measuring color difference 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 coordinate system of the color system comprises:
if a given sample color value
Figure FDA0003155482610000011
Color value of product
Figure FDA0003155482610000012
The calculation formula of the corresponding color difference is as follows:
Figure FDA0003155482610000013
Figure FDA0003155482610000014
Figure FDA0003155482610000015
wherein the content of the first and second substances,
Figure FDA0003155482610000021
according to the color of the sample
Figure FDA0003155482610000022
Figure FDA0003155482610000023
According to the color of the product
Figure FDA0003155482610000024
All are calculated by the following formula:
Figure FDA0003155482610000025
wherein, Δ L*The difference in brightness is represented by the difference in brightness,
Figure FDA0003155482610000026
the difference in chroma is indicated and,
Figure FDA0003155482610000027
indicating a hue difference.
5. The method for measuring color difference according to claim 1, wherein the converting coordinates of the RGB coordinate system output by the imaging device into coordinates of a coordinate system of a color system based on a preset policy specifically comprises:
obtaining a transformation matrix for transforming the coordinates of the RGB coordinate system output by the imaging equipment into the coordinates of the coordinate system of the color system;
obtaining a lookup table for converting the coordinates of the RGB coordinate system to the coordinates of the color system coordinate system through the conversion matrix;
respectively imaging the sample and the product, and respectively obtaining the coordinates of the sample and the product in a coordinate system of a color system 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 the coordinate system of the color system.
6. The color difference measurement method according to claim 5, wherein the color calibration is performed in the imaging environment to obtain a transformation matrix for transforming coordinates of an RGB coordinate system output by the imaging device into coordinates of a color coordinate system, and specifically comprises:
extracting color data of the color card;
establishing a color calibration model based on the extracted color data of the color chart;
and acquiring a conversion matrix for converting the coordinates of the RGB coordinate system to the coordinates of the color system coordinate system based on the parameters of the color calibration model.
7. The color difference measurement method according to claim 6, wherein the extracting of the color chip color data specifically comprises:
extracting color card CIE color data and color card image RGB data.
8. The color difference measurement method according to claim 6, wherein the color calibration model is:
O＝LUT(i,j,k)＝LUT(P)
wherein the content of the first and second substances,
p is an input color space color value, and P ═ ijk is a representation of the color value of the input color space;
o is an output color space color value;
LUT () is a color space conversion look-up table.
9. 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 in the imaging environment;
the system conversion unit is used for converting the coordinates of the RGB coordinate system output by the imaging equipment into the coordinates of the coordinate system of the color 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 coordinate system of a color 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 coordinate system of the color system.
10. An intelligent terminal, characterized in that, 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 to store one or more program instructions; the processor, configured to execute one or more program instructions to perform the method of any of claims 1-8.
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