CN112985605A

CN112985605A - Three-dimensional object color difference calculation method and device and three-dimensional object color difference calculation system

Info

Publication number: CN112985605A
Application number: CN202110179108.1A
Authority: CN
Inventors: 黄敏; 陈伟; 向东清; 李修; 潘洁
Original assignee: Zhuhai Sailner 3D Technology Co Ltd
Current assignee: Zhuhai Sailner 3D Technology Co Ltd
Priority date: 2021-02-09
Filing date: 2021-02-09
Publication date: 2021-06-18
Anticipated expiration: 2041-02-09
Also published as: CN112985605B; WO2022170747A1

Abstract

The application relates to a three-dimensional object color difference calculation method and device and a three-dimensional object color difference calculation system, wherein the three-dimensional object color difference calculation method is used for constructing a color difference fitting function by utilizing calculation color difference value samples and visual color difference value samples between a plurality of different color blocks in a gray ladder ruler and a target color block, and then utilizing the color difference fitting function to calculate a first calculation visual color difference value between a standard sample three-dimensional object model and a sample three-dimensional object model; according to the first chromatic value of the standard sample three-dimensional object model, the second chromatic value of the sample three-dimensional object model, the first calculated chromatic difference value and the first calculated visual chromatic difference value, the primary chromatic difference calculation formula is optimized, so that the chromatic difference of the three-dimensional object can be more accurately evaluated through the second calculated chromatic difference value calculated by the optimized chromatic difference calculation formula.

Description

Three-dimensional object color difference calculation method and device and three-dimensional object color difference calculation system

Technical Field

The application relates to the technical field of three-dimensional object color evaluation, in particular to a three-dimensional object color difference calculation method and device and a three-dimensional object color difference calculation system.

Background

The color is an information carrier, and can convey richer information than a single color, and the color can bring a beautiful feeling to people. Accurate color transfer, reproduction and evaluation calculation are key problems to be solved in the color science field and the industry. In order to quantitatively characterize object colors and further compare differences among different object colors, the international commission on illumination (hereinafter, referred to as "CIE") proposes a uniform color space and a color difference calculation formula for color calculation and evaluation. CIE existing color space, such as: CIELAB, CIELUV, CIECAM02, CIECAM16 color appearance models, etc. were created based on two-dimensional planar colors of different substrates.

Since a three-dimensional object has a shape different from that of a two-dimensional planar object, under the illumination of scattered light or a directional light source, the appearance color of the three-dimensional object is affected by factors such as the illumination angle of the light source, the shape of the object, translucency, texture and the like, and even colors having the same chromaticity value cause a phenomenon that the color of an observer feels inconsistence. Therefore, when comparing the color difference of the three-dimensional object, the overall perception of the object color by the observer needs to be considered, and the conventional color difference evaluation method has low accuracy.

Disclosure of Invention

The application provides a three-dimensional object color difference calculation method and device and a three-dimensional object color difference calculation system, which are used for improving the color difference calculation accuracy of a three-dimensional object.

In a first aspect, the present application provides a method for calculating color difference of a three-dimensional object, the method comprising:

constructing a color difference fitting function according to a calculated color difference value sample and a visual color difference value sample between a plurality of different color blocks in the gray scale and a target color block; performing color difference calculation according to a primary color difference calculation formula, a first chromatic value of a standard sample three-dimensional object model and a second chromatic value of a sample three-dimensional object model to obtain a first calculated color difference value delta E between the standard sample three-dimensional object model and the sample three-dimensional object model_i(ii) a Wherein, the colors of the standard sample three-dimensional object model and the sample three-dimensional object model in the original color difference calculation formula are in the same color system; acquiring an average visual color difference value between the standard sample three-dimensional object model and the sample three-dimensional object model, which is obtained by a user based on the gray scale;obtaining a first calculated visual color difference value DeltaV between the standard sample three-dimensional object model and the sample three-dimensional object model according to the color difference fitting function and the average visual color difference value_i(ii) a Optimizing the primary color difference calculation formula according to the first chromatic value, the second chromatic value, the first calculated color difference value and the first calculated visual color difference value, so that a STRES value between the second calculated color difference value calculated according to the optimized color difference calculation formula and the first calculated visual color difference value is smaller than a STRES value between the first calculated color difference value and the first calculated visual color difference value; and performing color difference calculation on the three-dimensional object to be evaluated according to the optimized color difference calculation formula.

With reference to the first aspect, in a possible implementation manner, the optimizing the primary color difference calculation formula according to the first chromatic value, the second chromatic value, the first calculated color difference value, and the first calculated visual color difference value includes:

determining a first calculated color difference value Delta E between the three-dimensional object model of the standard sample and the three-dimensional object model of the test sample_iThe first color difference calculation formula after optimization is less than or equal to a preset threshold value, and is shown as a formula (VII):

△E”＝a△E’^bformula (VII) and

wherein l is a brightness value optimization coefficient,

representing the lightness values of a three-dimensional object model of the specimen,

chromaticity parameters representing the color of the three-dimensional object model of the test specimen,

representing the lightness value of the three-dimensional object model of the standard sample,

chromaticity parameters representing the color of the three-dimensional object model of the standard sample;

using the optimized first color difference calculation formula to calculate the color difference value between the sample three-dimensional object model and the standard sample three-dimensional object model, so that the STRES value between the second calculated color difference value calculated according to the optimized first color difference calculation formula and the first calculated visual color difference value is minimum;

the values of a, b, l in the formula (VII) are determined based on the minimum STRESS value.

determining a first calculated color difference value Delta E between the three-dimensional object model of the standard sample and the three-dimensional object model of the test sample_i>Presetting a threshold value, wherein the optimized calculation formula of the second color difference is shown as a formula (VIII):

Δ E ═ k Δ E' + c formula (VIII), and

wherein l is a brightness value optimization coefficient;

using the optimized second color difference calculation formula to calculate the color difference value between the sample three-dimensional object model and the standard three-dimensional object model, so that the STRES value between the second calculated color difference value calculated according to the optimized second color difference calculation formula and the first calculated visual color difference value is minimum;

the values of k, l, c in the formula (VIII) are determined based on the minimum STRESS value.

With reference to the first aspect, in a possible implementation manner, the performing, according to the optimized color difference calculation formula, color difference calculation on the three-dimensional object to be evaluated includes:

acquiring a chromatic value of a three-dimensional object to be evaluated; calculating according to a primary color difference calculation formula, a target chromatic value and a chromatic value of the three-dimensional object to be evaluated to obtain a first calculated chromatic difference value delta E of the three-dimensional object to be evaluated_i(ii) a And when the first calculated color difference value is less than or equal to the preset threshold value, calling the optimized first color difference calculation formula to calculate a second calculated color difference value of the three-dimensional object to be evaluated.

With reference to the first aspect, in one possible implementation manner, the target chromaticity value is

The colorimetric value of the three-dimensional object to be evaluated is

The original color difference calculation formula is a CIELAB color difference calculation formula, and the optimized first color difference calculation formula is as follows:

△E”＝2.32△E’^0.26and is and

or, the original color difference calculation formula is a CIEDE2000 color difference calculation formula, and the optimized first color difference calculation formula is as follows:

△E”＝1.99△E’^0.33and is and

acquiring a chromatic value of a three-dimensional object to be evaluated; calculating according to a primary color difference calculation formula, a target chromatic value and a chromatic value of the three-dimensional object to be evaluated to obtain a first calculated chromatic difference value delta E of the three-dimensional object to be evaluated_i(ii) a When the first calculated color difference value>And calling the optimized second color difference calculation formula to calculate a second calculated color difference value of the three-dimensional object to be evaluated when the threshold value is preset.

The colorimetric value of the three-dimensional object to be evaluated is

The primary color difference calculation formula is a CIELAB color difference calculation formula, and the optimized secondary color difference calculation formula is as follows:

Δ E ″ + 0.81 Δ E' +1.50, and

or, the original color difference calculation formula is a CIEDE2000 color difference calculation formula, and the optimized second color difference calculation formula is:

Δ E ″ + 0.45 Δ E' +3.14, and

with reference to the first aspect, in one possible implementation, the preset threshold is 5.0.

With reference to the first aspect, in a possible implementation manner, the calculation formula of the STRESS value is shown as formula (VI),

and is

Wherein, Δ V_iFor a first calculated apparent color difference value, Delta E, between the ith specimen three-dimensional object model and the standard specimen three-dimensional object model_iCalculating a first color difference value between the ith sample three-dimensional object model and the standard sample three-dimensional object model; m is the number of the standard sample three-dimensional object models, and n is the number of the sample three-dimensional object models in the same color system.

With reference to the first aspect, in one possible embodiment, the method satisfies at least one of the following features (1) to (7):

(1) the gray ladder ruler, the standard sample three-dimensional object model and the sample three-dimensional object model are obtained by adopting a three-dimensional printing technology;

(2) the minimum dimension of the three-dimensional object model of the standard sample is greater than or equal to 4 cm;

(3) the standard sample three-dimensional object model is a solid model with a regular shape and a single color;

(4) the number of the standard sample three-dimensional object models is m, and m is an integer greater than or equal to 5;

(5) the color of the standard three-dimensional object model is selected from the colors of color centers recommended by the international commission on illumination, and the colors of a plurality of standard three-dimensional object models are different;

(6) the number of the sample three-dimensional object models in the same color system is n times of the number of the standard sample three-dimensional object models in the same color system, and n is an integer greater than or equal to 30;

(7) the shape and the dimension of the sample three-dimensional object model and the standard sample three-dimensional object model in the same color system are consistent.

With reference to the first aspect, in a possible embodiment, the number of the standard three-dimensional object models is 5, and the colors of the 5 standard three-dimensional object models are respectively selected from gray, red, yellow, green and blue, wherein the chroma values of gray are (62.0, 0.0, 0.0), the chroma values of red are (44.0, 37.0, 23.0), the chroma values of yellow are (87.0, -7.0, 47.0), the chroma values of green are (56.0, -32.0, 0.0), and the chroma values of blue are (36.0, 5.0, -31.0).

With reference to the first aspect, in a possible implementation manner, before the calculating according to the primary color difference calculation formula, the first chromaticity value of the standard three-dimensional object model, and the second chromaticity value of the sample three-dimensional object model, the method further includes:

measuring colorimetric values of at least 5 different positions of each standard sample three-dimensional object model, and calculating an average value of the colorimetric values to obtain a first colorimetric value of the standard sample three-dimensional object model;

and measuring colorimetric values of at least 5 different positions of each sample three-dimensional object model, and calculating an average value of the colorimetric values to obtain a second colorimetric value of the sample three-dimensional object model.

With reference to the first aspect, in a possible implementation manner, after the calculating according to the primary color difference calculation formula, the first chromaticity value of the standard three-dimensional object model, and the second chromaticity value of the sample three-dimensional object model, and before the obtaining of the average visual color difference value between the standard three-dimensional object model and the sample three-dimensional object model, which is obtained by the user based on the gray scale, the method further includes:

and screening the effectiveness of the plurality of first calculated color difference values so that the first calculated color difference values are within a preset range.

With reference to the first aspect, in a possible implementation manner, when the first calculated color difference value is a CIELAB color difference value, the CIELAB color difference value is distributed between 0.0 and Δ E_maxWithin range, Delta E_maxNot less than 10.0.

With reference to the first aspect, in a possible implementation manner, before the constructing the color difference fitting function according to the calculated color difference value samples and the visual color difference value samples between the plurality of different color patches and the target color patch in the gray scale, the method further includes:

printing a target color block and a plurality of different color blocks of the same color system; measuring the colorimetric values of a target color block and each different color block, and calculating a calculated color difference value between the colorimetric value of each different color block and the colorimetric value of the target color block; and taking the calculated color difference value of each different color block as a calculated color difference value sample, and taking the integral value of the calculated color difference value of each different color block as a visual color difference value sample.

With reference to the first aspect, in one possible implementation, the method further includes: and screening the effectiveness of a plurality of visual color difference value samples to ensure that the visual color difference value samples are within a preset range.

With reference to the first aspect, in one possible embodiment, the method satisfies at least one of the following features (1) to (3):

(1) the chroma values of the different color blocks are sequentially increased or decreased by taking the preset chroma value of the target color block as a center;

(2) the thickness of the color block is less than or equal to 1mm, and the side length of the color block is consistent with the minimum dimension of the sample three-dimensional object model;

(3) the number of the calculated color difference value samples and the number of the visual color difference value samples are both greater than or equal to 12.

With reference to the first aspect, in one possible embodiment, the visual color difference value samples of the plurality of different color blocks are distributed between 0.0 and Δ V_max，△V_max≥△E_max，△E_maxNot less than 10.0.

With reference to the first aspect, in a possible implementation manner, before the obtaining an average visual color difference value between the standard three-dimensional object model and the sample three-dimensional object model obtained by the user based on the gray scale, the method further includes:

and carrying out precision inspection on visual color difference values between the plurality of standard sample three-dimensional object models and the sample three-dimensional object model, and deleting abnormal values.

With reference to the first aspect, in a possible implementation manner, performing precision check on the plurality of visual color difference values by using a tress 'value, where a calculation formula of the tress' value is shown as formula (V), a value range of the tress 'value is between 0 and 100, and deleting the visual color difference values with the tress' value greater than 100;

and is

Wherein, Delta E'_iThe average value of visual color difference values of all users to the ith sample three-dimensional object model is delta V'_iFor the user's visual color difference value for the ith sample three-dimensional object model, i is 1, 2.

With reference to the first aspect, in a possible implementation, an average of the values of the STRESS' of all the users retained with respect to the ith sample three-dimensional object model is less than or equal to 40.

With reference to the first aspect, in a possible embodiment, the average visual color difference value refers to an average value of the visual color difference values of all users on the ith sample three-dimensional object model.

In a second aspect, the present application provides a three-dimensional object color difference calculation apparatus, the apparatus comprising:

the acquisition unit is used for acquiring the chromatic value of the three-dimensional object to be evaluated;

a first calculating unit, configured to perform color difference calculation according to a primary color difference calculation formula, a target chromaticity value, and a chromaticity value of the three-dimensional object to be evaluated to obtain a first calculated color difference value Δ E of the three-dimensional object to be evaluated_i；

The first calling unit is used for calling the optimized first color difference calculation formula to calculate a second calculated color difference value of the three-dimensional object to be evaluated when the first calculated color difference value is smaller than or equal to a preset threshold value;

and the second calling unit is used for calling the optimized second color difference calculation formula to calculate a second calculated color difference value of the three-dimensional object to be evaluated when the first calculated color difference value is larger than a preset threshold value.

In combination with the second aspect, in one possible embodiment, the preset threshold is 5.0.

In one possible embodiment, the target chromaticity value is

The colorimetric value of the three-dimensional object to be evaluated is

Wherein L is^*Represents a lightness value, a^*，b^*A chromaticity parameter representing a color; when the first calculated color difference value is less than or equal to 5.0, the original color difference calculation formula is a CIELAB color difference calculation formula, and the optimized first color difference calculation formula is as follows:

△E”＝2.32△E’^0.26and is and

△E”＝1.99△E’^0.33and is and

in a possible embodiment, in combination with the second aspect, the target chromaticity value is

The colorimetric value of the three-dimensional object to be evaluated is

Wherein L is^*Represents a lightness value, a^*，b^*A chromaticity parameter representing a color; when the first calculated color difference value>At 5.0, the original color difference calculation formula is a CIELAB color difference calculation formula, and the optimized second color difference calculation formula is as follows:

△E”＝0.81△E’+1.50, and

Δ E ″ + 0.45 Δ E' +3.14, and

in a third aspect, the present application provides a computer non-volatile storage medium, where the storage medium includes a stored program, and when the program runs, the apparatus on which the storage medium is located is controlled to execute the color difference calculation formula optimized in the three-dimensional object color difference calculation method according to the first aspect of the present application.

In a fourth aspect, the present application provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the optimized color difference calculation formula in the three-dimensional object color difference calculation method according to the first aspect when executing the computer program.

In a fifth aspect, the present application provides a three-dimensional object color difference calculation system, which includes a detection component, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements an optimized color difference calculation formula in the three-dimensional object color difference calculation method according to the first aspect when executing the computer program.

Has the advantages that:

in the scheme, a chromatic aberration fitting function is constructed by utilizing calculated color difference value samples and visual color difference value samples between a plurality of different color blocks in a gray scale and a target color block, then a first calculated visual color difference value between a standard sample three-dimensional object model and a sample three-dimensional object model is calculated by utilizing the chromatic aberration fitting function, the first calculated color difference value is calculated according to a primary color difference calculation formula, the primary color difference calculation formula is optimized according to the first calculated visual color difference value, the first calculated color difference value, the first chromatic value and the second chromatic value, and the chromatic aberration of the three-dimensional object can be more accurately evaluated by obtaining the second calculated color difference value through the optimized chromatic aberration calculation formula. According to the scheme, the three-dimensional object is evaluated by not directly adopting a color difference evaluation method of the two-dimensional object, and the accuracy of color difference evaluation of the three-dimensional object is improved by optimizing a color difference calculation formula suitable for color difference evaluation of the two-dimensional object.

Drawings

The present application is further described below with reference to the drawings and examples.

FIG. 1 is a schematic flow chart of a method for calculating chromatic aberration of a three-dimensional object according to an embodiment of the present application;

FIG. 2 is a distribution of scattering points of visual color difference values and calculated color difference values (CIELAB color difference) between color patches in a specific embodiment of the present application;

FIG. 3 is a scatter plot distribution of visual color difference values and calculated color difference values (CIEDE2000) between color patches in a specific embodiment of the present application;

FIG. 4 is a graph of a second chrominance value of the three-dimensional object model printed with the first chrominance value of the three-dimensional object model of the standard sample in accordance with an embodiment of the present invention

Scatter distribution on a plane;

FIG. 5 is a graph of a second colorimetric value of a sample three-dimensional object model and a first colorimetric value of a standard three-dimensional object model in an embodiment of the present application

Scatter distribution on a plane;

FIG. 6 is a distribution of scattering points between a first calculated color difference value and a first calculated visual color difference value calculated using an original CIELAB color difference calculation formula recommended by CIE and between a second calculated color difference value and the first calculated visual color difference value calculated using an optimized CIELAB color difference calculation formula in an embodiment of the present application, where the original CIELAB color difference is less than or equal to 5.0;

FIG. 7 is a dispersion point distribution between a first calculated color difference value and a first calculated visual color difference value calculated using an original CIELAB color difference calculation formula recommended by CIE and a dispersion point distribution between a second calculated color difference value and the first calculated visual color difference value calculated using an optimized CIELAB color difference calculation formula in an embodiment of the present application, where the original CIELAB color difference is greater than 5.0;

FIG. 8 is a distribution of scattering points between a first calculated color difference value and a first calculated visual color difference value calculated using an original CIEDE2000 color difference calculation formula recommended by CIE and between a second calculated color difference value and the first calculated visual color difference value calculated using an optimized CIEDE2000 color difference calculation formula in an embodiment of the present application, where the original CIEDE2000 color difference is less than or equal to 5.0;

FIG. 9 is a graph of the scatter distribution between a first calculated color difference value and a first calculated visual color difference value calculated using the CIEDE2000 color difference calculation formula recommended by the CIE and the scatter distribution between a second calculated color difference value and the first calculated visual color difference value calculated using the CIEDE2000 color difference calculation formula after optimization in accordance with an exemplary embodiment of the present application, where the original CIEDE2000 color difference is greater than 5.0;

FIG. 10 is a block diagram of an apparatus for calculating color difference of a three-dimensional object according to another embodiment of the present application;

FIG. 11 is a block diagram illustrating a computer device according to another embodiment of the present application;

fig. 12 is a block diagram illustrating a structure of a system for calculating color difference of a three-dimensional object according to another embodiment of the present disclosure.

Detailed Description

For better understanding of the technical solutions of the present invention, the following detailed descriptions of the embodiments of the present invention are provided with reference to the accompanying drawings.

It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. 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.

The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention 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 understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

Fig. 1 is a schematic flow chart of a three-dimensional object color difference calculation method in an embodiment of the present application, where the three-dimensional object color difference calculation method includes the following steps S10 to S60:

step S10, constructing a color difference fitting function according to the calculated color difference value samples and the visual color difference value samples between a plurality of different color blocks in the gray scale and the target color block;

step S20, performing color difference calculation according to a primary color difference calculation formula, a first color value of the standard sample three-dimensional object model and a second color value of the sample three-dimensional object model to obtain a first calculated color difference value Delta E between the standard sample three-dimensional object model and the sample three-dimensional object model_i(ii) a Wherein, the colors of the standard sample three-dimensional object model and the sample three-dimensional object model in the original color difference calculation formula are in the same color system;

step S30, obtaining an average visual color difference value between the standard sample three-dimensional object model and the sample three-dimensional object model, which is obtained by a user based on the gray scale;

step S40, obtaining a first calculated visual color difference value DeltaV between the standard sample three-dimensional object model and the sample three-dimensional object model according to the color difference fitting function and the average visual color difference value_i；

Step S50, optimizing the primary color difference calculation formula according to the first color value, the second color value, the first calculated color difference value, and the first calculated visual color difference value, so that a STRESS value between the first calculated visual color difference value and the second calculated color difference value calculated according to the optimized color difference calculation formula is smaller than a STRESS value between the first calculated color difference value and the first calculated visual color difference value;

and step S60, performing color difference calculation on the three-dimensional object to be evaluated according to the optimized color difference calculation formula.

In the scheme, a color difference fitting function is constructed by utilizing calculated color difference value samples and visual color difference value samples of a plurality of different color blocks and target color blocks in a gray scale, then a first calculated visual color difference value between a standard sample three-dimensional object model and a sample three-dimensional object model is calculated by utilizing the color difference fitting function, the first calculated color difference value is calculated according to a primary color difference calculation formula, the primary color difference calculation formula is optimized according to the first calculated visual color difference value, the first calculated color difference value, the first chromatic value and the second chromatic value, and the color difference of the three-dimensional object can be evaluated more accurately by obtaining the second calculated color difference value through the optimized color difference calculation formula. According to the scheme, the three-dimensional object is evaluated by not directly adopting a color difference evaluation method of the two-dimensional object, and the accuracy of color difference evaluation of the three-dimensional object is improved by optimizing a color difference calculation formula suitable for color difference evaluation of the two-dimensional object.

The following describes the present solution in detail with reference to the embodiments and the calculation method provided by the present application:

prior to step S10, the method includes:

step S01, printing a target color block and a plurality of different color blocks of the same color system;

step S02, measuring the colorimetric values of the target color block and each different color block, and calculating the calculated color difference value between the colorimetric value of each different color block and the colorimetric value of the target color block;

and step S03, taking the calculated color difference value of each of the different color blocks as a calculated color difference value sample, and taking an integer value obtained by rounding the calculated color difference value of each of the different color blocks as a visual color difference value sample.

In a specific embodiment, the gray scale is a plurality of color patches with sequentially increasing or decreasing chromatic values, the plurality of color patches may correspond to the same target color patch, and in this embodiment, it is preferable that each color patch corresponds to a separate target color patch. The gray scale refers to gray blocks with different chromatic values arranged in multiple levels between black and white. The gray scale includes gray blocks with different chromaticity values of at least 10 levels, each gray block has the same area, and the gray scale can be divided into 11 levels, 12 levels, 13 levels, 14 levels, 15 levels, 16 levels and the like.

In this embodiment, a plurality of color blocks in the gray scale and a target color block are printed and formed by using a three-dimensional printing technology. And printing a plurality of target color blocks by taking gray colorimetric values (50.0, 0.0 and 0.0) as input values, and printing a plurality of different color blocks in a gray system, wherein the thickness of each color block is less than or equal to a cuboid of 1mm, and the side length of each color block is consistent with the minimum dimension of the sample three-dimensional object model. Illustratively, the color block is a rectangular parallelepiped having a length of 4cm × a width of 4cm × a height of 1mm, and correspondingly, the smallest dimension of the sample three-dimensional object model should be equal to 4cm, and for example, it may be a three-dimensional object having a length of 4cm × a width of 5cm × a height of 4 cm.

Further, an integer value obtained by rounding the calculated color difference value of each of the different color blocks is used as a visual color difference value sample, which may also be referred to as a color difference level for short. The rounding method can be a rounding method, for example, if the calculated color difference value of the first color block is 1.14, the visual color difference value is 1.0, or called color difference level is 1, and the calculated color difference value of the ninth color block is 8.96, the visual color difference value is 9.0, or called color difference level is 9.

In this embodiment, a plurality of color blocks with different visual color difference values are selected, and the visual color difference values of the plurality of color blocks are distributed from 0.0 to Δ V_max，△V_max≥△E_max，△E_maxNot less than 10.0. And arranging the selected color blocks in a mode of sequentially increasing or decreasing the visual color difference values to form a gray scale, wherein the visual color difference values of the color blocks are changed at intervals of 1.0.

Specifically, the visual color difference value of the gray scale is between 0.0 and 14.0, for example, the visual color difference value between the target color block and the fifth color block is 5.0, and the visual color difference value between the target color block and the tenth color block is 10.0.

In this embodiment, in step S02, the calculated color difference value of the color patch can be obtained by measuring the chromaticity values of the printed target color patch and different color patches with an X-Rite exact spectrophotometer under the measurement condition of D65 and 10 ° field of view, and further calculating according to the chromaticity value obtained by measurement and the primary color difference calculation formula. Specifically, the method for measuring the colorimetric value of the color block comprises the following steps:

and measuring the colorimetric values of at least 5 different positions of each color block, and calculating the average value of the colorimetric values to obtain the colorimetric values of the color blocks.

In particular, said at least 5 different positions are preferably smudge-free, scratch-free positions.

And then according to the measured colorimetric values of the target color block and different color blocks, calculating by using a primary color difference calculation formula to obtain the calculated color difference value of the different color blocks relative to the target color block.

In one embodiment, the primary color difference calculation formula is a CIELAB color difference calculation formula, as shown in formula I:

wherein L is^*Represents a lightness value, a^*，b^*A chromaticity parameter representing a color.

In another embodiment, the color difference calculation formula used is a CIEDE2000 color difference calculation formula, which is abbreviated as formula II in this embodiment, and the CIEDE2000 color difference calculation formula is one of color difference calculation formulas recommended by the commission internationale de l' eclectic lighting, which is directly cited herein and is not specifically listed.

Through measurement, color chrominance information of 14 blocks of different color lumps and chrominance information of a target color lump corresponding to the color chrominance information are obtained, and color difference values of the 14 blocks of different chrominance values and the target color lump are further calculated and obtained and are shown in table 1.

TABLE 1 color chroma information of color blocks of different visual color difference values

As can be seen from Table 1, the brightness differences between the different color blocks and the target color block

And calculating the color difference value

The ratio therebetween is

Therefore, the present application considers that the color difference between the color patches of different visual color difference values and the target color patch is mainly caused by the brightness difference.

Further, before step S03, in order to ensure color uniformity of the color patches and to calculate validity of the color difference samples, the method further includes:

and screening the effectiveness of a plurality of samples of the calculated color difference values so that the samples of the calculated color difference values are within a preset range.

In this embodiment, the CIELAB color difference is taken as an example by calculating the average color difference at different positions of a single color block, and the average color difference is not more than 1.0. Specifically, the step of calculating the chromatic aberration includes: and calculating the color difference between the chroma value of any position of the single color block and the average value of the chroma values of different positions of the single color block.

And obtaining a plurality of effective calculation color difference value samples and a plurality of effective visual color difference value samples after effectiveness screening. In this embodiment, the number of valid calculated color difference value samples and the number of valid visual color difference value samples are both greater than or equal to 12.

And step S10, constructing a color difference fitting function according to the calculated color difference value samples and the visual color difference value samples of a plurality of different color blocks and target color blocks in the gray scale.

And constructing a color difference fitting function according to the previously obtained calculated color difference value sample and the visual color difference value sample, namely calculating a mathematical trend relation between the color difference value and the visual color difference value. In this embodiment, the fitting function is fitted using a linear function.

Specifically, linear fitting is performed on the visual color difference values of the plurality of color blocks and the calculated color difference values of the color blocks calculated by the color difference calculation formula by using a linear trend line in data processing software such as Excel software, so that a relation function between the visual color difference values and the calculated color difference values is obtained.

In one embodiment, a CIELAB color difference calculation formula is used, and after linear fitting processing, a color difference fitting function is obtained as shown in formula III below:

y_Lab＝0.9647x_Lab+0.2302 (formula III);

wherein x is_LabIs the visual color difference value between the color block and the target color block (corresponding to the visual color difference value or color difference level in Table 1), y_LabIs the calculated color difference value between the calculated color patch and the target color patch (corresponding to that in Table 1)

). The scatter distribution of the visual color difference values and the calculated color difference values (i.e., CIELAB color differences) between the patches and the target patches in the specific embodiment of the present application is shown in fig. 2.

In another embodiment, a CIEDE2000 color difference calculation formula is used to calculate the color difference value between a color block and a target color block, and the obtained color difference fitting function is shown as the following formula IV:

y_DE2000＝0.8711x_DE2000+0.6767 (formula IV);

wherein x is_DE2000Is the visual color difference value between the color block and the target color block (corresponding to the visual color difference value or color difference level in Table 1), y_DE2000Is the calculated color difference value between the calculated color patch and the target color patch (corresponding to that in Table 1)

). The scatter distribution of the visual color difference values and the calculated color difference values (i.e., CIEDE2000) among the color blocks in the embodiment of the present application is shown in fig. 3, and it can be seen that the visual color difference values and the calculated color difference values satisfy a linear relationship.

Further, before step S20, the method further includes:

step S11, a three-dimensional object model of the standard is obtained, and a first colorimetric value of the three-dimensional object model of the standard is measured.

In the embodiment, the three-dimensional object model of the standard sample is printed and formed by adopting a three-dimensional printing technology. The minimum dimension of the standard sample three-dimensional object model is greater than or equal to 4cm, and the standard sample three-dimensional object model is a solid model which is in a regular shape and is monochromatic, such as a sphere, a cube, a cone and the like. Illustratively, the three-dimensional object model of the standard may be a rectangular parallelepiped of 5cm long by 5cm wide by 4cm high.

The number of the standard sample three-dimensional object models is m, and m is an integer greater than or equal to 5.

The color of the standard three-dimensional object model is selected from colors of color centers recommended by the international commission on illumination, and the colors of a plurality of the standard three-dimensional object models belong to different color systems. In this embodiment, a standard three-dimensional object model of 5 spheres is obtained by printing, the diameter of the sphere is 4cm, and the colors of the 5 standard three-dimensional object models are gray, red, yellow, green and blue, respectively. Specifically, the chromaticity values set at the time of printing for the gray scale three-dimensional object model are (62.0, 0.0, 0.0), the chromaticity values set at the time of printing for the red scale three-dimensional object model are (44.0, 37.0, 23.0), the chromaticity values set at the time of printing for the yellow scale three-dimensional object model are (87.0, -7.0, 47.0), the chromaticity values set at the time of printing for the green scale three-dimensional object model are (56.0, -32.0, 0.0), and the chromaticity values set at the time of printing for the blue scale three-dimensional object model are (36.0, 5.0, -31.0).

Further, the first colorimetric values of the 5 standard sample three-dimensional object models obtained by printing are measured by using an X-Rite exact spectrophotometer under the measurement condition of D65 and 10-degree visual field, and the specific measurement method comprises the following steps:

measuring colorimetric values of at least 5 different positions of each standard sample three-dimensional object model, and calculating an average value of the colorimetric values to obtain a first colorimetric value of the standard sample three-dimensional object model.

Further, in order to ensure the color uniformity of the standard sample three-dimensional object model and the sample effectiveness, the surface of the selected standard sample three-dimensional object model should have uniform color. The method further comprises the following steps:

and screening a plurality of standard sample three-dimensional object models to be selected to obtain effective standard sample three-dimensional object models.

In this embodiment, whether the surface color of the three-dimensional object model is uniform can be determined by calculating the average color differences of the single sample three-dimensional object model at different positions, so as to determine whether the sample three-dimensional object model is an effective sample three-dimensional object model. Specifically, the step of calculating the chromatic aberration includes: and calculating the color difference between the colorimetric value of any position of the single standard sample three-dimensional object model and the average value of the colorimetric values of different positions of the standard sample three-dimensional object model.

And determining that the off-average color difference of the three-dimensional object model of the standard sample is less than or equal to a first preset value. In this embodiment, the first preset value is 1.0 by CIELAB color difference calculation. When the off-average color difference of the three-dimensional object model of the standard sample is less than or equal to 1.0, the surface color of the three-dimensional object model of the standard sample meets the requirement of uniformity, and the three-dimensional object model of the standard sample can be used as an effective three-dimensional object model of the standard sample.

In this embodiment, the first colorimetric values of the three-dimensional object model of the standard sample obtained by printing and subjected to validity screening are shown in table 2:

TABLE 2 first chroma value distribution of a three-dimensional object model of a standard

Wherein the content of the first and second substances,

and chromaticity parameters representing the colors of the three-dimensional object model of the standard sample.

Representing the color saturation of the three-dimensional object model of the standard,

and representing hue angles of the three-dimensional object model of the standard sample.

Likewise, prior to step S20, the method further comprises:

step S12, a sample three-dimensional object model is acquired, and a second chromaticity value of the sample three-dimensional object model is measured.

In the embodiment, the sample three-dimensional object model is printed and formed by using a three-dimensional printing technology. And the number of the sample three-dimensional object models of the same color system is n times of the number of the standard sample three-dimensional object models of the same color system, and n is an integer greater than or equal to 30. In this embodiment, the number of sample three-dimensional object models is 30 times the number of sample three-dimensional object models of the same color system, that is, 30 blue sample three-dimensional object models are arranged for 1 blue sample three-dimensional object model.

The steps S11 and S12 may be performed synchronously or asynchronously, and are not limited herein. The equipment for printing the three-dimensional object model of the standard sample is the same as the equipment for printing the three-dimensional object model of the sample, and the shape and the dimensionality of the three-dimensional object model of the sample are also the same as those of the three-dimensional object model of the standard sample.

In order to improve the accuracy of the experimental data, the measurement condition, the measurement method, the calculation method of the self-uniform color difference and the requirement of the self-uniform color difference of the second chromaticity value of the sample three-dimensional object model are the same as the measurement condition, the measurement method, the calculation method of the self-uniform color difference and the requirement of the self-uniform color difference of the first chromaticity value of the standard sample three-dimensional object model, and are not repeated herein.

Scatter distribution on a plane; FIG. 5 is a second chromaticity value of a model of a sample three-dimensional object in an embodiment of the present applicationWith a first colorimetric value of a model of the three-dimensional object of the standard

Scatter distribution on the plane. As shown in fig. 4 and 5, in the present embodiment, the color tones of the sample sphere model are uniformly distributed around the color tones of the standard sphere model of the color system corresponding thereto, and the lightness and saturation values of the sample sphere model are uniformly distributed around the lightness and saturation values of the standard sphere model of the color system corresponding thereto; the color difference between the sample sphere model and the standard sphere model is caused by hue difference, lightness difference and saturation difference, respectively.

Step S20, performing color difference calculation according to a primary color difference calculation formula, a first color value of the standard sample three-dimensional object model and a second color value of the sample three-dimensional object model to obtain a first calculated color difference value Delta E between the standard sample three-dimensional object model and the sample three-dimensional object model_i(ii) a And the colors of the standard sample three-dimensional object model and the sample three-dimensional object model in the color difference calculation formula are in the same color system.

It can be understood that 30 sample three-dimensional object models of the same color system and the corresponding standard sample three-dimensional object models are subjected to color difference value calculation. It should be noted that the color difference values calculated by different color difference calculation formulas are different, in this embodiment, a CIELAB color difference calculation formula I is taken as an example:

In the present application, when the first calculated color difference value is a CIELAB color difference value, the CIELAB color difference distribution of the plurality of sample three-dimensional object models and the standard three-dimensional object model is 0.0 to Δ E_maxRange, Δ E_maxNot less than 10.0. Preferably, the CIELAB color difference is between 0.0 and 3.0, between 3.0 and 5.0, and between 5.0 and delta E_maxThe three different color difference levels are evenly distributed.

The color difference of CIELAB is limited to 0.0-3.0, 3.0-5.0, 5.0-delta E_maxThree different color difference grades are uniformly distributed, so that samples can be guaranteed to exist in all the color difference grades, and the accuracy of a color difference optimization formula is improved.

Table 3 shows the CIELAB color difference distribution between the three-dimensional object models of 150 specimens and the three-dimensional object model of the standard specimen, where Δ E_maxIs 12:

TABLE 3 CIELAB color difference distribution of sample three-dimensional object model and standard three-dimensional object model

Color difference distribution	0～1	1～3	3～5	5～8	8～12
						Number of	7	38	44	39	22
Percentage of	4.7％	25.3％	29.3％	26.0％	14.7％

Step S10 and step S20 may be performed synchronously or asynchronously, and are not limited herein.

And step S30, obtaining an average visual color difference value between the standard sample three-dimensional object model and the sample three-dimensional object model, which is obtained by the user based on the gray scale.

In the application, the user obtains the average visual color difference value between the sample three-dimensional object model and the standard sample three-dimensional object model based on the gray scale as a standard. When the visual color difference value between the sample three-dimensional object model and the standard sample three-dimensional object model is between the visual color difference values of the two color blocks in the gray scale, the decimal can be given between the two visual color difference values. For example, assuming that the visual color difference value of the sample three-dimensional object model and the standard three-dimensional object model is between 5.0 and 6.0 of the visual color difference value of the gray scale, the visual color difference value between the sample three-dimensional object model and the standard three-dimensional object model may be 5.8.

Specifically, a plurality of visual color difference values between at least 30 color-vision-normal male and female observers with respect to the sample three-dimensional object model and the standard three-dimensional object model may be acquired, and an average value of the plurality of visual color difference values, that is, an average visual color difference value may be obtained. Wherein the number of women is greater than the number of men, and the age distribution of the observers is between 20 and 32 years. In the embodiment, 33 observers with 22 male and female persons and ages of 20-24 years are organized, the observation is carried out in groups according to different color centers by taking gray scales with different visual color difference values as a standard, the standard three-dimensional object model and the sample three-dimensional object model of each color center are randomly presented to the observers, and the single time duration of each observer in a color difference evaluation experiment is 10-20 min (such as 15 min); the color vision normal described in this embodiment is based on the color vision detection of the observer in "new color vision inspection chart" published by li chun hui, li yohimo editions, and liaoning scientific and technical press (2 nd edition 1994), and the detection result meets the requirement, that is, the color vision of the observer is determined to be normal.

Further, after step S30, and before step S40, the method further comprises:

It can be understood that after obtaining a plurality of visual color difference values between the sample three-dimensional object model and the standard sample three-dimensional object model, the user performs precision inspection on all the visual color difference values, and deletes or supplements the visual color difference values with obvious errors to perform a color difference evaluation experiment to obtain new visual color difference values.

In this embodiment, a plurality of visual color difference values are subjected to precision test by using a value of STRESS ', and a calculation formula of the value of STRESS' is shown as formula V:

and is

As shown in equation V, where the STRESS 'value is between 0 and 100, the visual color difference value with a STRESS' value greater than 100 is deleted. The smaller the value of STRESS 'is, the better the correlation between the visual color difference value and the calculated color difference value is, and in the present embodiment, it is preferable that the average value of the STRESS' values of all observers is 40 or less.

Further, in step S40, a first calculated visual color difference value Δ V between the three-dimensional object model of the standard sample and the three-dimensional object model of the test sample is obtained according to the color difference fitting function and the average visual color difference value_i；

Specifically, all valid users average the visual color difference values of a single sample three-dimensional object modelI.e. average visual colour difference

Substituting the color difference value into a fitting function to calculate a first calculated visual color difference value DeltaV of the sample three-dimensional object model_i。

In one embodiment, all available users that are acquired average the visual color difference values of a single specimen three-dimensional object model

And will average the visual color difference value

Substituting x in CIELAB color difference calculation formula III_LabAnd calculating to obtain a first calculated visual color difference value delta V of a sample three-dimensional object model of the user₁。

In another embodiment, all available users that are acquired average the visual color difference values of a single specimen three-dimensional object model

And will average the visual color difference value

Respectively substituting x in formula IV of CIEDE2000 color difference calculation formula_DE2000And calculating to obtain a first calculated visual color difference value delta V of a sample three-dimensional object model of the user₂。

First calculated visual color difference value DeltaV calculated by two embodiments₁And Δ V₂As shown in table 4:

TABLE 4 first calculated apparent color difference values for the sample three-dimensional object model

And step S50, optimizing the primary color difference calculation formula according to the first color value, the second color value, the first calculated color difference value and the first calculated visual color difference value, so that the STRES value between the second calculated color difference value calculated according to the optimized color difference calculation formula and the first calculated visual color difference value is smaller than the STRES value between the first calculated color difference value and the first calculated visual color difference value.

The formula for calculating the STRESS value is shown in formula VI:

and is

In the formula, delta V_iFor a first calculated apparent color difference value, Delta E, between the ith specimen three-dimensional object model and the standard specimen three-dimensional object model_iA color difference value is calculated for a first time between the ith specimen three-dimensional object model and the standard specimen three-dimensional object model.

In a specific embodiment, a first calculated color difference value Δ E between the three-dimensional object model of the standard sample and the three-dimensional object model of the test sample_iDivided into at least two sections, step S50 includes:

when the first calculated color difference value Delta E_iWhen the color difference is less than or equal to the preset threshold value, the optimized first color difference calculation formula is shown as a formula (VII):

△E”＝a△E’^bformula (VII) and

wherein l is a brightness value optimization coefficient,

using the optimized color difference calculation formula to calculate the color difference between the sample three-dimensional object model and the standard sample three-dimensional object model, so that the STRES value between the second calculated color difference value calculated according to the optimized color difference calculation formula and the first calculated visual color difference value is minimum;

Further, step S50 further includes:

when the first calculated color difference value Delta E_i>When the threshold value is preset, the optimized second color difference calculation formula is shown as a formula (VIII):

Δ E ═ k Δ E' + c formula (VIII), and

wherein l is a brightness value optimization coefficient;

using the optimized second color difference calculation formula to calculate the color difference between the sample three-dimensional object model and the standard three-dimensional object model, so that the STRESS value between the second calculated color difference value calculated according to the optimized second color difference calculation formula and the first calculated visual color difference value is minimum;

In this embodiment, the preset threshold is 5.0.

In this embodiment, fig. 6 is a scattering point distribution between a first calculated color difference value and a first calculated visual color difference value calculated by using an original CIELAB color difference calculation formula recommended by CIE in the embodiment of the present application, and a scattering point distribution between a second calculated color difference value and the first calculated visual color difference value calculated by using an optimized CIELAB color difference calculation formula, where the original CIELAB color difference is less than or equal to 5.0; fig. 7 is a dispersion point distribution between a first calculated color difference value and a first calculated visual color difference value calculated by using an original CIELAB color difference calculation formula recommended by CIE in an embodiment of the present application, and a dispersion point distribution between a second calculated color difference value and the first calculated visual color difference value calculated by using an optimized CIELAB color difference calculation formula, where the original CIELAB color difference is greater than 5.0.

FIG. 8 is a distribution of scatter points between a first calculated color difference value and a first calculated visual color difference value calculated using an original CIEDE2000 color difference calculation formula recommended by CIE and a distribution of scatter points between a second calculated color difference value and a first calculated visual color difference value calculated using an optimized CIEDE2000 color difference calculation formula in an embodiment of the present application, wherein the original CIEDE2000 color difference is less than or equal to 5.0; fig. 9 shows a scatter distribution between a first calculated color difference value and a first calculated visual color difference value calculated by using an original CIEDE2000 color difference calculation formula recommended by CIE and a scatter distribution between a second calculated color difference value and the first calculated visual color difference value calculated by using an optimized CIEDE2000 color difference calculation formula in an embodiment of the present application, wherein the original CIEDE2000 color difference is greater than 5.0.

The calculation coefficients of the optimized color difference calculation formula in the embodiment of the present application, and the values of the STRESS between the calculation results of the original color difference calculation formula and the optimized color difference calculation formula and the visual color difference value are shown in table 5:

TABLE 5 original and optimized color difference calculation formula calculation results (STRESS values and optimization coefficients)

As can be seen from table 5 above, the correlations between the color difference calculated using the optimized color difference calculation formula and the visual color difference are all better than the correlations between the color difference calculated using the original color difference calculation formula and the visual color difference.

It is known to those skilled in the art that, under the color difference measurement method of this embodiment 1, changing the shapes of the standard sample three-dimensional object model and the sample three-dimensional object model, and/or changing the measurement condition of the chromaticity values, and/or changing the number of the sample three-dimensional object models may have a certain influence on the values of a, b, l and k, c, l in the optimized color difference calculation formula, and these are all within the protection scope of the present application.

Taking the CIELAB color difference calculation formula as an example:

first calculated color difference value

Then the optimized CIELAB color difference calculation formula is: delta E'^0.26，

And is

When the first calculated color difference value

Then the optimized CIELAB color difference calculation formula is Δ E ″, which is 0.81△E’+1.50，

And is

Detecting and obtaining a colorimetric value of the target three-dimensional object by using an X-Rite exact spectrophotometer under the measuring conditions of D65 and 10 degrees of visual field, calculating and obtaining a first calculated color difference value of the target three-dimensional object by using an original color difference calculation formula, and when the first calculated color difference value is less than or equal to 5.0, namely delta E is 2.32 delta E'^0.26And (5) carrying out color difference calculation. When the first calculated color difference value>5.0, namely, the color difference calculation is carried out by using 0.81 delta E '+ 1.50 as delta E'.

Taking the CIEDE2000 color difference calculation formula as an example:

first calculated color difference value

Then the optimized CIEDE2000 color difference calculation formula is: delta E ″ -1.99 Delta E'^0.33，

And is

When the first calculated color difference value

Then the optimized CIEDE2000 color difference calculation formula is 0.45 Δ E' +3.14,

and is

Detecting and obtaining a colorimetric value of the target three-dimensional object by using an X-Rite exact spectrophotometer under the measuring conditions of D65 and 10 degrees of visual field, calculating and obtaining a first calculated color difference value of the target three-dimensional object by using an original color difference calculation formula, and when the first calculated color difference value is less than or equal to 5.0, namely using < delta > E ″, which is 1.99 < delta > E'^0.33And (5) carrying out color difference calculation. When the first calculated color difference value>5.0, namely using 0.45 Δ E' +3.14 to calculate the color difference.

And step S60, performing color difference calculation on the three-dimensional object to be evaluated according to the optimized color difference calculation formula to obtain the chromatic value of the three-dimensional object to be evaluated.

In one embodiment, step S60 includes:

In another embodiment, step S60 includes:

Specifically, the target chromaticity value is

The colorimetric value of the three-dimensional object to be evaluated is

When the first calculated color difference value of the three-dimensional object to be evaluated is less than or equal to 5.0, the original color difference calculation formula is a CIELAB color difference calculation formula, and the optimized first color difference calculation formula is as follows:

△E”＝2.32△E’^0.26and is and

△E”＝1.99△E’^0.33and is and

when the first calculated color difference value of the three-dimensional object to be evaluated is larger than 5.0, the primary color difference calculation formula is a CIELAB color difference calculation formula, and the optimized second color difference calculation formula is as follows:

Δ E ″ + 0.81 Δ E' +1.50, and

Δ E ″ + 0.45 Δ E' +3.14, and

it should be noted that other detection instruments may also be used to measure the colorimetric value of the target three-dimensional object, which is not limited herein.

Example 2

The present application provides a three-dimensional object color difference calculation apparatus, as shown in fig. 10, the apparatus including:

the acquiring unit 10 is used for acquiring a chromatic value of the three-dimensional object to be evaluated;

a first calculating unit 20, configured to perform color difference calculation according to a primary color difference calculation formula, a target chromaticity value, and a chromaticity value of the three-dimensional object to be evaluated to obtain a first calculated color difference value Δ E of the three-dimensional object to be evaluated_i；

The first calling unit 30 is configured to call the optimized first color difference calculation formula to calculate a second calculated color difference value of the three-dimensional object to be evaluated when the first calculated color difference value is smaller than or equal to a preset threshold value;

and the second calling unit 40 is configured to call the optimized second color difference calculation formula to calculate a second calculated color difference value of the three-dimensional object to be evaluated when the first calculated color difference value is greater than a preset threshold value.

In the scheme, a first calculated color difference value of the three-dimensional object to be evaluated is calculated by using an original color difference calculation formula, when the first calculated color difference value is smaller than or equal to a preset threshold value, the optimized first color difference calculation formula is used for calculating the color difference value of the three-dimensional object to be evaluated, otherwise, the optimized second color difference calculation formula is used for calculating the color difference value of the three-dimensional object to be evaluated, so that the calculated color difference value of the three-dimensional object to be evaluated can be more accurate, and the color difference value can be more visually perceived by a user.

In this embodiment, the optimized CIELAB color difference calculation formula or CIEDE2000 color difference calculation formula is as shown in embodiment 1, and is not described herein again.

Example 3

An embodiment of the present application further provides a computer nonvolatile storage medium, where the storage medium includes a stored program, and when the program runs, the apparatus in which the storage medium is located is controlled to execute the optimized color difference calculation formula in the three-dimensional object color difference calculation method according to embodiment 1. In this embodiment, the optimized CIELAB color difference calculation formula or CIEDE2000 color difference calculation formula is as shown in embodiment 1, and is not described herein again.

Example 4

An embodiment of the present application further provides a computer device, as shown in fig. 11, the computer device 200 includes a memory 202, a processor 201, and a computer program 203 stored in the memory 202 and executable on the processor, and the processor implements the optimized color difference calculation formula in the three-dimensional object color difference calculation method according to any one of claims 1 to 19 when executing the computer program 203. In this embodiment, the optimized CIELAB color difference calculation formula or CIEDE2000 color difference calculation formula is as shown in embodiment 1, and is not described herein again.

Example 5

The embodiment of the application also provides a system for calculating the chromatic aberration of the three-dimensional object,as shown in fig. 12, the three-dimensional object color difference calculation system 300 includes a detection part 303, a memory 302, a processor 301, and a computer program stored in the memory 302 and executable on the processor, wherein the detection part 303 is used for measuring a chromaticity value of an object to be evaluated

Or measuring the colorimetric value of the object to be evaluated

And the colorimetric value of the target object compared with the object to be evaluated

For example, the color difference calculation formula may be an X-Rite exact spectrophotometer, and the optimized color difference calculation formula in the three-dimensional object color difference calculation method according to embodiment 1 is implemented by the processor 301 when executing the computer program. Namely, the computer program includes an optimized color difference calculation formula, so that an optimized calculated color difference value can be calculated.

It should be noted that the computer device may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The computer device may include, but is not limited to, a processor, a memory. Those skilled in the art will appreciate that fig. 11 is merely an example of a computing device and is not intended to be limiting and that a computing device may include more or fewer components than those shown, or some of the components may be combined, or different components, e.g., a computing device may also include input output devices, network access devices, buses, etc.

The Processor may be a Central Processing Unit (CPU), other 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, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The storage may be an internal storage unit of the computer device, such as a hard disk or a memory of the computer device. The memory may also be an external storage device of the computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc. provided on the computer device. Further, the memory may also include both internal and external storage units of the computer device. The memory is used for storing computer programs and other programs and data required by the computer device. The memory may also be used to temporarily store data that has been output or is to be output.

The present invention is not intended to be limited to the particular embodiments shown and described, but is to be accorded the widest scope consistent with the principles and novel features herein disclosed.

Claims

1. A method for calculating chromatic aberration of a three-dimensional object, the method comprising:

constructing a color difference fitting function according to a calculated color difference value sample and a visual color difference value sample between a plurality of different color blocks in the gray scale and a target color block;

performing color difference calculation according to a primary color difference calculation formula, a first chromatic value of a standard sample three-dimensional object model and a second chromatic value of a sample three-dimensional object model to obtain a first calculated color difference value delta E between the standard sample three-dimensional object model and the sample three-dimensional object model_i(ii) a Wherein, the colors of the standard sample three-dimensional object model and the sample three-dimensional object model in the original color difference calculation formula are in the same color system;

acquiring an average visual color difference value between the standard sample three-dimensional object model and the sample three-dimensional object model, which is obtained by a user based on the gray scale;

obtaining a first calculated visual color difference value DeltaV between the standard sample three-dimensional object model and the sample three-dimensional object model according to the color difference fitting function and the average visual color difference value_i；

Optimizing the primary color difference calculation formula according to the first chromatic value, the second chromatic value, the first calculated color difference value and the first calculated visual color difference value, so that a STRES value between the second calculated color difference value calculated according to the optimized color difference calculation formula and the first calculated visual color difference value is smaller than a STRES value between the first calculated color difference value and the first calculated visual color difference value;

and performing color difference calculation on the three-dimensional object to be evaluated according to the optimized color difference calculation formula.

2. The method of claim 1, wherein said optimizing said primary color difference calculation formula based on said first chroma value, said second chroma value, said first calculated color difference value, said first calculated visual color difference value comprises:

△E”＝a△E’^bformula (VII) and

wherein l is a brightness value optimization coefficient,

3. The method of claim 1, wherein said optimizing said primary color difference calculation formula based on said first chroma value, said second chroma value, said first calculated color difference value, said first calculated visual color difference value comprises:

Δ E ═ k Δ E' + c formula (VIII), and

wherein l is a brightness value optimization coefficient;

4. The method according to claim 2, wherein the performing the color difference calculation on the three-dimensional object to be evaluated according to the optimized color difference calculation formula comprises:

acquiring a chromatic value of a three-dimensional object to be evaluated;

calculating according to a primary color difference calculation formula, a target chromatic value and a chromatic value of the three-dimensional object to be evaluated to obtain a first calculated chromatic difference value delta E of the three-dimensional object to be evaluated_i；

And when the first calculated color difference value is less than or equal to the preset threshold value, calling the optimized first color difference calculation formula to calculate a second calculated color difference value of the three-dimensional object to be evaluated.

5. The method of claim 4, wherein the target chroma value is

The colorimetric value of the three-dimensional object to be evaluated is

△E”＝2.32△E’^0.26and is and

△E”＝1.99△E’^0.33and is and

6. the method according to claim 3, wherein the performing the color difference calculation on the three-dimensional object to be evaluated according to the optimized color difference calculation formula comprises:

acquiring a chromatic value of a three-dimensional object to be evaluated;

And when the first calculated color difference value is larger than the preset threshold value, calling the optimized second color difference calculation formula to calculate a second calculated color difference value of the three-dimensional object to be evaluated.

7. The method of claim 6, wherein the target chroma value is

The colorimetric value of the three-dimensional object to be evaluated is

Δ E ″ + 0.81 Δ E' +1.50, and

Δ E ″ + 0.45 Δ E' +3.14, and

8. the method according to any one of claims 2 to 7, wherein the predetermined threshold value is 5.0.

9. The method of claim 1, wherein the STRESS value is calculated according to a formula shown in formula (VI),

and is

10. The method according to claim 9, characterized in that the method satisfies at least one of the following features (1) to (7):

11. The method of claim 10, wherein the number of the standard three-dimensional object models is 5, and the colors of the 5 standard three-dimensional object models are respectively selected from gray, red, yellow, green, and blue, wherein the chroma values of gray are (62.0, 0.0, 0.0), red are (44.0, 37.0, 23.0), yellow are (87.0, -7.0, 47.0), green are (56.0, -32.0, 0.0), and blue are (36.0, 5.0, -31.0).

12. The method of claim 1, wherein prior to said calculating according to the primary color difference calculation formula, the first chrominance value of the standard three-dimensional object model, and the second chrominance value of the sample three-dimensional object model, the method further comprises:

13. The method of claim 12, wherein after said calculating according to a primary color difference calculation formula, a first chrominance value of a standard three-dimensional object model, and a second chrominance value of a sample three-dimensional object model, and before said obtaining an average visual color difference value between the standard three-dimensional object model and the sample three-dimensional object model based on the gray scale by the user, the method further comprises:

14. The method of claim 13, wherein the CIELAB color difference values are distributed between 0.0 and Δ E when the first calculated color difference value is a CIELAB color difference value_maxWithin range, Delta E_maxNot less than 10.0.

15. The method of claim 1, wherein prior to said constructing a color difference fit function from calculated and visual color difference value samples between a plurality of different color patches in a gray scale and a target color patch, the method further comprises:

printing a target color block and a plurality of different color blocks of the same color system;

measuring the colorimetric values of a target color block and each different color block, and calculating a calculated color difference value between the colorimetric value of each different color block and the colorimetric value of the target color block;

and taking the calculated color difference value of each different color block as a calculated color difference value sample, and taking the integral value of the calculated color difference value of each different color block as a visual color difference value sample.

16. The method of claim 15, further comprising:

and screening the effectiveness of a plurality of visual color difference value samples to ensure that the visual color difference value samples are within a preset range.

17. The method according to claim 15, characterized in that the method satisfies at least one of the following features (1) to (3):

18. The method of claim 17, wherein said plurality of different color blocks have visual color difference value samples distributed between 0.0 and Δ V_max，△V_max≥△E_max，△E_maxNot less than 10.0.

19. The method of claim 10, wherein prior to said obtaining an average visual color difference value between said standard three-dimensional object model and said sample three-dimensional object model based on said gray scale by a user, said method further comprises:

20. The method of claim 19, wherein the plurality of visual color difference values are precision checked using a STRESS 'value, wherein the formula for calculating the STRESS' value is shown in formula (V), the range of the STRESS 'value is between 0 and 100, and visual color difference values with the STRESS' value greater than 100 are deleted;

and is

21. The method of claim 20, wherein the average of the STRESS' values of all remaining users for the ith specimen three-dimensional object model is less than or equal to 40.

22. The method of claim 20 wherein the average visual color difference value is an average of all remaining visual color difference values of the ith sample three-dimensional object model from all users.

23. A three-dimensional object color difference calculation apparatus, the apparatus comprising:

24. The apparatus of claim 23, wherein the preset threshold is 5.0.

25. The apparatus of claim 24, wherein the target chroma value is

The colorimetric value of the three-dimensional object to be evaluated is

△E”＝2.32△E’^0.26and is and

△E”＝1.99△E’^0.33and is and

26. the apparatus of claim 24, wherein the target chroma value is

The colorimetric value of the three-dimensional object to be evaluated is

Δ E ″ + 0.81 Δ E' +1.50, and

Δ E ″ + 0.45 Δ E' +3.14, and

27. a computer non-volatile storage medium, wherein the storage medium includes a stored program, and when the program runs, the apparatus on which the storage medium is located is controlled to execute the color difference calculation formula optimized in the method for calculating color difference of three-dimensional object according to any one of claims 1 to 22.

28. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements a color difference calculation formula optimized in the method for calculating color difference of three-dimensional object according to any one of claims 1 to 22 when executing the computer program.

29. A three-dimensional object color difference calculation system comprising a detection component, a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements a color difference calculation formula optimized in the three-dimensional object color difference calculation method according to any one of claims 1 to 22 when executing the computer program.