WO2022183683A1 - 三维物体色度值计算方法及装置、三维物体色度值计算系统 - Google Patents

三维物体色度值计算方法及装置、三维物体色度值计算系统 Download PDF

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WO2022183683A1
WO2022183683A1 PCT/CN2021/111939 CN2021111939W WO2022183683A1 WO 2022183683 A1 WO2022183683 A1 WO 2022183683A1 CN 2021111939 W CN2021111939 W CN 2021111939W WO 2022183683 A1 WO2022183683 A1 WO 2022183683A1
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value
dimensional object
chromaticity
calculation formula
model
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PCT/CN2021/111939
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English (en)
French (fr)
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黄敏
陈伟
向东清
李修
潘洁
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珠海赛纳三维科技有限公司
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Publication of WO2022183683A1 publication Critical patent/WO2022183683A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/46—Measurement of colour; Colour measuring devices, e.g. colorimeters

Definitions

  • the present application relates to the technical field of color evaluation of three-dimensional objects, and in particular, to a method and device for calculating a chromaticity value of a three-dimensional object, and a system for calculating a chromaticity value of a three-dimensional object.
  • the color measurement of plane objects includes two categories: light source color measurement and object color measurement. Object color measurement is divided into contact measurement and non-contact measurement. There are three methods for measuring the color of plane objects: visual method, photoelectric integration method and spectrophotometry.
  • Patent CN107421468A proposes a color 3D scanning system without marking points, which projects the coding pattern on the scanned object, uses two industrial cameras to collect the projected coding pattern for geometric 3D model reconstruction, and obtains color photos of the 3D object through a color camera; The method requires the use of a calibration algorithm to pair the three-dimensional data with the color data, which is a complicated process, and because the color of the sampling point is the color presented by the ambient light provided by the scanning system, the obtained surface color of the object is different from the visual effect under natural light.
  • the color measurement of three-dimensional objects mostly follows the method of color measurement of two-dimensional objects.
  • 3D objects have different shapes than 2D flat objects, under scattered light or directional light source illumination, their appearance color is affected by factors such as the illumination angle of the light source, object shape, translucency and texture, even if they have the same chromaticity.
  • the color of the value can also appear inconsistent in the observer's perception of color. Therefore, the existing method for calculating the chromaticity value of a three-dimensional object has low accuracy.
  • the present application provides a method and device for calculating the chromaticity value of a three-dimensional object, and a system for calculating the chromaticity value of a three-dimensional object, so as to improve the accuracy of calculating the chromaticity value of the three-dimensional object.
  • the present application provides a method for calculating a chromaticity value of a three-dimensional object, the method comprising:
  • the target plane model is the plane model with the highest color similarity to the three-dimensional object model among the multiple plane models of the same color system; according to the spectral reflectance and the spectral energy distribution value, respectively, to obtain the first calculated chromaticity value of the three-dimensional object model and the second calculated chromaticity value of the target plane model; value and a plurality of second calculated chromaticity values of the target plane model to obtain a linear fitting function
  • the linear fitting function is the calculation formula of the chromaticity value after fitting; according to the calculation formula of the chromaticity value after the fitting The chromaticity value calculation is performed on the three-dimensional object to be evaluated.
  • the first calculated chromaticity value and the second calculated chromaticity value include a lightness value, a saturation value, and a hue angle value.
  • the method satisfies at least one of the following features (1) to (7):
  • the three-dimensional object model and the plane model are obtained by using three-dimensional printing technology
  • the minimum dimension of the three-dimensional object model is greater than or equal to 4cm
  • the three-dimensional object model is a three-dimensional model of regular shape and monochrome
  • the number of the three-dimensional object models of the same color system is m, where m is an integer greater than or equal to 4.
  • the colors of the multiple three-dimensional object models are printed with reference to the color of the color center recommended by the International Commission on Illumination, including at least 5 different color systems, and the chromaticity values of the multiple three-dimensional object models of the same color system are different. ;
  • n is an integer greater than or equal to 10;
  • the colors of the multiple three-dimensional object models are selected from gray, red, yellow, green, and blue for printing, wherein the gray referenced
  • the chromaticity value is (62.0, 0.0, 0.0)
  • the red reference The chromaticity values are (44.0, 37.0, 23.0)
  • the yellow reference Chroma values are (87.0, -7.0, 47.0)
  • green referenced The chromaticity value is (56.0, -32.0, 0.0)
  • the blue reference The chromaticity values are (36.0, 5.0, -31.0).
  • the thickness of the plane model is less than or equal to 1 mm, and the orthographic projection area of the three-dimensional object model on the plane model is equal to the area of the plane model.
  • the method further includes:
  • Screening a plurality of plane models to obtain an effective plane model Screening a plurality of plane models to obtain an effective plane model; screening a target plane model from a plurality of effective plane models of the same color system based on the color of each of the three-dimensional object models, wherein the target plane The color similarity between the model and the three-dimensional object model of the same color system is the highest.
  • the screening of multiple plane models to obtain an effective plane model specifically includes:
  • the measuring to obtain the first measured chromaticity value of each of the three-dimensional object models includes: measuring at least 5 different positions of each of the three-dimensional object models. The chromaticity value is calculated, and the arithmetic mean value of the chromaticity value is calculated to obtain the first measured chromaticity value of the three-dimensional object model.
  • the at least five different positions are located on the same plane or the same arc surface of the three-dimensional object model.
  • the measuring to obtain the second measured chromaticity value of each of the planar models includes: measuring the chromaticity at at least 5 different positions of each of the planar models value, and calculate the arithmetic mean of the chromaticity values to obtain the second measured chromaticity value of the plane model.
  • the three-dimensional object model is a cube, the cube includes an upper surface, and the fitted upper surface chromaticity value calculation formula includes a lightness value calculation formula, saturation Value calculation formula and hue angle value calculation formula; wherein, x is the initial chromaticity value of the three-dimensional object to be evaluated, and y is the chromaticity value of the three-dimensional object to be evaluated after fitting;
  • the three-dimensional object model is a cube, the cube includes a front surface, and the fitted front surface chromaticity value calculation formula includes a lightness value calculation formula, saturation Value calculation formula and hue angle value calculation formula; wherein, x is the initial chromaticity value of the three-dimensional object to be evaluated, and y is the chromaticity value of the three-dimensional object to be evaluated after fitting;
  • the chromaticity value calculation of the three-dimensional object to be evaluated is performed according to the fitted chromaticity value calculation formula, including:
  • an embodiment of the present application provides an apparatus for calculating a chromaticity value of a three-dimensional object, and the apparatus includes:
  • a first acquisition unit used to acquire multiple three-dimensional object models
  • a second acquiring unit configured to acquire a plurality of plane models of the same color system based on the color of the three-dimensional object model
  • the third acquisition unit is used to acquire the spectral reflectance of the three-dimensional object model and the target plane model placed in the standard observation box and the relative spectral energy distribution value of the illumination light source in the standard observation box;
  • a first calculation unit configured to obtain a first calculated chromaticity value of the three-dimensional object model and a second calculated chromaticity value of the target plane model according to the spectral reflectance and the spectral energy distribution value respectively; wherein , the target plane model is a plane model with the highest color proximity to the three-dimensional object model among the plurality of plane models of the same color system;
  • a construction unit is configured to construct a linear fitting function based on the first calculated chromaticity values of the multiple three-dimensional object models and the second calculated chromaticity values of the multiple target plane models, and the linear fitting function is a The calculation formula of the combined chromaticity value;
  • the second calculation unit is configured to calculate the chromaticity value of the three-dimensional object to be evaluated according to the fitted chromaticity value calculation formula.
  • the first calculated chromaticity value and the second calculated chromaticity value include a lightness value, a saturation value, and a hue angle value.
  • the three-dimensional object model is a cube, the cube includes an upper surface, and the fitted upper surface chromaticity value calculation formula includes a lightness value calculation formula, saturation Value calculation formula and hue angle value calculation formula; wherein, x is the initial chromaticity value of the three-dimensional object to be evaluated, and y is the chromaticity value of the three-dimensional object to be evaluated after fitting;
  • the three-dimensional object model is a cube
  • the cube includes a front surface
  • the fitted front surface chromaticity value calculation formula includes a lightness value calculation formula, saturation Value calculation formula and hue angle value calculation formula; wherein, x is the initial chromaticity value of the three-dimensional object to be evaluated, and y is the chromaticity value of the three-dimensional object to be evaluated after fitting;
  • the second computing unit includes:
  • the acquisition subunit is used to acquire the three-dimensional object to be evaluated, and to obtain the measured chromaticity value of the upper surface and/or the front surface of the three-dimensional object to be evaluated, and the measured chromaticity value of the upper surface and/or the front surface includes the lightness value , saturation value and hue angle value;
  • the first processing subunit for substituting the lightness value of the upper surface and/or the front surface into the lightness value calculation formula of the fitted upper surface and/or the front surface, to obtain the fitted lightness value;
  • the second processing subunit is used for substituting the saturation value of the upper surface and/or the front surface into the calculation formula of the saturation value of the upper surface and/or the front surface after fitting to obtain the saturation value after fitting;
  • the third processing subunit is used for substituting the hue angle value of the upper surface and/or the front surface into the hue angle value calculation formula of the upper surface and/or the front surface after fitting, to obtain the hue angle value after fitting;
  • An output subunit configured to obtain the fitted chromaticity value of the three-dimensional object to be evaluated according to the fitted lightness value, saturation value and hue angle value.
  • the present application provides a computer non-volatile storage medium, the storage medium includes a stored program, and when the program runs, the device where the storage medium is located is controlled to perform the three-dimensional object coloring described in the first aspect above.
  • the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program Then, the fitted chromaticity value calculation formula in the three-dimensional object chromaticity value calculation method described in the first aspect is realized.
  • the present application provides a chromaticity value calculation system for a three-dimensional object, including a detection component, a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing The computer program implements the fitted chromaticity value calculation formula in the three-dimensional object chromaticity value calculation method described in the first aspect.
  • the calculated chromaticity values of the three-dimensional object model and the target plane model are obtained.
  • the calculated chromaticity value and the calculated chromaticity values of multiple target plane models are used to construct a fitting function, so as to obtain the fitted chromaticity value calculation formula, so that the obtained three-dimensional chromaticity value can be improved by the fitted chromaticity value calculation formula.
  • the accuracy of the chromaticity value of the object is a simple formula, so as to obtain the fitted chromaticity value calculation formula, so that the obtained three-dimensional chromaticity value can be improved by the fitted chromaticity value calculation formula.
  • FIG. 1 is a schematic flowchart of a method for calculating a chromaticity value of a three-dimensional object in a specific embodiment of the application;
  • Fig. 2-1 is the scatter point distribution and mathematical fitting relationship diagram of the color L * 10 of the upper surface of the three-dimensional object model and the target plane model in the specific embodiment of the application;
  • 2-3 is the scatter distribution and mathematical fitting relationship diagram of the color h * 10,ab of the upper surface of the three-dimensional object model and the target plane model in the specific embodiment of the application;
  • Fig. 3-1 is the scatter point distribution and mathematical fitting relationship diagram of the color L * 10 of the front surface of the three-dimensional object model and the target plane model in the embodiment of the application;
  • 3-3 is the scatter distribution and mathematical fitting relationship diagram of the color h * 10,ab of the front surface of the three-dimensional object model and the target plane model in the embodiment of the application;
  • FIG. 4 is a schematic structural block diagram of an apparatus for calculating a chromaticity value of a three-dimensional object in another specific embodiment of the present application;
  • FIG. 5 is a schematic structural block diagram of a computer device in another specific embodiment of the present application.
  • FIG. 6 is a schematic structural block diagram of a system for calculating a chromaticity value of a three-dimensional object according to another specific embodiment of the present application.
  • FIG. 1 is a schematic flowchart of a method for calculating a chromaticity value of a three-dimensional object in a specific embodiment of the present application.
  • the method for calculating a chromaticity value of a three-dimensional object in the present application includes the following steps S10 to S60:
  • Step S10 acquiring multiple three-dimensional object models
  • Step S20 obtaining multiple plane models of the same color system based on the color of the three-dimensional object model
  • Step S30 obtaining the spectral reflectance of the three-dimensional object model and the target plane model placed in the standard observation box and the relative spectral energy distribution value of the illumination light source in the standard observation box; wherein, the target plane model is the same color system A plane model with the highest color proximity to the three-dimensional object model among the plurality of plane models;
  • Step S40 respectively calculating the first calculated chromaticity value of the three-dimensional object model and the second calculated chromaticity value of the target plane model according to the spectral reflectance and the spectral energy distribution value;
  • Step S50 constructing a linear fitting function based on the first calculated chromaticity values of the plurality of three-dimensional object models and the second calculated chromaticity values of the plurality of target plane models, and the linear fitting function is after fitting.
  • Step S60 Calculate the chromaticity value of the three-dimensional object to be evaluated according to the fitted chromaticity value calculation formula.
  • the calculated chromaticity values of the three-dimensional object model and the target plane model are obtained.
  • the calculated chromaticity value and the calculated chromaticity values of multiple target plane models are used to construct a fitting function, so as to obtain the fitted chromaticity value calculation formula, so that the obtained three-dimensional chromaticity value can be improved by the fitted chromaticity value calculation formula.
  • the accuracy of the chromaticity value of the object is a simple formula, so as to obtain the fitted chromaticity value calculation formula, so that the obtained three-dimensional chromaticity value can be improved by the fitted chromaticity value calculation formula.
  • Step S10 acquiring multiple three-dimensional object models.
  • the three-dimensional object model is printed and formed by using the three-dimensional printing technology.
  • the minimum dimension of the three-dimensional object model is greater than or equal to 4 cm
  • the three-dimensional object model is a three-dimensional model of regular shape and monochrome, such as a sphere, a cube, a cone, and the like.
  • the three-dimensional object model may be a cube with a length of 4 cm by a width of 4 cm by a height of 4 cm.
  • the colors of the multiple three-dimensional object models are different, and specifically, at least five three-dimensional object models of different color systems can be printed.
  • the three-dimensional object models of the same color system have different colors and the number of three-dimensional object models of the same color system is m, where m is an integer greater than or equal to 4. Exemplarily, 4 red 3D object models, 4 blue 3D object models, 4 yellow 3D object models, 4 green 3D object models, and 4 gray 3D object models can be printed.
  • the color of the three-dimensional object model is printed with reference to the color of the color center recommended by the International Commission on Illumination.
  • the color of the reference center of each color is printed to obtain 4 cube 3D object models, and the colors of the 4 cube 3D object models are different.
  • the size of the cube is 4cm long ⁇ 4cm wide ⁇ 4cm high. Refer to The colors in the center of the 5 colors are gray, red, yellow, green and blue.
  • the first calculated chromaticity value and the second calculated chromaticity value both include a lightness value, a saturation value and a hue angle value.
  • the gray 3D object model is referenced when printing The chromaticity value is (62.0, 0.0, 0.0)
  • the red 3D object model is referenced when printing
  • the chromaticity value is (44.0, 37.0, 23.0)
  • the yellow 3D object model is referenced when printing
  • the chromaticity value is (87.0, -7.0, 47.0)
  • the green 3D object model is referenced when printing
  • the chromaticity value is (56.0, -32.0, 0.0)
  • the blue 3D object model is referenced when printing
  • the chromaticity values are (36.0, 5.0, -31.0).
  • the surface of the selected three-dimensional object model should have a uniform color.
  • the method also includes:
  • the step of calculating the from-average color difference includes: calculating the color difference between the chromaticity value at any position of the single three-dimensional object model and the average value of the chromaticity values at different positions of the three-dimensional object model.
  • the from-average color difference of the three-dimensional object model is less than or equal to the first preset value.
  • the CIELAB color difference calculation formula is used to calculate the from-average color difference, and the first preset value is 1.0.
  • the off-average color difference of the three-dimensional object model is less than or equal to 1.0, the surface color of the three-dimensional object model meets the uniformity requirement and can be used as an effective three-dimensional object model.
  • Step S20 acquiring multiple plane models of the same color system based on the color of the three-dimensional object model.
  • the plane model is printed and formed by using a three-dimensional printing technology
  • the plane model is a plane figure with regular shape and uniform color, such as a circle, a rectangle, a triangle, and the like.
  • the color center referenced in the printing of the 3D object model respectively, in gray Chroma value (50.0, 0.0, 0.0), red Chroma value (44.0, 37.0, 23.0), yellow Chroma value (87.0, -7.0, 47.0), green Chroma value (56.0, -32.0, 0.0), blue
  • the chromaticity value (36.0, 5.0, -31.0) is a reference to print a plurality of plane models, wherein the thickness of the plane model is less than or equal to 1mm, and the orthographic projection area of the three-dimensional object model on the plane model is equal to the plane area of the model.
  • the three-dimensional object model is 4cm long x 4cm wide x 4cm high, and the plane model is a cuboid with a length of 4cm x 4cm wide x 1mm high; or, the three-dimensional object model is 4cm long x 5cm wide x 4cm high, and the three-dimensional object model is 4cm long
  • the plane model corresponding to ⁇ width 5cm is 4cm long ⁇ 5cm wide.
  • the number of plane models of the same color system corresponding to each of the three-dimensional object models is n, where n is an integer greater than or equal to 10.
  • the number of plane models of the same color system corresponding to each of the three-dimensional object models is 16, that is, one gray three-dimensional object model is configured with 16 gray plane models.
  • step S10 and step S20 may be performed synchronously or asynchronously, which is not limited herein.
  • the equipment for printing the three-dimensional object model is the same as the equipment for printing the plane model, and the area of the orthographic projection of the three-dimensional object model on the plane model is equal to the area of the plane model.
  • the method further includes:
  • a target plane model is screened from a plurality of valid plane models of the same color system, wherein the color of the target plane model and the three-dimensional object model of the same color system are close to each other highest degree.
  • the step of screening a plurality of plane models to obtain an effective plane model includes:
  • the measurement conditions and measurement methods of the first measurement chromaticity value of the three-dimensional object model are the same as the measurement conditions and measurement methods of the second measurement chromaticity value of the plane model.
  • the at least 5 different positions are located on the same plane or the same arc surface of the three-dimensional object model.
  • the first measured chromaticity value of the three-dimensional object model obtained after printing and screening for validity is shown in Table 1:
  • L * 10 represents the lightness value of the three-dimensional object model
  • a * 10 and b * 10 represent the chromaticity parameters of the color of the three-dimensional object model.
  • the measurement obtains the second measured chromaticity value of each of the plane models, including:
  • an effective plane model with a color close to the three-dimensional object model can be obtained.
  • the second measured chromaticity value of the plane model before determining the second measured chromaticity value of the plane model, it is determined whether the color of the surface of the plane model is uniform by calculating the color difference from the average at different positions of a single plane model.
  • the calculation method of the from-average color difference is the same as the calculation method of the from-average color difference of the three-dimensional object model; it is determined that the from-average color difference of the plane model is less than or equal to the first preset value.
  • the CIELAB color difference calculation formula is used to calculate the from-average color difference, and the first preset value is 1.0.
  • the arithmetic mean value of the calculated chromaticity values of the plane model is determined as the second measured chromaticity value of the plane model.
  • an odd number of observers can also be organized to observe, and the number of observers is as large as possible.
  • the number of observers is at least 5, and it is required that more than 50% of all observers believe that the plane model corresponds to the corresponding If the colors of the three-dimensional object model are visually close, it is preliminarily determined that the plane model and the three-dimensional object model are plane models of the same color system and similar colors. Exemplarily, if at least 4 of the 7 observers believe that the color of the plane model is consistent with the color of the three-dimensional object model, it is considered that the color of the plane model is visually close to the color of the three-dimensional object model, which is valid. flat model.
  • the observer can observe through a standard observation box, and the specific observation conditions of the standard observation box are as described below, which will not be repeated here.
  • an odd number of observers can also observe the color of the three-dimensional object model and the color of the plane model and simultaneously refer to the first measured chromaticity value and the second measured chromaticity value to obtain an effective flat model.
  • a target plane model is obtained by screening from a plurality of valid plane models of the same color system.
  • At least 10 male and female observers with normal color vision can be obtained by screening the multiple plane models to obtain the target plane model.
  • the age distribution of the observers is 20-32 years old.
  • the target plane model with the highest selection probability is selected as the target plane model.
  • the observation distance of the observer from the standard observation box is 50cm-60cm.
  • the observation environment of the experiment is a dark room.
  • the experiment is carried out in the LEDView standard observation box.
  • the color temperature of the experimental light source is 6496K, the illumination is 800lux, and the color rendering index is 93.5.
  • Each group of plane models and three-dimensional object models to be evaluated are randomly presented to the observers, and each observer has a single duration of about 20 minutes in the observation experiment;
  • the normal color vision described in this example is based on Li Chunhui, edited by Li Yuhong, The "Newly Edited Color Vision Examination Chart” (2nd edition in 1994) published by Liaoning Science and Technology Press conducts the observer's color vision test, and the test results meet the requirements, that is, it is judged that the observer's color vision is normal.
  • Observers are also required to have a professional background in color science.
  • Step S30 obtaining the spectral reflectance of the three-dimensional object model and the target plane model placed in the standard observation box and the relative spectral energy distribution value of the illumination light source in the standard observation box; wherein, the target plane model is the same color system A plane model with the highest color similarity to the three-dimensional object model among the plurality of plane models.
  • the three-dimensional object model and the target plane model can be placed in the same standard observation box, and the first spectral reflectance ⁇ 1 ( ⁇ ) of the three-dimensional object model and the target plane can be obtained by measuring The second spectral reflectance ⁇ 2 ( ⁇ ) of the model, wherein the relative spectral energy distribution value of the illumination light source of the standard observation box is S( ⁇ );
  • Step S40 calculating a first calculated chromaticity value of the three-dimensional object model and a second calculated chromaticity value of the target plane model according to the spectral reflectance and the spectral energy distribution value, respectively.
  • the spectral radiance PR655 is used to measure the relative spectral energy distribution S( ⁇ ) of the illumination light source in the standard observation box, the first spectral reflectance ⁇ 1 ( ⁇ ) of the three-dimensional object model and the second spectrum of the target plane model
  • the reflectance ⁇ 2 ( ⁇ ) is substituted into the formula for calculating the chromaticity value, and the tristimulus values XYZ of the three-dimensional object model and the plane model can be obtained by formula (1), and then the lightness value (L * ), chromaticity value can be calculated by formula (2) Parameters (a * , b * ):
  • X n , Y n , and Zn in formula (2) are the tri-stimulus values of the illumination light source in the standard observation box, respectively, and X, Y, and Z are the tri-stimulus values of the three - dimensional object model or the plane model, respectively;
  • the color saturation value C * ab and the hue angle value h * ab are further calculated according to the formula (3) and the formula (4).
  • the first calculated chromaticity values of the upper surface and the front surface of the three-dimensional object model under the illumination of the light source in the standard observation box are shown in Table 3.
  • the second calculated chromaticity value of the target plane model under the illumination of the light source in the standard observation box is shown in Table 4:
  • Table 3 The first calculated chromaticity values of the upper surface and front surface of the three-dimensional object model under the illumination of the light source in the standard observation box
  • Step S50 constructing a linear fitting function based on the first calculated chromaticity values of the plurality of three-dimensional object models and the second calculated chromaticity values of the plurality of target plane models, and the linear fitting function is after fitting.
  • the chromaticity value calculation formula is
  • a scatter diagram is drawn, and the The linear fitting method is used to obtain the fitted chromaticity value calculation formula by fitting.
  • the fitted upper surface chromaticity value calculation formula includes a lightness value calculation formula, a saturation value calculation formula and a hue angle value calculation formula.
  • step S50 includes:
  • the fitted upper surface and/or front surface brightness value calculation formula is obtained;
  • the fitted upper surface and/or front surface saturation value calculation formula is obtained
  • Fig. 2-1 is the scatter point distribution and mathematical fitting relationship between the upper surface of the three-dimensional object model and the color L * 10 of the target plane model in the specific embodiment of the application. As shown in Fig. 2-1, the upper surface of the three-dimensional object model The calculation formula of the lightness value after surface fitting is:
  • y Lup 1.0797x Lup- 5.6981 (A-1), where x Lup represents the initial brightness value of the upper surface of the three-dimensional object model, and y Lup represents the brightness value of the fitted upper surface of the three-dimensional object model.
  • Fig. 2-2 is the scatter point distribution and mathematical fitting relationship between the upper surface of the three-dimensional object model and the color C * 10,ab of the target plane model in the specific embodiment of the application, as shown in Fig. 2-2, the three-dimensional object model
  • the calculation formula of the saturation value after fitting on the upper surface of is:
  • yCup 1.0077xCup+0.666 (B-1), where xCup represents the initial saturation value of the upper surface of the 3D object model, and yCup represents the saturation value of the upper surface of the fitted 3D object model .
  • Fig. 2-3 is the scatter point distribution and mathematical fitting relation diagram of the upper surface of the three-dimensional object model and the color h * 10,ab of the target plane model in the specific embodiment of the application, as shown in Fig. 2-3, the three-dimensional object model
  • the calculation formula of the hue angle value after fitting on the upper surface is:
  • y h on 0.9853x h on +1.587 (C-1), where x h represents the initial hue angle value of the upper surface of the 3D object model, and y h represents the hue angle of the upper surface of the fitted 3D object model value.
  • Fig. 3-1 is the scatter point distribution and mathematical fitting relationship between the front surface of the three-dimensional object model and the color L * 10 of the target plane model in the embodiment of the application. As shown in Fig. 3-1, the front surface of the three-dimensional object model is shown in Fig. 3-1.
  • the calculation formula of the fitted lightness value is:
  • y L front 1.0304x L front -10.3 (A-2), where x L front represents the initial brightness value of the front surface of the three-dimensional object model, and y L front represents the brightness value of the fitted front surface of the three-dimensional object model.
  • Fig. 3-2 is the scatter point distribution and mathematical fitting relationship between the front surface of the three-dimensional object model and the color C * 10,ab of the target plane model in the embodiment of the application, as shown in Fig. 3-2, the three-dimensional object model
  • the calculation formula of the saturation value after front surface fitting is:
  • y C front 1.0082x C front -1.7921 (B-2), where x C front represents the initial saturation value of the front surface of the 3D object model, y C front represents the saturation value of the front surface of the 3D object model after fitting .
  • Fig. 3-3 is the scatter point distribution and mathematical fitting relationship between the front surface of the three-dimensional object model and the color h * 10,ab of the target plane model in the embodiment of the application, as shown in Fig. 3-3, the three-dimensional object model
  • the calculation formula of the hue angle value after front surface fitting is:
  • y h front 0.9582x h front +3.8288 (C-2), where x h front represents the initial hue angle value of the upper surface of the 3D object model, y h represents the hue angle of the front surface of the fitted 3D object model value.
  • Step S60 calculating the chromaticity value of the three-dimensional object to be evaluated according to the fitted chromaticity value calculation formula, which specifically includes:
  • the fitted chromaticity value of the three-dimensional object to be evaluated is obtained according to the fitted lightness value, saturation value and hue angle value.
  • the measured chromaticity value of the three-dimensional object to be evaluated can be measured according to the above-mentioned measurement conditions for measuring the chromaticity value of the three-dimensional object model, and the measured chromaticity value of the three-dimensional object to be evaluated includes lightness value, saturation value and hue
  • the angle value is substituted into the corresponding calculation formula, so as to obtain the chromaticity value after fitting of the three-dimensional object to be evaluated.
  • the measured chromaticity value of the three-dimensional object to be evaluated in this application includes lightness value, saturation value and hue angle value, which can be measured directly or indirectly.
  • the saturation value and the hue angle value are derived from the calculation formula.
  • the present application provides a three-dimensional object chromaticity value calculation device, characterized in that, as shown in FIG. 4 , the device includes:
  • a first acquisition unit used for acquiring multiple three-dimensional object models
  • a second acquiring unit configured to acquire a plurality of plane models of the same color system based on the color of the three-dimensional object model
  • the third acquisition unit is used to acquire the spectral reflectance of the three-dimensional object model and the target plane model placed in the standard observation box and the relative spectral energy distribution value of the illumination light source in the standard observation box;
  • a first calculation unit configured to obtain a first calculated chromaticity value of the three-dimensional object model and a second calculated chromaticity value of the target plane model according to the spectral reflectance and the spectral energy distribution value respectively; wherein , the target plane model is a plane model with the highest color proximity to the three-dimensional object model among the plurality of plane models of the same color system;
  • a construction unit is configured to construct a linear fitting function based on the first calculated chromaticity values of the multiple three-dimensional object models and the second calculated chromaticity values of the multiple target plane models, and the linear fitting function is a The calculation formula of the combined chromaticity value;
  • the second calculation unit is configured to calculate the chromaticity value of the three-dimensional object to be evaluated according to the fitted chromaticity value calculation formula.
  • the first calculated chromaticity value and the second calculated chromaticity value include a lightness value, a saturation value and a hue angle value.
  • the three-dimensional object model is a cube, the cube includes an upper surface, and the fitted upper surface chromaticity value calculation formula includes a lightness value calculation formula, a saturation value calculation formula and a hue angle value calculation formula; wherein , x is the initial chromaticity value of the three-dimensional object to be evaluated, and y is the fitted chromaticity value of the three-dimensional object to be evaluated;
  • the three-dimensional object model is a cube, the cube includes a front surface, and the fitted front surface chromaticity value calculation formula includes a lightness value calculation formula, a saturation value calculation formula and a hue angle value calculation formula; wherein , x is the initial chromaticity value of the three-dimensional object to be evaluated, and y is the fitted chromaticity value of the three-dimensional object to be evaluated;
  • the second computing unit includes:
  • the acquisition subunit is used to acquire the three-dimensional object to be evaluated, and to obtain the measured chromaticity value of the upper surface and/or the front surface of the three-dimensional object to be evaluated, and the measured chromaticity value of the upper surface and/or the front surface includes the lightness value , saturation value and hue angle value;
  • the first processing subunit for substituting the lightness value of the upper surface and/or the front surface into the lightness value calculation formula of the fitted upper surface and/or the front surface, to obtain the fitted lightness value;
  • the second processing subunit is used for substituting the saturation value of the upper surface and/or the front surface into the calculation formula of the saturation value of the upper surface and/or the front surface after fitting to obtain the saturation value after fitting;
  • the third processing subunit is used for substituting the hue angle value of the upper surface and/or the front surface into the hue angle value calculation formula of the upper surface and/or the front surface after fitting, to obtain the hue angle value after fitting;
  • An output subunit configured to obtain the fitted chromaticity value of the three-dimensional object to be evaluated according to the fitted lightness value, saturation value and hue angle value.
  • the device for calculating the chromaticity value of the three-dimensional object in this application may be an integrated device, or may be multiple separate devices, and the multiple separate devices perform different functions.
  • An embodiment of the present application further provides a computer non-volatile storage medium, the storage medium includes a stored program, and when the program runs, the device where the storage medium is located is controlled to execute the chromaticity value of the three-dimensional object described in Embodiment 1
  • the calculation formula of the fitted chromaticity value in the calculation method is as shown in Embodiment 1, and details are not repeated here.
  • the computer device 200 includes a memory 202, a processor 201, and a computer program 203 stored in the memory 202 and running on the processor.
  • the processor executes the computer program 203, the fitted chromaticity value calculation formula in the three-dimensional object chromaticity value calculation method in Embodiment 1 is implemented.
  • the calculation formula of the fitted chromaticity value is as shown in Embodiment 1, and details are not repeated here.
  • the three-dimensional object chromaticity value calculation system 300 includes a detection component 303, a memory 302, a processor 301, and A computer program that can be run on the processor, and the detection component 303 is used to measure the chromaticity values (such as L* 2 , C * 2 , h * 2 ) of the three-dimensional object to be evaluated, such as X-Rite eXact In the spectrophotometer, when the processor 301 executes the computer program, the fitted chromaticity value calculation formula in the three-dimensional object chromaticity value calculation method described in Embodiment 1 is implemented. That is, the computer program includes the calculation formula of the fitted chromaticity value, so that the fitted chromaticity value can be obtained by calculation.
  • the computer program includes the calculation formula of the fitted chromaticity value, so that the fitted chromaticity value can be obtained by calculation.
  • the computer device may be a desktop computer, a notebook, a palmtop computer, a cloud server and other computing devices.
  • Computer equipment may include, but is not limited to, processors, memory.
  • FIG. 11 is only an example of a computer device, and does not constitute a limitation to the computer device, and may include more or less components than those shown in the figure, or combine some components, or different components, such as Computer devices may also include input and output devices, network access devices, buses, and the like.
  • the so-called processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (Digital Signal Processors, DSPs), application specific integrated circuits (ASICs), field Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
  • a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
  • the memory may be an internal storage unit of a computer device, such as a hard disk or a memory of the computer device.
  • the memory can also be an external storage device of the computer equipment, such as a plug-in hard disk equipped on the computer equipment, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card (Flash Card), etc.
  • the memory may also include both an internal storage unit of the computer device and an external storage device. Memory is used to store computer programs and other programs and data required by computer equipment. The memory may also be used to temporarily store data that has been or will be output.

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Abstract

一种三维物体色度值计算方法及装置、三维物体色度值计算系统，三维物体色度值计算方法包括：获取多个三维物体模型以及同一色系的多个平面模型；获取置于标准观察箱中的三维物体模型与目标平面模型的光谱反射率以及标准观察箱中的照明光源的相对光谱能量分布值；根据计算得到的三维物体模型的第一计算色度值、目标平面模型的第二计算色度值构建得到线性拟合函数，线性拟合函数为拟合后的色度值计算公式；根据拟合后的色度值计算公式对待评价三维物体进行色度值计算，能够提高三维物体的色度值的准确度。

Description

三维物体色度值计算方法及装置、三维物体色度值计算系统
本申请要求于2021年03月04日提交中国专利局、申请号为202110242021.4，申请名称为“三维物体色度值计算方法及装置、三维物体色度值计算系统”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及三维物体颜色评价技术领域，尤其涉及三维物体色度值计算方法及装置、三维物体色度值计算系统。
背景技术
平面物体颜色测量包括光源颜色测量与物体颜色测量两大类，其中物体颜色测量分为接触式测量和非接触式测量。现有平面物体颜色测量方法有目视法、光电积分法和分光光度法三种。专利CN107421468A提出了无需标记点的彩色三维扫描系统，将编码图案投影到扫描物体上，用两个工业相机采集投影编码图案进行几何三维模型重建，通过一个彩色相机获取三维物体的彩色照片；这种方法需要用到标定算法，将三维数据与颜色数据配对起来，过程复杂，且由于采样点的色彩是由扫描系统提供的环境光照射下呈现的颜色，获得的物体表面色彩与自然光下视觉效果不会完全一样。目前在工业界，对三维物体的颜色测量，较多沿用对二维平面物体颜色测量的方法。然而，三维物体由于具有不同于二维平面物体的形状，在散射光或定向光源照明下，其外观颜色受光源照明角度、物体形状、半透明度和纹理等因素的影响，即便是具有同一色度值的颜色也会出现观察者颜色感觉不一致的现象。因此，现有的三维物体的色度值计算方法准确度低。
申请内容
本申请提供三维物体色度值计算方法及装置、三维物体色度值计算系统，以提高三维物体的色度值计算准确度。
第一方面，本申请提供一种三维物体色度值计算方法，所述方法包括：
获取多个三维物体模型；基于所述三维物体模型的颜色获取同一色系的多个平面模型；获取置于标准观察箱中的三维物体模型与目标平面模型的光谱反射率以及标准观察箱中的照明光源的相对光谱能量分布值；其中，所述目标平面模型为所述同一色系的多个平面模型中与所述三维物体模型的颜色接近度最高的一个平面模型；根据所述光谱反射率及所述光谱能量分布值分别计算得到所述三维物体模型的第一计算色度值、所述目标平面模型的第二计算色度值；基于多个所述三维物体模型的第一计算色度值与多个所述目标平面模型的第二计算色度值构建得到线性拟合函数，所述线性拟合函数为拟合后的色度值计算公式；根据拟合后的色度值计算公式对待评价三维物体进行色度值计算。
结合第一方面，在一种可行的实施方式中，所述第一计算色度值和第二计算色度值包括明度值、饱和度值及色调角值。
结合第一方面，在一种可行的实施方式中，所述方法满足下列特征(1)至(7)中的至 少一种：
(1)所述三维物体模型、所述平面模型均采用三维打印技术得到；
(2)所述三维物体模型的最小维度大于或等于4cm；
(3)所述三维物体模型为规则形状且单色的立体模型；
(4)同一色系的所述三维物体模型的数量为m，m为大于或等于4的整数；
(5)所述多个三维物体模型的颜色参考国际照明委员会推荐的颜色中心的颜色进行打印，至少包括5种不同色系，且同一色系的多个所述三维物体模型的色度值不同；
(6)与每个所述三维物体模型对应的同一色系的平面模型的数量为n，n为大于或等于10的整数；
(7)同一色系的三维物体模型、平面模型的维度一致。
结合第一方面，在一种可行的实施方式中，所述多个三维物体模型的颜色分别选自灰色、红色、黄色、绿色和蓝色进行打印，其中，灰色参考的
Figure PCTCN2021111939-appb-000001
色度值为(62.0，0.0，0.0)，红色参考的
Figure PCTCN2021111939-appb-000002
色度值为(44.0，37.0，23.0)，黄色参考的
Figure PCTCN2021111939-appb-000003
色度值为(87.0，-7.0，47.0)，绿色参考的
Figure PCTCN2021111939-appb-000004
色度值为(56.0，-32.0，0.0)，蓝色参考的
Figure PCTCN2021111939-appb-000005
色度值为(36.0，5.0，-31.0)。
结合第一方面，在一种可行的实施方式中，所述平面模型的厚度小于或等于1mm，且所述三维物体模型在所述平面模型上的正投影面积等于所述平面模型的面积。
结合第一方面，在一种可行的实施方式中，在所述获取置于标准观察箱中的三维物体模型与目标平面模型的光谱反射率以及标准观察箱中的照明光源的相对光谱能量分布值之前，所述方法还包括：
对多个平面模型进行筛选，得到有效的平面模型；基于每个所述三维物体模型的颜色从所述同一色系的多个有效的平面模型中筛选得到目标平面模型，其中，所述目标平面模型与同一色系的所述三维物体模型的颜色接近度最高。
结合第一方面，在一种可行的实施方式中，所述对多个平面模型进行筛选，得到有效的平面模型具体包括：
测量得到每个所述三维物体模型的第一测量色度值；测量得到每个所述平面模型的第二测量色度值；基于所述第一测量色度值和第二测量色度值获取与所述三维物体模型的颜色属于同一色系的多个有效的平面模型。
结合第一方面，在一种可行的实施方式中，所述测量得到每个所述三维物体模型的第一测量色度值，包括：测量每个所述三维物体模型至少5个不同位置处的色度值，并计算所述色度值的算术平均值，得到所述三维物体模型的第一测量色度值。
结合第一方面，在一种可行的实施方式中，所述至少5个不同位置位于所述三维物体模型同一平面或同一弧面上。
结合第一方面，在一种可行的实施方式中，所述测量得到每个所述平面模型的第二测量色度值，包括：测量每个所述平面模型至少5个不同位置处的色度值，并计算所述色度值的算术平均值，得到所述平面模型的第二测量色度值。
结合第一方面，在一种可行的实施方式中，所述三维物体模型为立方体，所述立方体包括上表面，所述拟合后的上表面色度值计算公式包括明度值计算公式、饱和度值计算公式及色调角值计算公式；其中，x为待评价三维物体的初始色度值，y为待评价三维物体拟合后的 色度值；
所述明度值计算公式如式(A-1)为：y L上＝1.0797x L上-5.6981   (A-1)；
所述饱和度值计算公式如式(B-1)为：y c上＝1.0077x C上+0.666   (B-1)；
所述色调角值计算公式如式(C-1)为：y h上＝0.9853x h上+1.587   (C-1)。
结合第一方面，在一种可行的实施方式中，所述三维物体模型为立方体，所述立方体包括前表面，所述拟合后的前表面色度值计算公式包括明度值计算公式、饱和度值计算公式及色调角值计算公式；其中，x为待评价三维物体的初始色度值，y为待评价三维物体拟合后的色度值；
所述明度值计算公式如式(A-2)为：y L前＝1.0304x L前-10.3   (A-2)；
所述饱和度值计算公式如式(B-2)为：y c前＝1.0082x C前-1.7921   (B-2)；
所述色调角值计算公式如式(C-2)为：y h前＝0.9582x h前+3.8288   (C-2)。
结合第一方面，在一种可行的实施方式中，根据拟合后的色度值计算公式对待评价三维物体进行色度值计算，包括：
获取待评价三维物体，测量得到所述待评价三维物体上表面和/或前表面的测量色度值，所述上表面和/或前表面的测量色度值包括明度值、饱和度值及色调角值；将所述上表面和/或前表面的明度值代入拟合后的上表面和/或前表面的明度值计算公式，得到拟合后的明度值；将所述上表面和/或前表面的饱和度值代入拟合后的上表面和/或前表面的饱和度值计算公式，得到拟合后的饱和度值；将所述上表面和/或前表面的色调角值代入拟合后的上表面和/或前表面的色调角值计算公式，得到拟合后的色调角值；根据拟合后的明度值、饱和度值及色调角值得到所述待评价三维物体拟合后的色度值。
第二方面，本申请实施例提供一种三维物体色度值计算装置，所述装置包括：
第一获取单元，用于获取多个三维物体模型；
第二获取单元，用于基于所述三维物体模型的颜色获取同一色系的多个平面模型；
第三获取单元，用于获取置于标准观察箱中的三维物体模型与目标平面模型的光谱反射率以及标准观察箱中的照明光源的相对光谱能量分布值；
第一计算单元，用于根据所述光谱反射率及所述光谱能量分布值分别计算得到所述三维物体模型的第一计算色度值、所述目标平面模型的第二计算色度值；其中，所述目标平面模型为所述同一色系的多个平面模型中与所述三维物体模型的颜色接近度最高的一个平面模型；
构建单元，用于基于多个所述三维物体模型的第一计算色度值与多个所述目标平面模型的第二计算色度值构建得到线性拟合函数，所述线性拟合函数为拟合后的色度值计算公式；
第二计算单元，用于根据拟合后的色度值计算公式对待评价三维物体进行色度值计算。
结合第二方面，在一种可行的实施方式中，所述第一计算色度值和第二计算色度值包括明度值、饱和度值及色调角值。
结合第二方面，在一种可行的实施方式中，所述三维物体模型为立方体，所述立方体包括上表面，所述拟合后的上表面色度值计算公式包括明度值计算公式、饱和度值计算公式及色调角值计算公式；其中，x为待评价三维物体的初始色度值，y为待评价三维物体拟合后的色度值；
所述明度值计算公式如式(A-1)为：y L上＝1.0797x L上-5.6981   (A-1)；
所述饱和度值计算公式如式(B-1)为：y c上＝1.0077x C上+0.666   (B-1)；
所述色调角值计算公式如式(C-1)为：y h上＝0.9853x h上+1.587   (C-1)。
结合第二方面，在一种可行的实施方式中，所述三维物体模型为立方体，所述立方体包括前表面，所述拟合后的前表面色度值计算公式包括明度值计算公式、饱和度值计算公式及色调角值计算公式；其中，x为待评价三维物体的初始色度值，y为待评价三维物体拟合后的色度值；
所述明度值计算公式如式(A-2)为：y L前＝1.0304x L前-10.3   (A-2)；
所述饱和度值计算公式如式(B-2)为：y c前＝1.0082x C前-1.7921   (B-2)；
所述色调角值计算公式如式(C-2)为：y h前＝0.9582x h前+3.8288   (C-2)。
结合第二方面，在一种可行的实施方式中，所述第二计算单元，包括：
获取子单元，用于获取待评价三维物体，测量得到所述待评价三维物体上表面和/或前表面的测量色度值，所述上表面和/或前表面的测量色度值包括明度值、饱和度值及色调角值；
第一处理子单元，用于将所述上表面和/或前表面的明度值代入拟合后的上表面和/或前表面的明度值计算公式，得到拟合后的明度值；
第二处理子单元，用于将所述上表面和/或前表面的饱和度值代入拟合后的上表面和/或前表面的饱和度值计算公式，得到拟合后的饱和度值；
第三处理子单元，用于将所述上表面和/或前表面的色调角值代入拟合后的上表面和/或前表面的色调角值计算公式，得到拟合后的色调角值；及
输出子单元，用于根据拟合后的明度值、饱和度值及色调角值得到所述待评价三维物体拟合后的色度值。
第三方面，本申请提供一种计算机非易失性存储介质，所述存储介质包括存储的程序，在所述程序运行时控制所述存储介质所在设备执行上述第一方面所述的三维物体色度值计算方法中拟合后的色度值计算公式。
第四方面，本申请提供一种计算机设备，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现上述第一方面所述的三维物体色度值计算方法中拟合后的色度值计算公式。
第五方面，本申请提供一种三维物体色度值计算系统，包括检测部件、存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现上述第一方面所述的三维物体色度值计算方法中拟合后的色度值计算公式。
有益效果：
在本方案中，通过利用与三维物体模型颜色最接近的目标平面模型，将两者置于同一标准观察箱中，得到三维物体模型与目标平面模型的计算色度值，通过多个三维物体模型的计算色度值以及多个目标平面模型的计算色度值来构建拟合函数，从而得到拟合后的色度值计算公式，使得通过拟合后的色度值计算公式能够提高得到的三维物体的色度值的准确度。
附图说明
下面结合附图和实施例对本申请进一步说明。
图1为本申请具体实施例中三维物体色度值计算方法流程示意图；
图2-1为本申请具体实施例中三维物体模型的上表面与目标平面模型的颜色L * 10的散点分布和数学拟合关系图；
图2-2为本申请具体实施例中三维物体模型的上表面与目标平面模型的颜色C * 10,ab的散点分布和数学拟合关系图；
图2-3为本申请具体实施例中三维物体模型的上表面与目标平面模型的颜色h * 10,ab的散点分布和数学拟合关系图；
图3-1为本申请实施例中三维物体模型的前表面与目标平面模型的颜色L * 10的散点分布和数学拟合关系图；
图3-2为本申请实施例中三维物体模型的前表面与目标平面模型的颜色C * 10,ab的散点分布和数学拟合关系图；
图3-3为本申请实施例中三维物体模型的前表面与目标平面模型的颜色h * 10,ab的散点分布和数学拟合关系图；
图4为本申请另一具体实施例中三维物体色度值计算装置的结构框图示意图；
图5为本申请另一具体实施例中计算机设备的结构框图示意图；
图6为本申请另一具体实施例中三维物体色度值计算系统的结构框图示意图。
具体实施方式
为了更好的理解本申请的技术方案，下面结合附图对本申请实施例进行详细描述。
应当明确，所描述的实施例仅仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其它实施例，都属于本申请保护的范围。
在本申请实施例中使用的术语是仅仅出于描述特定实施例的目的，而非旨在限制本申请。在本申请实施例和所附权利要求书中所使用的单数形式的“一种”、“所述”和“该”也旨在包括多数形式，除非上下文清楚地表示其他含义。
应当理解，本文中使用的术语“和/或”仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。另外，本文中字符“/”，一般表示前后关联对象是一种“或”的关系。
图1为本申请具体实施例中三维物体色度值计算方法的流程示意图，本申请三维物体色度值计算方法包括以下步骤S10至步骤S60：
步骤S10，获取多个三维物体模型；
步骤S20，基于所述三维物体模型的颜色获取同一色系的多个平面模型；
步骤S30，获取置于标准观察箱中的三维物体模型与目标平面模型的光谱反射率以及标准观察箱中的照明光源的相对光谱能量分布值；其中，所述目标平面模型为所述同一色系的多个平面模型中与所述三维物体模型的颜色接近度最高的一个平面模型；
步骤S40，根据所述光谱反射率及所述光谱能量分布值分别计算得到所述三维物体模型的第一计算色度值、所述目标平面模型的第二计算色度值；
步骤S50，基于多个所述三维物体模型的第一计算色度值与多个所述目标平面模型的第二计算色度值构建得到线性拟合函数，所述线性拟合函数为拟合后的色度值计算公式；
步骤S60，根据拟合后的色度值计算公式对待评价三维物体进行色度值计算。
在本方案中，通过利用与三维物体模型颜色最接近的目标平面模型，将两者置于同一标准观察箱中，得到三维物体模型与目标平面模型的计算色度值，通过多个三维物体模型的计 算色度值以及多个目标平面模型的计算色度值来构建拟合函数，从而得到拟合后的色度值计算公式，使得通过拟合后的色度值计算公式能够提高得到的三维物体的色度值的准确度。
以下结合实施例以及本申请提供的计算方法详细阐述本方案：
步骤S10，获取多个三维物体模型。
在本实施例中，三维物体模型采用三维打印技术打印成型。所述三维物体模型的最小维度大于或等于4cm，所述三维物体模型为规则形状且单色的立体模型，如球体、立方体、锥体等。示例性地，三维物体模型可以是长4cm×宽4cm×高4cm的立方体。
多个三维物体模型的颜色不同，具体地，可以打印至少5种不同色系的三维物体模型。同一色系的三维物体模型的颜色不同且同一色系的三维物体模型的数量为m，m为大于或等于4的整数。示例性地，可以打印4个红色的三维物体模型，4个蓝色的三维物体模型，4个黄色的三维物体模型，4个绿色的三维物体模型，4个灰色的三维物体模型。
所述三维物体模型的颜色参考国际照明委员会推荐的颜色中心的颜色进行打印。在本实施例中，参考的每种颜色中心的颜色打印得到4个立方体的三维物体模型且该4个立方体的三维物体模型的颜色不同，立方体的尺寸为长4cm×宽4cm×高4cm，参考的5种颜色中心的颜色分别为灰色、红色、黄色、绿色和蓝色。
在本实施例中，所述第一计算色度值和第二计算色度值均包括明度值、饱和度值及色调角值。具体地，灰色的三维物体模型在打印时参考的
Figure PCTCN2021111939-appb-000006
色度值为(62.0，0.0，0.0)，红色的三维物体模型在打印时参考的
Figure PCTCN2021111939-appb-000007
色度值为(44.0，37.0，23.0)，黄色的三维物体模型在打印时参考的
Figure PCTCN2021111939-appb-000008
色度值为(87.0，-7.0，47.0)，绿色的三维物体模型在打印时参考的
Figure PCTCN2021111939-appb-000009
色度值为(56.0，-32.0，0.0)，蓝色的三维物体模型在打印时参考的
Figure PCTCN2021111939-appb-000010
色度值为(36.0，5.0，-31.0)。
进一步地，为了保证三维物体模型的颜色均匀性以及样本有效性，选用的三维物体模型的表面应具有均匀的颜色。所述方法还包括：
对多个拟选用的三维物体模型进行筛查，得到有效的三维物体模型。
在本实施例中，可以通过计算单个三维物体模型不同位置处的离均色差来判断三维物体模型表面颜色是否均匀，从而确定该三维物体模型是否为有效的三维物体模型。
具体地，所述离均色差的计算步骤，包括：计算单个三维物体模型任意一个位置的色度值与所述三维物体模型不同位置处的色度值的平均值之间的色差。
确定三维物体模型的离均色差小于或等于第一预设值。在本实施例中，采用CIELAB色差计算公式进行离均色差计算，第一预设值为1.0。当三维物体模型的离均色差小于或等于1.0时，则该三维物体模型的表面颜色满足均匀性要求，可以作为有效的三维物体模型。
步骤S20，基于所述三维物体模型的颜色获取同一色系的多个平面模型。
在本实施例中，平面模型采用三维打印技术打印成型，平面模型为形状规则、颜色均匀的平面图形，如圆形、矩形、三角形等模型。基于三维物体模型打印中参考的颜色中心的颜色，分别以灰色
Figure PCTCN2021111939-appb-000011
色度值(50.0，0.0，0.0)、红色
Figure PCTCN2021111939-appb-000012
色度值(44.0，37.0，23.0)，黄色
Figure PCTCN2021111939-appb-000013
色度值(87.0，-7.0，47.0)，绿色
Figure PCTCN2021111939-appb-000014
色度值(56.0，-32.0，0.0)，蓝色
Figure PCTCN2021111939-appb-000015
Figure PCTCN2021111939-appb-000016
色度值(36.0，5.0，-31.0)为参考打印多个平面模型，其中，平面模型的厚度小于或等于1mm，且所述三维物体模型在所述平面模型上的正投影面积等于所述平面模型的面积。示例性地，三维物体模型长4cm×宽4cm×高4cm，平面模型为长4cm×宽4cm×高1mm的长 方体；或者，三维物体模型长4cm×宽5cm×高4cm，与三维物体模型长4cm×宽5cm所对应的平面模型为长4cm×宽5cm。
并且，与每个所述三维物体模型对应的同一色系的平面模型的数量为n，n为大于或等于10的整数。在本实施例中，与每个所述三维物体模型对应的同一色系的平面模型的数量为16，即1个灰色的三维物体模型配置16个灰色的平面模型。
需要说明的是，步骤S10以及步骤S20可以同步进行，也可以异步进行，在此不做限定。打印三维物体模型的设备和打印平面模型的设备相同，所述三维物体模型在所述平面模型上的正投影面积等于所述平面模型的面积。
在步骤S30之前，所述方法还包括：
对多个平面模型进行筛查，得到有效的平面模型；
基于每个所述三维物体模型的颜色从所述同一色系的多个有效的平面模型中筛选得到目标平面模型，其中，所述目标平面模型与同一色系的所述三维物体模型的颜色接近度最高。
在本实施例中，所述对多个平面模型进行筛查，得到有效的平面模型的步骤包括：
测量得到每个所述三维物体模型的第一测量色度值；
测量得到每个所述平面模型的第二测量色度值；
基于所述第一测量色度值和第二测量色度值获取与所述三维物体模型的颜色属于同一色系的多个有效的平面模型。
为了提高实验数据的准确性，三维物体模型的第一测量色度值的测量条件、测量方法与平面模型的第二测量色度值的测量条件、测量方法相同。
具体地，使用X-Rite eXact分光光度计在D65、10°视场的测量条件下，测量得到每个所述三维物体模型的第一测量色度值，具体测量方法为：
测量每个所述三维物体模型至少5个不同位置处的色度值，并计算所述色度值的算术平均值，得到所述三维物体模型的第一测量色度值。
其中，所述至少5个不同位置位于所述三维物体模型同一平面或同一弧面上。在本实施例中，打印得到并进行有效性筛选后的三维物体模型的第一测量色度值如表1所示：
表1.三维物体模型的第一测量色度值分布
Figure PCTCN2021111939-appb-000017
Figure PCTCN2021111939-appb-000018
其中，L * 10表示三维物体模型的明度值；a * 10，b * 10表示三维物体模型的颜色的色品参数。
具体地，使用X-Rite eXact分光光度计在D65、10°视场的测量条件下，所述测量得到每个所述平面模型的第二测量色度值，包括：
测量每个所述平面模型至少5个不同位置处的色度值，并计算所述色度值的算术平均值，得到所述平面模型的第二测量色度值。
以4个灰色三维物体模型的上表面为例，对应的平面模型的L* 10，a* 10，b* 10如表2所示:
表2 与灰色三维物体模型的上表面对应的平面模型的第二测量色度值
Figure PCTCN2021111939-appb-000019
基于所述第一测量色度值和第二测量色度值对平面模型的有效性筛查，可以得到与三维物体模型颜色接近的有效的平面模型。
在一个可选的实施方式中，在确定所述平面模型的第二测量色度值之前，通过计算单个平面模型不同位置处的离均色差来判断平面模型表面的颜色是否均匀，具体的平面模型离均色差的计算方法与三维物体模型离均色差的计算方法相同；确定平面模型的离均色差小于或等于第一预设值。在本实施例中，采用CIELAB色差计算公式进行离均色差计算，第一预设值为1.0。当平面模型的离均色差小于或等于1.0时，则该平面模型的表面颜色满足均匀性要求，可以作为满足有效的平面模型的前提条件。
在平面模型的表面颜色满足均匀性的前提下，将计算的平面模型的色度值的算术平均值，确定为所述平面模型的第二测量色度值。
在其他实施方式中，还可以组织奇数名观察者进行观察，人数要求是越多越好，观察者 人数最少5人，要求所有观察者中要有50％以上的观察者认为平面模型与对应的三维物体模型的颜色视觉上接近，则初步认定该平面模型与该三维物体模型为同一色系且颜色接近的平面模型。示例性地，如果7名观察者中，至少有4名观察者认为平面模型的颜色与三维物体模型的颜色一致，此时认为该平面模型的颜色与三维物体模型的颜色视觉上接近，为有效的平面模型。观察者可通过标准观察箱进行观察，具体的标准观察箱的观察条件如下文所述，在此不再赘述。
在另一可选的实施方式中，还可以在组织奇数名观察者对三维物体模型的颜色和平面模型的颜色进行观察并同时参考第一测量色度值和第二测量色度值以得到有效的平面模型。
进一步地，基于每个所述三维物体模型的颜色从所述同一色系的多个有效的平面模型中筛选得到目标平面模型。
具体地，可以获取至少10名色觉正常的男性和女性观察者从所述多个平面模型中筛选得到目标平面模型。其中女性的人数多于男性，且观察者的年龄分布在20-32岁。在本实施例中，组织了31名，其中男9名，女22名，年龄分布在20～26岁的观察者，逐一比对在标准观察箱中的多个平面模型以及对应的三维物体模型在颜色上的差异，筛选得到目标平面模型。要求每个三维物体模型和对应的平面模型在观察箱中观察次数不少于30次。当目标平面模型存在多个时，选取被挑选概率最高的目标平面模型作为目标平面模型。
观察者距离标准观察箱的观察距离为50cm-60cm，实验的观察环境为暗室，实验在LEDView标准观察箱中进行，实验光源的色温为6496K，照度800lux，显色指数93.5。
每组待评价的平面模型和三维物体模型随机呈现给观察者，每个观察者在观察实验中单次持续时间为20min左右；本实施例中所述的色觉正常是基于李春慧，李育宏编著，辽宁科学技术出版社出版的《新编色觉检查图》(1994年第2版)进行观察者色觉检测，检测结果满足要求，即判断为观察者色觉正常。观察者还要求具有颜色科学的专业背景。
步骤S30，获取置于标准观察箱中的三维物体模型与目标平面模型的光谱反射率以及标准观察箱中的照明光源的相对光谱能量分布值；其中，所述目标平面模型为所述同一色系的多个平面模型中与所述三维物体模型的颜色接近度最高的一个平面模型。
在具体实施例中，可以将所述三维物体模型与所述目标平面模型置于同一标准观察箱内，测量得到所述三维物体模型的第一光谱反射率ρ 1(λ)及所述目标平面模型的第二光谱反射率ρ 2(λ)，其中，所述标准观察箱的照明光源的相对光谱能量分布值为S(λ)；
步骤S40，根据所述光谱反射率及所述光谱能量分布值分别计算得到所述三维物体模型的第一计算色度值、所述目标平面模型的第二计算色度值。
在本实施例中，使用光谱辐射度PR655测量标准观察箱中照明光源的相对光谱能量分布S(λ)、三维物体模型的第一光谱反射率ρ 1(λ)和目标平面模型的第二光谱反射率ρ 2(λ)，代入色度值计算公式，式(1)可得到三维物体模型和平面模型的三刺激值XYZ，进而可由式(2)计算得到明度值(L *)、色品参数(a *，b *)：
Figure PCTCN2021111939-appb-000020
其中，
Figure PCTCN2021111939-appb-000021
Figure PCTCN2021111939-appb-000022
其中，式(2)中X n、Y n、Z n分别为标准观察箱中照明光源的三刺激值，X、Y、Z分别为三维物体模型或平面模型的三刺激值；
通过式(1)计算照明光源的三刺激值X n、Y n、Z n时，式(1)中ρ(λ)＝1。
进一步根据式(3)及式(4)计算得到色彩饱和度值C * ab、色调角值h * ab。
Figure PCTCN2021111939-appb-000023
Figure PCTCN2021111939-appb-000024
对于20个三维物体模型，标准观察箱中光源照明下的三维物体模型上表面及前表面的第一计算色度值如表3所示。标准观察箱中光源照明下的目标平面模型的第二计算色度值如表4所示：
表3 标准观察箱中光源照明下三维物体模型上表面及前表面的第一计算色度值
Figure PCTCN2021111939-appb-000025
表4 与三维物体模型上表面和前表面颜色视觉上最接近的平面模型的第二计算色度值
Figure PCTCN2021111939-appb-000026
Figure PCTCN2021111939-appb-000027
步骤S50，基于多个所述三维物体模型的第一计算色度值与多个所述目标平面模型的第二计算色度值构建得到线性拟合函数，所述线性拟合函数为拟合后的色度值计算公式。
在本实施例中，分别以上述多个三维物体模型的上表面和前表面的第一计算色度值以及对应的目标平面模型的第二计算色度值为基础，绘制散点图，并采用线性拟合的方法，拟合得到拟合后的色度值计算公式。所述拟合后的上表面色度值计算公式包括明度值计算公式、饱和度值计算公式及色调角值计算公式。
具体地，步骤S50，包括：
根据所述三维物体模型上表面和/或前表面的明度值以及目标平面模型的明度值拟合得到拟合后的上表面和/或前表面明度值计算公式；
根据所述三维物体模型上表面和/或前表面的饱和度值以及目标平面模型的饱和度值拟合得到拟合后的上表面和/或前表面饱和度值计算公式；
根据所述三维物体模型上表面和/或前表面的色调角值以及目标平面模型的色调角值拟合得到拟合后的上表面和/或前表面色调角值计算公式。
图2-1为本申请具体实施例中三维物体模型的上表面与目标平面模型的颜色L * 10的散点分布和数学拟合关系图，如图2-1所示，三维物体模型的上表面拟合后的明度值的计算公式为：
y L上＝1.0797x L上-5.6981   (A-1)，其中，x L上表示三维物体模型上表面的初始明度值，y L上表示拟合后的三维物体模型上表面的明度值。
图2-2为本申请具体实施例中三维物体模型的上表面与目标平面模型的颜色C * 10,ab的散点分布和数学拟合关系图，如图2-2所示，三维物体模型的上表面拟合后的饱和度值的计算公式为：
y C上＝1.0077x C上+0.666   (B-1)，其中，x C上表示三维物体模型上表面的初始饱和度值，y C上表示拟合后的三维物体模型上表面的饱和度值。
图2-3为本申请具体实施例中三维物体模型的上表面与目标平面模型的颜色h * 10,ab的散点分布和数学拟合关系图，如图2-3所示，三维物体模型的上表面拟合后的色调角值的计算公式为：
y h上＝0.9853x h上+1.587   (C-1)，其中，x h上表示三维物体模型上表面的初始色调角值，y h上表示拟合后的三维物体模型的上表面的色调角值。
图3-1为本申请实施例中三维物体模型的前表面与目标平面模型的颜色L * 10的散点分布和数学拟合关系图，如图3-1所示，三维物体模型的前表面拟合后的明度值的计算公式为：
y L前＝1.0304x L前-10.3   (A-2)，其中，x L前表示三维物体模型前表面的初始明度值，y L前表示拟合后的三维物体模型前表面的明度值。
图3-2为本申请实施例中三维物体模型的前表面与目标平面模型的颜色C * 10,ab的散点分布和数学拟合关系图，如图3-2所示，三维物体模型的前表面拟合后的饱和度值的计算公式为：
y C前＝1.0082x C前-1.7921   (B-2)，其中，x C前表示三维物体模型前表面的初始饱和度值，y C前表示拟合后的三维物体模型前表面的饱和度值。
图3-3为本申请实施例中三维物体模型的前表面与目标平面模型的颜色h * 10,ab的散点分布和数学拟合关系图，如图3-3所示，三维物体模型的前表面拟合后的色调角值的计算公式为：
y h前＝0.9582x h前+3.8288   (C-2)，其中，x h前表示三维物体模型上表面的初始色调角值，y h上表示拟合后的三维物体模型的前表面的色调角值。
步骤S60，根据拟合后的色度值计算公式对待评价三维物体进行色度值计算，具体包括：
获取待评价三维物体，测量得到所述待评价三维物体上表面和/或前表面的测量色度值，所述上表面和/或前表面的测量色度值包括明度值、饱和度值及色调角值；
将所述上表面和/或前表面的明度值代入拟合后的上表面和/或前表面的明度值计算公式，得到拟合后的明度值；
将所述上表面和/或前表面的饱和度值代入拟合后的上表面和/或前表面的饱和度值计算公式，得到拟合后的饱和度值；
将所述上表面和/或前表面的色调角值代入拟合后的上表面和/或前表面的色调角值计算公式，得到拟合后的色调角值；
根据拟合后的明度值、饱和度值及色调角值得到所述待评价三维物体拟合后的色度值。
在具体实施例中，可以按照上述测量三维物体模型的色度值的测量条件，测量待评价三维物体的测量色度值，待评价三维物体的测量色度值包括明度值、饱和度值及色调角值，并分别代入对应的计算公式中，从而得到待评价三维物体拟合后的色度值。本申请中待评价三维物体的测量色度值包括明度值、饱和度值及色调角值可以是直接测量或间接测量，可以是通过测量明度值、色品参数进而根据饱和度值及色调角值的计算公式得出的饱和度值和色调角值。
本申请中，使用不同形状的三维物体模型、和/或在不同的测量条件下，得到的三维物体的色度值的计算公式中系数存在差异，但这也在本申请的保护范围内。
实施例2
本申请提供一种三维物体色度值计算装置，其特征在于，如图4所示，所述装置包括：
第一获取单元，用于获取多个三维物体模型；
第二获取单元，用于基于所述三维物体模型的颜色获取同一色系的多个平面模型；
第三获取单元，用于获取置于标准观察箱中的三维物体模型与目标平面模型的光谱反射率以及标准观察箱中的照明光源的相对光谱能量分布值；
第一计算单元，用于根据所述光谱反射率及所述光谱能量分布值分别计算得到所述三维物体模型的第一计算色度值、所述目标平面模型的第二计算色度值；其中，所述目标平面模型为所述同一色系的多个平面模型中与所述三维物体模型的颜色接近度最高的一个平面模型；
构建单元，用于基于多个所述三维物体模型的第一计算色度值与多个所述目标平面模型的第二计算色度值构建得到线性拟合函数，所述线性拟合函数为拟合后的色度值计算公式；
第二计算单元，用于根据拟合后的色度值计算公式对待评价三维物体进行色度值计算。
在本实施例中，所述第一计算色度值和第二计算色度值包括明度值、饱和度值及色调角值。
具体地，所述三维物体模型为立方体，所述立方体包括上表面，所述拟合后的上表面色度值计算公式包括明度值计算公式、饱和度值计算公式及色调角值计算公式；其中，x为待评价三维物体的初始色度值，y为待评价三维物体拟合后的色度值；
所述明度值计算公式如式(A-1)为：y L上＝1.0797x L上-5.6981   (A-1)；
所述饱和度值计算公式如式(B-1)为：y c上＝1.0077x C上+0.666   (B-1)；
所述色调角值计算公式如式(C-1)为：y h上＝0.9853x h上+1.587   (C-1)。
进一步地，所述三维物体模型为立方体，所述立方体包括前表面，所述拟合后的前表面色度值计算公式包括明度值计算公式、饱和度值计算公式及色调角值计算公式；其中，x为待评价三维物体的初始色度值，y为待评价三维物体拟合后的色度值；
所述明度值计算公式如式(A-2)为：y L前＝1.0304x L前-10.3   (A-2)；
所述饱和度值计算公式如式(B-2)为：y c前＝1.0082x C前-1.7921   (B-2)；
所述色调角值计算公式如式(C-2)为：y h前＝0.9582x h前+3.8288   (C-2)。
可选地，所述第二计算单元，包括：
获取子单元，用于获取待评价三维物体，测量得到所述待评价三维物体上表面和/或前表面的测量色度值，所述上表面和/或前表面的测量色度值包括明度值、饱和度值及色调角值；
第一处理子单元，用于将所述上表面和/或前表面的明度值代入拟合后的上表面和/或前表面的明度值计算公式，得到拟合后的明度值；
第二处理子单元，用于将所述上表面和/或前表面的饱和度值代入拟合后的上表面和/或前表面的饱和度值计算公式，得到拟合后的饱和度值；
第三处理子单元，用于将所述上表面和/或前表面的色调角值代入拟合后的上表面和/或前表面的色调角值计算公式，得到拟合后的色调角值；及
输出子单元，用于根据拟合后的明度值、饱和度值及色调角值得到所述待评价三维物体拟合后的色度值。
需要说明的是本申请中三维物体色度值计算装置可以是一个集成的装置，也可以是多个分开的装置，多个分开的装置执行不同的功能。
实施例3
本申请实施例还提供一种计算机非易失性存储介质，所述存储介质包括存储的程序，在所述程序运行时控制所述存储介质所在设备执行实施例1所述的三维物体色度值计算方法中拟合后的色度值计算公式。在本实施例中，所述拟合后的色度值计算公式如实施例1中所示，在此不再赘述。
实施例4
本申请实施例还提供一种计算机设备，如图5所示，计算机设备200包括存储器202、 处理器201以及存储在所述存储器202中并可在所述处理器上运行的计算机程序203，所述处理器执行所述计算机程序203时实现实施例1中的三维物体色度值计算方法中拟合后的色度值计算公式。在本实施例中，所述拟合后的色度值计算公式如实施例1中所示，在此不再赘述。
实施例5
本申请实施例还提供一种三维物体色度值计算系统，如图6所示，三维物体色度值计算系统300包括检测部件303、存储器302、处理器301以及存储在所述存储器302中并可在所述处理器上运行的计算机程序，所述检测部件303用于测量待评价三维物体的色度值(如L* 2，C * 2，h * 2)，例如可以是X-Rite eXact分光光度计，所述处理器301执行所述计算机程序时实现实施例1所述的三维物体色度值计算方法中拟合后的色度值计算公式。即所述计算机程序包括拟合后的色度值计算公式，从而能够计算得到拟合后的色度值。
在本实施例中，所述拟合后的色度值计算公式如实施例1中所示，在此不再赘述。
需要说明的是，计算机设备可以是桌上型计算机、笔记本、掌上电脑及云端服务器等计算设备。计算机设备可包括，但不仅限于，处理器、存储器。本领域技术人员可以理解，图11仅仅是计算机设备的示例，并不构成对计算机设备的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件，例如计算机设备还可以包括输入输出设备、网络接入设备、总线等。
所称处理器可以是中央处理单元(Central Processing Unit，CPU)，还可以是其他通用处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现场可编程门阵列(Field-Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
存储器可以是计算机设备的内部存储单元，例如计算机设备的硬盘或内存。存储器也可以是计算机设备的外部存储设备，例如计算机设备上配备的插接式硬盘，智能存储卡(Smart Media Card,SMC)，安全数字(Secure Digital,SD)卡，闪存卡(Flash Card)等。进一步地，存储器还可以既包括计算机设备的内部存储单元也包括外部存储设备。存储器用于存储计算机程序以及计算机设备所需的其他程序和数据。存储器还可以用于暂时地存储已经输出或者将要输出的数据。
以上仅为本申请的较佳实施例而已，并不用以限制本申请，凡在本申请的精神和原则之内，所做的任何修改、等同替换、改进等，均应包含在本申请保护的范围之内

Claims (21)

  1. 一种三维物体色度值计算方法，其特征在于，所述方法包括：
    获取多个三维物体模型；
    基于所述三维物体模型的颜色获取同一色系的多个平面模型；
    获取置于标准观察箱中的三维物体模型与目标平面模型的光谱反射率以及标准观察箱中的照明光源的相对光谱能量分布值；其中，所述目标平面模型为所述同一色系的多个平面模型中与所述三维物体模型的颜色接近度最高的一个平面模型；
    根据所述光谱反射率及所述光谱能量分布值分别计算得到所述三维物体模型的第一计算色度值、所述目标平面模型的第二计算色度值；
    基于多个所述三维物体模型的第一计算色度值与多个所述目标平面模型的第二计算色度值构建得到线性拟合函数，所述线性拟合函数为拟合后的色度值计算公式；
    根据拟合后的色度值计算公式对待评价三维物体进行色度值计算。
  2. 根据权利要求1所述的方法，其特征在于，所述第一计算色度值和第二计算色度值均包括明度值、饱和度值及色调角值。
  3. 根据权利要求1所述的方法，其特征在于，所述方法满足下列特征(1)至(7)中的至少一种：
    (1)所述三维物体模型、所述平面模型均采用三维打印技术得到；
    (2)所述三维物体模型的最小维度大于或等于4cm；
    (3)所述三维物体模型为规则形状且单色的立体模型；
    (4)同一色系的所述三维物体模型的数量为m，m为大于或等于4的整数；
    (5)所述多个三维物体模型的颜色参考国际照明委员会推荐的颜色中心的颜色进行打印，至少包括5种不同色系，且同一色系的多个所述三维物体模型的色度值不同；
    (6)与每个所述三维物体模型对应的同一色系的平面模型的数量为n，n为大于或等于10的整数；
    (7)同一色系的三维物体模型、平面模型的维度一致。
  4. 根据权利要求3所述的方法，其特征在于，所述多个三维物体模型的颜色分别选自灰色、红色、黄色、绿色和蓝色进行打印，其中，灰色参考的
    Figure PCTCN2021111939-appb-100001
    色度值为(62.0，0.0，0.0)，红色参考的
    Figure PCTCN2021111939-appb-100002
    色度值为(44.0，37.0，23.0)，黄色参考的
    Figure PCTCN2021111939-appb-100003
    色度值为(87.0，-7.0，47.0)，绿色参考的
    Figure PCTCN2021111939-appb-100004
    色度值为(56.0，-32.0，0.0)，蓝色参考的
    Figure PCTCN2021111939-appb-100005
    色度值为(36.0，5.0，-31.0)。
  5. 根据权利要求3或4所述的方法，其特征在于，所述平面模型的厚度小于或等于1mm，且所述三维物体模型在所述平面模型上的正投影面积等于所述平面模型的面积。
  6. 根据权利要求1所述的方法，其特征在于，在所述获取置于标准观察箱中的三维物体模型与目标平面模型的光谱反射率以及标准观察箱中的照明光源的相对光谱能量分布值之前，所述方法还包括：
    对多个平面模型进行筛选，得到有效的平面模型；
    基于每个所述三维物体模型的颜色从所述同一色系的多个有效的平面模型中筛选得到目标平面模型，其中，所述目标平面模型与同一色系的所述三维物体模型的颜色接近度最高。
  7. 根据权利要求6所述的方法，其特征在于，所述对多个平面模型进行筛选，得到有效 的平面模型具体包括：
    测量得到每个所述三维物体模型的第一测量色度值；
    测量得到每个所述平面模型的第二测量色度值；
    基于所述第一测量色度值和第二测量色度值获取与所述三维物体模型的颜色属于同一色系的多个有效的平面模型。
  8. 根据权利要求7所述的方法，其特征在于，所述测量得到每个所述三维物体模型的第一测量色度值，包括：
    测量每个所述三维物体模型至少5个不同位置处的色度值，并计算所述色度值的算术平均值，得到所述三维物体模型的第一测量色度值。
  9. 根据权利要求8所述的方法，其特征在于，所述至少5个不同位置位于所述三维物体模型同一平面或同一弧面上。
  10. 根据权利要求7所述的方法，其特征在于，所述测量得到每个所述平面模型的第二测量色度值，包括：
    测量每个所述平面模型至少5个不同位置处的色度值，并计算所述色度值的算术平均值，得到所述平面模型的第二测量色度值。
  11. 根据权利要求2所述的方法，其特征在于，所述三维物体模型为立方体，所述立方体包括上表面，所述拟合后的上表面色度值计算公式包括明度值计算公式、饱和度值计算公式及色调角值计算公式；其中，x为待评价三维物体的初始色度值，y为待评价三维物体拟合后的色度值；
    所述明度值计算公式如式(A-1)为：y L上＝1.0797x L上-5.6981  (A-1)；
    所述饱和度值计算公式如式(B-1)为：y c上＝1.0077x C上+0.666  (B-1)；
    所述色调角值计算公式如式(C-1)为：y h上＝0.9853x h上+1.587  (C-1)。
  12. 根据权利要求2所述的方法，其特征在于，所述三维物体模型为立方体，所述立方体包括前表面，所述拟合后的前表面色度值计算公式包括明度值计算公式、饱和度值计算公式及色调角值计算公式；其中，x为待评价三维物体的初始色度值，y为待评价三维物体拟合后的色度值；
    所述明度值计算公式如式(A-2)为：y L前＝1.0304x L前-10.3  (A-2)；
    所述饱和度值计算公式如式(B-2)为：y c前＝1.0082x C前-1.7921  (B-2)；
    所述色调角值计算公式如式(C-2)为：y h前＝0.9582x h前+3.8288  (C-2)。
  13. 根据权利要求11或12所述的方法，其特征在于，根据拟合后的色度值计算公式对待评价三维物体进行色度值计算，包括：
    获取待评价三维物体，测量得到所述待评价三维物体上表面和/或前表面的测量色度值，所述上表面和/或前表面的测量色度值包括明度值、饱和度值及色调角值；
    将所述上表面和/或前表面的明度值代入拟合后的上表面和/或前表面的明度值计算公式，得到拟合后的明度值；
    将所述上表面和/或前表面的饱和度值代入拟合后的上表面和/或前表面的饱和度值计算公式，得到拟合后的饱和度值；
    将所述上表面和/或前表面的色调角值代入拟合后的上表面和/或前表面的色调角值计算公式，得到拟合后的色调角值；
    根据拟合后的明度值、饱和度值及色调角值得到所述待评价三维物体拟合后的色度值。
  14. 一种三维物体色度值计算装置，其特征在于，所述装置包括：
    第一获取单元，用于获取多个三维物体模型；
    第二获取单元，用于基于所述三维物体模型的颜色获取同一色系的多个平面模型；
    第三获取单元，用于获取置于标准观察箱中的三维物体模型与目标平面模型的光谱反射率以及标准观察箱中的照明光源的相对光谱能量分布值；
    第一计算单元，用于根据所述光谱反射率及所述光谱能量分布值分别计算得到所述三维物体模型的第一计算色度值、所述目标平面模型的第二计算色度值；其中，所述目标平面模型为所述同一色系的多个平面模型中与所述三维物体模型的颜色接近度最高的一个平面模型；
    构建单元，用于基于多个所述三维物体模型的第一计算色度值与多个所述目标平面模型的第二计算色度值构建得到线性拟合函数，所述线性拟合函数为拟合后的色度值计算公式；
    第二计算单元，用于根据拟合后的色度值计算公式对待评价三维物体进行色度值计算。
  15. 根据权利要求14所述的装置，其特征在于，所述第一计算色度值和第二计算色度值均包括明度值、饱和度值及色调角值。
  16. 根据权利要求15所述的装置，其特征在于，所述三维物体模型为立方体，所述立方体包括上表面，所述拟合后的上表面色度值计算公式包括明度值计算公式、饱和度值计算公式及色调角值计算公式；其中，x为待评价三维物体的初始色度值，y为待评价三维物体拟合后的色度值；
    所述明度值计算公式如式(A-1)为：y L上＝1.0797x L上-5.6981  (A-1)；
    所述饱和度值计算公式如式(B-1)为：y c上＝1.0077x C上+0.666  (B-1)；
    所述色调角值计算公式如式(C-1)为：y h上＝0.9853x h上+1.587  (C-1)。
  17. 根据权利要求15所述的装置，其特征在于，所述三维物体模型为立方体，所述立方体包括前表面，所述拟合后的前表面色度值计算公式包括明度值计算公式、饱和度值计算公式及色调角值计算公式；其中，x为待评价三维物体的初始色度值，y为待评价三维物体拟合后的色度值；
    所述明度值计算公式如式(A-2)为：y L前＝1.0304x L前-10.3  (A-2)；
    所述饱和度值计算公式如式(B-2)为：y c前＝1.0082x C前-1.7921  (B-2)；
    所述色调角值计算公式如式(C-2)为：y h前＝0.9582x h前+3.8288  (C-2)。
  18. 根据权利要求16或17所述的装置，其特征在于，所述第二计算单元，包括：
    获取子单元，用于获取待评价三维物体，测量得到所述待评价三维物体上表面和/或前表面的测量色度值，所述上表面和/或前表面的测量色度值包括明度值、饱和度值及色调角值；
    第一处理子单元，用于将所述上表面和/或前表面的明度值代入拟合后的上表面和/或前表面的明度值计算公式，得到拟合后的明度值；
    第二处理子单元，用于将所述上表面和/或前表面的饱和度值代入拟合后的上表面和/或前表面的饱和度值计算公式，得到拟合后的饱和度值；
    第三处理子单元，用于将所述上表面和/或前表面的色调角值代入拟合后的上表面和/或前表面的色调角值计算公式，得到拟合后的色调角值；及
    输出子单元，用于根据拟合后的明度值、饱和度值及色调角值得到所述待评价三维物体拟合后的色度值。
  19. 一种计算机非易失性存储介质，其特征在于，所述存储介质包括存储的程序，在所述程序运行时控制所述存储介质所在设备执行权利要求1至13任意一项所述的三维物体色度值计算方法中拟合后的色度值计算公式。
  20. 一种计算机设备，其特征在于，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现权利要求1至13任意一项所述的三维物体色度值计算方法中拟合后的色度值计算公式。
  21. 一种三维物体色度值计算系统，包括检测部件、存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现权利要求1至13任意一项所述的三维物体色度值计算方法中拟合后的色度值计算公式。
PCT/CN2021/111939 2021-03-04 2021-08-11 三维物体色度值计算方法及装置、三维物体色度值计算系统 WO2022183683A1 (zh)

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