Color evaluation system, color evaluation method, production method for dye, and color evaluation program

Abstract

A color evaluation system according to the present invention comprises an acquisition unit that acquires reference color information about a reference color, a subject model that represents recognition of color by a subject, and a reference model that represents recognition of color by a reference color vision person, a calculation unit that, on the basis of the reference color information and the subject model, calculates a subject response that represents recognition of the reference color by the subject and, on the basis of the reference color information and the reference model, calculates a reference response that represents recognition of the reference color by the reference color vision person, and a comparison unit that calculates the difference between the subject response and the reference response as a response difference.

Description

Color evaluation system, color evaluation method, dye manufacturing method, and color evaluation program

[0001] One aspect of the present disclosure relates to a color evaluation system, a color evaluation method, a dye manufacturing method, and a color evaluation program.

[0002] Information processing related to color vision has been known for some time. For example, a color processing device described in Patent Document 1 acquires color values ​​to be subjected to color processing, calculates a color vision degree coefficient representing the degree of color vision deficiency based on the population distribution of test results obtained from a color vision test administered to a predetermined group, calculates color conversion coefficients used to convert the acquired color values ​​based on the correspondence between the color vision degree coefficients and the sensitivity characteristics of L-, M-, and S-cones, and performs color conversion processing on the color values ​​using the color conversion coefficients.

[0003] Patent No. 5924289

[0004] There is a need for a system for quantitatively evaluating colors from the perspective of human color vision.

[0005] A color evaluation system according to one aspect of the present disclosure includes an acquisition unit that acquires reference color information regarding a reference color, a subject model that indicates the subject's perception of the color, and a reference model that indicates the reference color perception by a reference color vision person; a calculation unit that calculates a subject response that indicates the subject's perception of the reference color based on the reference color information and the subject model, and calculates a reference response that indicates the reference color perception by the reference color vision person based on the reference color information and the reference model; and a comparison unit that calculates the difference between the subject response and the reference response as a response difference.

[0006] A color evaluation method according to an aspect of the present disclosure is executed by a color evaluation system including at least one processor. The color evaluation method includes the steps of acquiring reference color information regarding reference colors, a subject model representing the perception of the colors by a subject, and a reference model representing the perception of the colors by a reference color vision person, calculating a subject response representing the perception of the reference colors by the subject based on the reference color information and the subject model, calculating a reference response representing the perception of the reference colors by the reference color vision person based on the reference color information and the reference model, and calculating a response difference between the subject response and the reference response.

[0007] A color evaluation program according to one aspect of the present disclosure causes a computer to perform the following steps: acquiring reference color information regarding a reference color, a subject model indicating the subject's perception of the color, and a reference model indicating the reference color perception by a reference color vision person; calculating a subject response indicating the subject's perception of the reference color based on the reference color information and the subject model; calculating a reference response indicating the reference color perception by the reference color vision person based on the reference color information and the reference model; and calculating the difference between the subject response and the reference response as a response difference.

[0008] In this aspect, the subject's perception of the reference color is calculated as the subject response, the reference color's perception by the reference color vision subject is calculated as the reference response, and the difference between these two responses is calculated as the response difference. This response difference quantitatively indicates the difference in perception of the reference color between the subject and the reference color vision subject. Therefore, by using this response difference, it is possible to quantitatively evaluate colors (reference colors) from the perspective of color vision.

[0009] According to one aspect of the present disclosure, colors can be quantitatively evaluated from the perspective of human color vision.

[0010] It is a diagram showing an example of the functional configuration of a color evaluation system. It is a flowchart showing an example of the operation of the color evaluation system. It is a graph showing an example of the sensitivity characteristics of an L cone, an M cone, and an S cone. It is a flowchart showing an example of the operation of the color evaluation system.

[0011] Various examples of the present disclosure will be described in detail below with reference to the accompanying drawings. In the description of the drawings, the same or equivalent elements are designated by the same reference numerals, and redundant description will be omitted.

[0012] [System Overview] The color assessment system according to the present disclosure is a computer system for quantitatively evaluating colors from the perspective of human color vision. It can also be said that the color assessment system is a computer system that evaluates colors taking color vision diversity into account. Color vision diversity refers to situations in which people differ in their perception or discrimination of colors. The color assessment system can be used to foster a common understanding of colors among people with different color vision, and to promote mutual understanding regarding color perception or discrimination.

[0013] There are five types of color vision: C type (Common), P type (Protanope), D type (Deuteranope), T type (Tritanope), and A type (Acromatic).

[0014] Type C is a group that has three types of cones: L cones, M cones, and S cones. L cones are photoreceptor cells that are highly sensitive to light in the long wavelength range, such as red. M cones are photoreceptor cells that are highly sensitive to light in the medium wavelength range, such as green. S cones are photoreceptor cells that are highly sensitive to light in the short wavelength range, such as blue. In the case of Japanese people, 95% of men and 99% of women belong to type C. Type C people are also said to have general color vision.

[0015] Meanwhile, people with P, D, T, and A types are also called colorblind. P type is a group consisting of P type strong (Protanopia) who do not have L cones and P type weak (Protanomaly) in which the sensitivity of L cones is shifted and similar to that of M cones. D type is a group consisting of D type strong (Deuteranopia) who do not have M cones and D type weak (Deuteranomaly) in which the sensitivity of M cones is shifted and similar to that of L cones. T type is a group that does not have S cones. A type is a group that has only one type of cone or no cones at all. P type and D type account for the majority of colorblind people, with T type and A type accounting for an extremely small proportion.

[0016] As an example of promoting common recognition or mutual understanding as described above, the color evaluation system may be used to evaluate the difference in recognition of a certain color between a person with color blindness and a person with normal color vision. Alternatively, the color evaluation system may be used to evaluate whether a certain color causes a discrepancy in recognition between a person with color blindness and a person with normal color vision. Alternatively, the color evaluation system may be used to adjust a reference spectrum, which is the spectrum of a reference color, to provide a color that is recognized in the same way by both people with normal color vision and a person with color blindness. The reference spectrum is an example of reference color information regarding the reference color. The color evaluation system may be used to promote common recognition or mutual understanding of colors among people with blood types C, P, D, T, and A.

[0017] [System Configuration] The color evaluation system is composed of one or more computers. When multiple computers are used, these computers are connected via a communication network such as the Internet or an intranet to logically construct a single color evaluation system.

[0018] A computer constituting a color evaluation system generally includes hardware devices such as a processor, memory, a communication interface, an input device, and an output device. Examples of the processor include a CPU and a GPU. The memory may be configured using a flash memory, a hard disk, etc. The communication interface may be configured using a network card or a wireless communication module. Examples of the input device include a keyboard, a pointing device, a touch panel, a microphone, a sensor, and a camera. Examples of the output device include a monitor, a touch panel, a head-mounted display (HMD), and a speaker.

[0019] A color evaluation program for causing a computer to function as a color evaluation system includes program code for implementing each functional module of the color evaluation system. This color evaluation program may be provided by being non-temporarily recorded on a tangible recording medium, such as a CD-ROM, a DVD-ROM, or a semiconductor memory. Alternatively, the color evaluation program may be provided via a communication network as a data signal superimposed on a carrier wave. The provided color evaluation program is recorded in, for example, a memory.

[0020] The configuration of an example color evaluation system 10 will be described with reference to Fig. 1. Fig. 1 is a diagram showing the functional configuration of the color evaluation system 10.

[0021] The color evaluation system 10 includes a processor 101 and a memory 102. In one example, the processor 101 functions as an acquisition unit 11, a calculation unit 12, a comparison unit 13, an evaluation unit 14, and a generation unit 15. The memory 102 pre-stores a color spectrum, which is color spectral data, a subject model that indicates color perception by a subject, and a reference model that indicates color perception by a reference color vision person. The memory 102 may store one or more color spectra, one or more subject models, and one or more reference models. Both the subject model and the reference model are color vision models that represent the human color vision system using algorithms or data. The color vision system is composed of the eyeball, the optic nerve, the visual cortex, etc.

[0022] A subject refers to a person assumed to evaluate colors, and a reference color vision subject refers to a person assumed to be compared with the subject. The subject may be a person with normal color vision, or a person with a specific type of color vision deficiency, such as P-type or D-type. For example, when a specific color vision deficiency subject is selected as the subject, a person with normal color vision is assumed as the reference color vision, and when a person with normal color vision is selected as the subject, a person with a specific type of color vision deficiency is assumed as the reference color vision. Reference models may be prepared for both normal color vision subjects and color vision deficiencies. When a color vision deficiency subject is assumed as the reference color vision subject, reference models may be prepared for each type of color vision, for example, a P-type reference model, a D-type reference model, a T-type reference model, and an A-type reference model. Furthermore, reference models may be prepared that take into account differences in the severity or severity of color vision deficiency.

[0023] The acquisition unit 11 is a functional module that acquires a reference spectrum, a subject model, and a reference model. The calculation unit 12 is a functional module that calculates a subject response indicating the subject's perception of the reference color based on the reference spectrum and the subject model, and calculates a reference response indicating the reference color's perception by a reference color vision person based on the reference spectrum and the reference model. The comparison unit 13 is a functional module that calculates the difference between the subject response and the reference response as a response difference. The evaluation unit 14 is a functional module that evaluates the reference color based on the response difference. The generation unit 15 is a functional module that generates an adjusted spectrum, which is a spectrum of a color having a smaller response difference than the reference spectrum, based on the reference spectrum and the response difference. A color having an adjusted spectrum is a color that is perceived in the same way by both the subject and the reference color vision person, i.e., a color that is perceived in the same way by both people with normal color vision and people with color deficiency.

[0024] [System Operation] A color evaluation method executed by the color evaluation system 10 will be described with reference to Fig. 2. Fig. 2 is a flowchart showing an example of the operation of the color evaluation system 10 as a processing flow S1.

[0025] In step S11, the acquisition unit 11 acquires a reference spectrum, a subject model, and a reference model. In one example, a user of the color evaluation system 10 inputs a reference color, the subject's color vision type, and the color vision type of a reference color vision holder. The acquisition unit 11 accepts the input and reads out from the memory 102 a reference spectrum, which is the spectrum of the reference color, a subject model corresponding to the subject's color vision type, and a reference model corresponding to the color vision type of the reference color vision holder. Alternatively, the acquisition unit 11 may directly accept input of the reference spectrum, the subject model, and the reference model. Alternatively, the acquisition unit 11 may receive the reference spectrum, the subject model, and the reference model from another computer.

[0026] In one example, the reference spectrum is the luminance (cd / m) at each wavelength (nm) in the visible light range. ２ The reference spectrum may be expressed as a spectral function that indicates the relationship between wavelength and intensity.

[0027] In one example, both the subject model and the reference model show the sensitivity characteristics of L cones, M cones, and S cones. Sensitivity characteristics are also referred to as spectral characteristics. FIG. 3 is a graph showing examples of the sensitivity characteristics of each cone for a person with normal color vision and a person with color deficiency. The horizontal and vertical axes of the graph represent wavelength (nm) and relative sensitivity, respectively. The color-blind person shown in FIG. 3 corresponds to P-type acuity. Compared to a person with normal color vision (C-type), the sensitivity characteristics of the M cones and the L cones overlap to a greater extent. These differences in sensitivity characteristics result in differences in color recognition or discrimination. The color vision model shown in FIG. 3 may be expressed by a sensitivity function showing the relationship between wavelength and relative sensitivity. This sensitivity function is prepared for each of the L cones, M cones, and S cones. In the present disclosure, such sensitivity functions are also referred to as "cone sensitivity functions." The subject model includes sensitivity functions showing the sensitivity characteristics of the subject's L cones, M cones, and S cones. The reference model includes sensitivity functions that indicate the sensitivity characteristics of the L-, M-, and S-cones of a reference color vision subject. These color vision models may be generated based on measurements obtained by measuring the sensitivities of the L-, M-, and S-cones of an individual, or may be generated based on representative values ​​for C-, P-, and D-type acuity.

[0028] Returning to FIG. 2, in step S12, the calculation unit 12 calculates a subject response that indicates the subject's perception of the reference color based on the reference spectrum and the subject model.

[0029] In one example, the calculation unit 12 calculates a subject response indicating responses from each of the subject's L cones, M cones, and S cones. In this example, the subject response defined by the response α from the L cone, the response β from the M cone, and the response γ from the S cone is expressed as (α, β, γ). For each of the subject's L cones, M cones, and S cones, the calculation unit 12 calculates the response from the cone that senses the reference color as follows: The calculation unit 12 calculates the product of the relative sensitivity of the cone and the luminance shown in the reference spectrum at each wavelength in the visible light range. This product can be said to indicate the degree of excitation. The calculation unit 12 obtains the sum of the products at each wavelength as the response from the cone.

[0030] Let the wavelength be represented by x, and let the sensitivity functions of the L cone, M cone, and S cone be f Ｌ (x), f Ｍ (x), f Ｓ Let the spectral function of the reference color be denoted by (x) and the spectral function of the reference color be denoted by g(x). In this case, the responses α, β, and γ can be expressed as in equations (1) to (3), respectively.

[0031] α=∫f Ｌ (x)g(x)dx…(1) β=∫f Ｍ (x)g(x)dx…(2) γ=∫f Ｓ (x)g(x)dx…(3)

[0032] That is, the calculation unit 12 calculates the integral of the product of the sensitivity function and the spectral function for each cone of the subject as the subject response (α, β, γ).

[0033] In step S13, the calculation unit 12 calculates a reference response indicating the recognition of the reference color by the reference color vision subject based on the reference spectrum and the reference model. In one example, the calculation unit 12 calculates a reference response indicating the response from each of the L cones, M cones, and S cones of the reference color vision subject. In this example, the reference response defined by the response α' from the L cone, the response β' from the M cone, and the response γ' from the S cone is expressed as (α', β', γ'). As in the case of calculating the subject response, the calculation unit 12 calculates the response from each of the L cones, M cones, and S cones of the reference color vision subject that sense the reference color using the above equations (1) to (3) to obtain the reference response (α', β', γ'). That is, the calculation unit 12 calculates the integral of the product of the sensitivity function and the spectral function for each cone of the reference color vision subject as the reference response (α', β', γ').

[0034] In step S14, the comparison unit 13 calculates the difference between the subject response and the reference response as a response difference. If the subject response and the reference response indicate responses from the L cone, the M cone, and the S cone, the comparison unit 13 calculates the difference between the subject response and the reference response for each of the L cone, the M cone, and the S cone, and calculates the response difference based on a combination of the difference in the L cone, the difference in the M cone, and the difference in the S cone. For example, the comparison unit 13 obtains the response difference (α-α', β-β', γ-γ'). Alternatively, the comparison unit 13 may calculate the response difference as a ratio based on the reference response, in which case the response difference can be expressed as {(α-α') / α', (β-β') / β', (γ-γ') / γ'}.

[0035] In step S15, the evaluation unit 14 evaluates the reference color based on the response difference. For example, if the response difference is equal to or greater than a predetermined threshold Th, the evaluation unit 14 determines that the reference color is a color perceived differently by the subject and the reference color vision subject. On the other hand, if the response difference is less than the threshold Th, the evaluation unit 14 determines that the reference color is a color perceived in the same way by the subject and the reference color vision subject. The threshold Th is set so as to determine a color perceived in the same way by the subject and the reference color vision subject. The evaluation unit 14 outputs the determination result. The evaluation unit 14 may display the determination result on a display device, store the determination result in a predetermined storage device such as memory 102, or transmit the determination result to another computer system.

[0036] If the cone responses are used, the evaluation unit 14 determines the threshold Th for the L cones. Ｌ , the threshold Th for M cones Ｍ , and Th for S-cones Ｓ A combination of the above may be used as the threshold Th. In this case, the evaluation unit 14 compares the difference for each of the L cones, M cones, and S cones with the threshold for that cone. If the difference for at least one of the three types of cones is equal to or greater than the threshold, the evaluation unit 14 determines that the reference color is a color that is perceived differently by the subject and the reference color vision person. On the other hand, if the differences for all three types of cones are less than the threshold, the evaluation unit 14 determines that the reference color is a color that is perceived the same by the subject and the reference color vision person.

[0037] In step S16, the generation unit 15 determines whether to generate an adjusted spectrum. In one example, if the evaluation unit 14 determines that the reference color is a color that is perceived differently by the subject and the reference color vision person, the generation unit 15 determines to generate an adjusted spectrum (YES in step S16). In this case, the process proceeds to step S17. On the other hand, if the evaluation unit 14 determines that the reference color is a color that is perceived the same by the subject and the reference color vision person, the generation unit 15 determines not to generate an adjusted spectrum (NO in step S16). In this case, the process flow S1 ends without executing step S17.

[0038] In step S17, the generation unit 15 generates an adjusted spectrum, which is a spectrum of a color having a smaller response difference than the reference spectrum, based on the reference spectrum and the response difference. In one example, the generation unit 15 generates a candidate spectrum by modifying at least a portion of the reference spectrum. The generation unit 15 then calculates the above formulas (1) to (3) based on the spectral function of the candidate spectrum and the sensitivity functions of the subject's L cones, M cones, and S cones to calculate the subject responses (α, β, γ) corresponding to the candidate spectrum. The generation unit 15 also calculates the above formulas (1) to (3) based on the spectral function of the candidate spectrum and the sensitivity functions of the L cones, M cones, and S cones of the reference color vision subject to calculate the reference responses (α', β', γ') corresponding to the candidate spectrum. The generation unit 15 then calculates the response difference between the subject responses (α, β, γ) and the reference responses (α', β', γ'). The generator 15 repeatedly calculates the subject response (α, β, γ) and the reference response (α', β', γ') and calculates the response difference while changing at least a portion of the reference spectrum. The generator 15 then selects, as the adjustment spectrum, a candidate spectrum that has a response difference smaller than the response difference in the reference spectrum. For example, the generator 15 selects, as the adjustment spectrum, a candidate spectrum whose response difference is equal to or less than the threshold value Th. The adjustment spectrum selected based on the threshold value Th can be said to be a color spectrum whose subject response matches or approximates the reference response.

[0039] The generation unit 15 outputs the adjusted spectrum. The generation unit 15 may display the adjusted spectrum on a display device, store the adjusted spectrum in a predetermined storage device such as the memory 102, or transmit the adjusted spectrum to another computer system. Alternatively, the generation unit 15 may output the adjusted spectrum to a manufacturing device, which is a device or group of devices that manufactures a pigment. A pigment is a substance that imparts color to an object. The pigment may be a dye or a pigment. The manufacturing device may be a component of the color evaluation system 10 or may be provided external to the color evaluation system 10. The manufacturing device refers to the adjusted spectrum, selects one or more pigment materials from a plurality of pigment materials prepared in advance, and determines a mixing ratio for each of the selected pigment materials. The manufacturing device then mixes the selected one or more pigment materials according to the determined mixing ratio to manufacture the pigment. The manufacturing device may produce the pigment according to one or more pigment materials and mixing ratios selected by an operator. In either case, the manufacturing device manufactures the pigment based on the adjusted spectrum. This pigment has an adjusted spectrum and can contribute to color expression that takes color vision diversity into consideration.

[0040] [Modifications] The technology according to the present disclosure has been described in detail above based on various examples. However, the present disclosure is not limited to the above examples. The technology according to the present disclosure can be modified in various ways without departing from the spirit of the present disclosure.

[0041] (First Modification) In the above example, the subject model and the reference model include sensitivity functions of cones. As another example, both the subject model and the reference model may include sensitivity functions indicating the relationship between the color spectrum and electroencephalograms. In the present disclosure, such sensitivity functions are also referred to as "electroencephalogram sensitivity functions." The electroencephalogram sensitivity functions may be sensitivity functions indicating the relationship between the color spectrum and steady-state visual evoked potentials (SSVEPs) obtained by processing electroencephalograms using frequency analysis such as Fourier transform. The SSVEPs are expressed as power spectral densities obtained by Fourier transforming the frequency components of an observer's electroencephalogram signal when the observer is viewing periodically changing colors. The subject model is generated based on the subject's electroencephalograms, and the reference model is generated based on the electroencephalograms of a reference color vision person.

[0042] When the electroencephalogram sensitivity function is used, the calculation unit 12 inputs the reference spectrum into the sensitivity function of the subject to calculate a subject response based on the electroencephalogram of the subject. The calculation unit 12 also inputs the reference spectrum into the sensitivity function of a reference color vision person to calculate a reference response based on the electroencephalogram of the reference color vision person. The comparison unit 13 calculates the difference between these two responses as a response difference. When the electroencephalogram sensitivity function is used, as in the case where the cone sensitivity function is used, the evaluation unit 14 may evaluate the reference color based on the response difference, the generation unit 15 may generate an adjusted spectrum based on the reference spectrum and the response difference, and a manufacturing device may manufacture a pigment based on the adjusted spectrum.

[0043] (Second Modification) The sensitivity function of the electroencephalogram is a sensitivity function f that indicates the ratio of the magnitude of the SSVEP (second SSVEP) of the subject when the subject visually recognizes a change from a reference color to a predetermined different color to the magnitude of the SSVEP (first SSVEP) of the subject when the subject visually recognizes a change from a predetermined first gray color to a predetermined second gray color. Ｂ That is, f Ｂ= (magnitude of second SSVEP) / (magnitude of first SSVEP). The first gray and the second gray have different intensities. The different color may be preset to match the reference color, and may be, for example, a color located symmetrically to the reference color in a color coordinate system with the difference in cone response as its axis. This coordinate system is also called the MB-DKL space. Alternatively, the different color may be a color that is difficult for the subject to distinguish from the reference color, or a color located on the same confusion color line as the reference color. The sensitivity function f Ｂ The ratio obtained as a response by the above equation is a value greater than 0. The SSVEP corresponds to the frequency components of the electroencephalogram of a subject who visually recognizes a periodic change in color. The electroencephalogram is measured at one or more locations, for example, four or more locations, corresponding to the location of the cerebral visual cortex at the back of the head. If the subject cannot sense the difference between the reference color and another color, the electroencephalogram components become small, and the sensitivity function f Ｂ The response obtained from the sensitivity function f Ｂ The response obtained from

[0044] The subject model is a sensitivity function f Ｂ The reference model includes a sensitivity function f Ｂ When these sensitivity functions are used, the acquisition unit acquires the first SSVEP and the second SSVEP of the subject who viewed the reference color, and the first SSVEP and the second SSVEP of the reference color vision person who viewed the reference color. The acquisition unit also acquires a subject model and a reference model. The calculation unit calculates the sensitivity function f Ｂ Similarly, the calculation unit calculates the ratio obtained by substituting the first SSVEP and the second SSVEP of the subject into the sensitivity function f Ｂ The ratio obtained by substituting the first SSVEP and the second SSVEP of the reference color vision person into is calculated as the reference response. The comparison unit calculates the difference between the subject response and the reference response as the response difference. ＢEven when the above method is used, the evaluation unit may evaluate the reference color based on the response difference, the generation unit may generate an adjusted spectrum based on the reference spectrum and the response difference, and the manufacturing device may manufacture the dye based on the adjusted spectrum.

[0045] (Third Variant) As another example of electroencephalogram-based processing, both the subject model and the reference model may include a database showing the relationship between a sample color and the SSVEP of a subject who viewed the sample color for multiple sample colors. Each record in the database includes a sample color and the SSVEP of the subject who viewed the sample color. This database may be prepared for each subject, and therefore may be prepared separately for the subject and the reference color vision person. Alternatively, the database may be a common database prepared by collecting correspondences for multiple sample colors from multiple subjects and statistically processing the correspondences for each sample color. The common database is prepared by calculating statistics (e.g., averages) of the SSVEPs of multiple subjects for each of the multiple sample colors and generating correspondences between the sample colors and the statistical values. The common database is used as both the subject model and the reference model.

[0046] When a database is used, the acquisition unit acquires the SSVEP of the subject who viewed the reference color and the SSVEP of the reference color vision subject who viewed the reference color. The acquisition unit also acquires a subject model and a reference model. Accessing the database is an example of acquiring the subject model and the reference model. The calculation unit references the database corresponding to the subject and identifies a sample color corresponding to the acquired SSVEP of the subject as the subject response. The calculation unit may select two or more SSVEPs close to the acquired SSVEP from the database, linearly combine the two or more SSVEPs to generate a single SSVEP, and identify a sample color corresponding to the generated SSVEP as the subject response. The calculation unit references the database corresponding to the reference color vision subject and identifies a sample color corresponding to the acquired SSVEP of the reference color vision subject as the reference response. As with the subject response, the calculation unit may perform linear combination to identify the reference response. The comparison unit calculates the distance between the sample color indicated as the subject response and the sample color indicated as the reference response in a color space (e.g., an HSV color space) as a response difference. Even when a database indicating the correspondence between sample colors and SSVEPs is used, the evaluation unit may evaluate the reference color based on the response difference, the generation unit may generate an adjusted spectrum based on the reference spectrum and the response difference, and the manufacturing device may manufacture a pigment based on the adjusted spectrum.

[0047] (Fourth Variation) Both the subject model and the reference model may include a trained model that accepts input SSVEPs and estimates sample colors. This trained model is generated by machine learning, a method of autonomously discovering laws or rules by iteratively learning based on given information. This machine learning uses training data that indicates the correspondence between sample colors and the SSVEPs of subjects who view the sample colors, such as the data stored in the database described above. This machine learning uses the sample colors as ground truth. The trained model may be generated by a learning unit of the color evaluation system. Alternatively, a trained model generated by a computer system different from the color evaluation system may be implanted into the color evaluation system. Since the trained model estimates sample colors from SSVEPs, it can be said to indicate the relationship between the sample colors and the steady-state visual evoked potentials of the subjects who view the sample colors, similar to the database described above. A trained model may be prepared for each subject, and therefore may be prepared separately for the subject and the reference color vision person. Alternatively, the trained model may be generated to be used commonly by the subject and the reference color vision person.

[0048] When a trained model is used, the acquisition unit acquires the SSVEP of the subject who viewed the reference color and the SSVEP of the reference color vision subject who viewed the reference color. The acquisition unit also acquires a subject model and a reference model. Accessing the trained model is an example of acquiring the subject model and the reference model. The calculation unit inputs the acquired SSVEP of the subject into a trained model corresponding to the subject and identifies a sample color output from the trained model as the subject response. The calculation unit may select two or more SSVEPs close to the acquired SSVEP from the database, linearly combine the two or more SSVEPs to generate one SSVEP, and input the generated SSVEP into the trained model. The calculation unit inputs the acquired SSVEP of the reference color vision subject into a trained model corresponding to the reference color vision subject and identifies a sample color output from the trained model as the reference response. As in the case of the subject response, the calculation unit may perform linear combination. The comparison unit calculates a response difference as a distance between a sample color indicated by the subject response and a sample color indicated by the reference response in a color space (e.g., an HSV color space). Even when a trained model that accepts an input of an SSVEP and outputs a sample color is used, the evaluation unit may evaluate a reference color based on the response difference, the generation unit may generate an adjusted spectrum based on the reference spectrum and the response difference, and the manufacturing device may manufacture a pigment based on the adjusted spectrum.

[0049] FIG. 4 is a flowchart showing an example of the operation of the color evaluation system corresponding to the second to fourth modified examples as a processing flow S2.

[0050] In step S21, the acquisition unit acquires the SSVEP of the subject who viewed the reference color, the SSVEP of the reference color vision subject who viewed the reference color, a subject model, and a reference model. The SSVEP of the subject who viewed the reference color and the SSVEP of the reference color vision subject who viewed the reference color are both examples of reference color information. In step S22, the calculation unit calculates a subject response indicating the subject's recognition of the reference color based on the subject's SSVEP and the subject model. In step S23, the calculation unit calculates a reference response indicating the reference color perception by the reference color vision subject based on the SSVEP of the reference color vision subject and the reference model. The processes of steps S24 to S27 are similar to the processes of steps S14 to S17 in the processing flow S1.

[0051] (Fifth Variation) As an example other than cones and electroencephalograms, it is also possible to construct a sensitivity function that reflects changes in pupil size. Pupil size changes depending on how much a subject's attention is attracted to a certain color. If the subject cannot sense the difference between a certain color Cx and another color Cd, it is predicted that the pupil size will not change much (i.e., the amount of change in pupil size will be less than a predetermined threshold). On the other hand, if the subject can sense the difference between a color Cx and another color Cd, it is predicted that the pupil size will change (i.e., the amount of change in pupil size will be equal to or greater than a predetermined threshold).

[0052] The pupil sensitivity function may be a sensitivity function that indicates the relationship between a color spectrum and a change in pupil size. When the pupil sensitivity function is used, the calculation unit 12 inputs a reference spectrum into the subject's sensitivity function to calculate a subject response based on a change in pupil size of the subject. The calculation unit 12 also inputs the reference spectrum into the sensitivity function of a reference color vision person to calculate a reference response based on a change in pupil size of the reference color vision person. The comparison unit 13 calculates the difference between these two responses as a response difference. When the pupil sensitivity function is used, as in the case where the cone sensitivity function is used, the evaluation unit 14 may evaluate the reference color based on the response difference, the generation unit 15 may generate an adjusted spectrum based on the reference spectrum and the response difference, and a manufacturing device may manufacture a pigment based on the adjusted spectrum.

[0053] (Sixth Variation) As yet another example, it is possible to construct a sensitivity function that reflects changes in cerebral blood flow. Cerebral blood flow changes depending on how much a subject's attention is attracted to a certain color. If the subject cannot sense the difference between a certain color Cx and another color Cd, it is predicted that the cerebral blood flow will not change much (i.e., the amount of change in cerebral blood flow will be less than a predetermined threshold). On the other hand, if the subject can sense the difference between the color Cx and another color Cd, it is predicted that the cerebral blood flow will change (i.e., the amount of change in cerebral blood flow will be equal to or greater than a predetermined threshold).

[0054] The cerebral blood flow sensitivity function may be a sensitivity function that indicates the relationship between a color spectrum and a change in cerebral blood flow. When the cerebral blood flow sensitivity function is used, the calculation unit 12 inputs a reference spectrum into the subject's sensitivity function to calculate a subject response based on a change in cerebral blood flow of the subject. The calculation unit 12 also inputs the reference spectrum into the sensitivity function of a reference color vision person to calculate a reference response based on a change in cerebral blood flow of the reference color vision person. The comparison unit 13 calculates the difference between these two responses as a response difference. When the cerebral blood flow sensitivity function is used, as in the case where the cone sensitivity function is used, the evaluation unit 14 may evaluate the reference color based on the response difference, the generation unit 15 may generate an adjusted spectrum based on the reference spectrum and the response difference, and a manufacturing device may manufacture a pigment based on the adjusted spectrum.

[0055] (Seventh Variation) As yet another example, a sensitivity function that reflects changes in amylase concentration can be constructed. The amylase concentration changes depending on how much a subject's attention is attracted to a certain color. If the subject cannot sense the difference between a certain color Cx and another color Cd, it is predicted that the amylase concentration will not change significantly (i.e., the amount of change in amylase concentration will be less than a predetermined threshold). On the other hand, if the subject can sense the difference between color Cx and another color Cd, it is predicted that the amylase concentration will change (i.e., the amount of change in amylase concentration will be greater than or equal to a predetermined threshold).

[0056] The sensitivity function for amylase concentration may be a sensitivity function that indicates the relationship between the color spectrum and the change in amylase concentration. When the sensitivity function for amylase concentration is used, the calculation unit 12 inputs the reference spectrum into the sensitivity function for the subject and calculates the subject's response based on the change in amylase concentration of the subject. The calculation unit 12 also inputs the reference spectrum into the sensitivity function for the reference color vision person and calculates the reference response based on the change in amylase concentration of the reference color vision person. The comparison unit 13 calculates the difference between these two responses as the response difference. When the sensitivity function for amylase concentration is used, as in the case where the sensitivity function for cones is used, the evaluation unit 14 may evaluate the reference color based on the response difference, the generation unit 15 may generate an adjusted spectrum based on the reference spectrum and the response difference, and the manufacturing device may manufacture a pigment based on the adjusted spectrum.

[0057] (Eighth Variation) As yet another example, it is possible to construct a sensitivity function that reflects changes in gaze. The gaze changes depending on how much a subject's attention is attracted to a certain color. If the subject cannot sense the difference between a certain color Cx and another color Cd, it is predicted that the gaze will not change much (i.e., the amount of change in gaze will be less than a predetermined threshold). On the other hand, if the subject can sense the difference between a color Cx and another color Cd, it is predicted that the gaze will change (i.e., the amount of change in gaze will be equal to or greater than a predetermined threshold).

[0058] The gaze sensitivity function may be a sensitivity function that indicates the relationship between the color spectrum and the amount of change in the gaze. When the gaze sensitivity function is used, the calculation unit 12 inputs the reference spectrum into the subject's sensitivity function to calculate a subject response based on the amount of change in the subject's gaze. The calculation unit 12 also inputs the reference spectrum into the sensitivity function of a reference color vision person to calculate a reference response based on the amount of change in the reference color vision person's gaze. The comparison unit 13 calculates the difference between these two responses as a response difference. When the gaze sensitivity function is used, as in the case where the cone sensitivity function is used, the evaluation unit 14 may evaluate the reference color based on the response difference, the generation unit 15 may generate an adjusted spectrum based on the reference spectrum and the response difference, and the manufacturing device may manufacture a pigment based on the adjusted spectrum.

[0059] (Ninth Variation) As yet another example, it is possible to construct a sensitivity function that reflects changes in skin potential. The skin potential changes depending on how much a subject's attention is attracted to a certain color. If the subject cannot sense the difference between a certain color Cx and another color Cd, it is predicted that the skin potential will not change much (i.e., the amount of change in the skin potential will be less than a predetermined threshold). On the other hand, if the subject can sense the difference between the color Cx and another color Cd, it is predicted that the skin potential will change (i.e., the amount of change in the skin potential will be equal to or greater than a predetermined threshold).

[0060] The skin potential sensitivity function may be a sensitivity function that indicates the relationship between the color spectrum and the amount of change in skin potential. When the skin potential sensitivity function is used, the calculation unit 12 inputs the reference spectrum into the subject's sensitivity function to calculate a subject response based on the amount of change in the subject's skin potential. The calculation unit 12 also inputs the reference spectrum into the sensitivity function of a reference color vision person to calculate a reference response based on the amount of change in the reference color vision person's skin potential. The comparison unit 13 calculates the difference between these two responses as a response difference. When the skin potential sensitivity function is used, as in the case where the cone sensitivity function is used, the evaluation unit 14 may evaluate the reference color based on the response difference, the generation unit 15 may generate an adjusted spectrum based on the reference spectrum and the response difference, and the manufacturing device may manufacture a pigment based on the adjusted spectrum.

[0061] The color evaluation system may not perform at least one of evaluation of the reference color based on the response difference and generation of the adjustment spectrum, and therefore may not include a functional module corresponding to at least one of the evaluation unit 14 and the generation unit 15.

[0062] The processing steps of the method executed by at least one processor are not limited to the above examples. For example, some of the above steps may be omitted, or the steps may be executed in a different order. Furthermore, any two or more of the above steps may be combined, or some of the steps may be modified or deleted. Alternatively, other steps may be executed in addition to the above steps.

[0063] In the present disclosure, when comparing the magnitude of two numerical values, either of the two criteria "greater than or equal to" and "greater than" may be used, or either of the two criteria "less than or equal to" and "less than" may be used.

[0064] In the present disclosure, the expression "at least one processor executes a first process, executes a second process, ... executes an nth process" or an expression corresponding thereto indicates a concept including a case where the entity executing the n processes from the first process to the nth process, i.e., the processor, changes midway through. In other words, this expression indicates a concept including both a case where all n processes are executed by the same processor and a case where the processor changes among the n processes according to an arbitrary policy.

[0065] [Supplementary Notes] As can be seen from the various examples above, the present disclosure includes the following aspects. (Supplementary Note 1) A color evaluation system comprising: an acquisition unit that acquires reference color information regarding a reference color, a subject model that indicates the perception of color by a subject, and a reference model that indicates the perception of color by a reference color vision person; a calculation unit that calculates a subject response that indicates the perception of the reference color by the subject based on the reference color information and the subject model, and calculates a reference response that indicates the perception of the reference color by the reference color vision person based on the reference color information and the reference model; and a comparison unit that calculates a response difference, which is a difference between the subject response and the reference response. (Supplementary Note 2) The color evaluation system according to Supplementary Note 1, further comprising an evaluation unit that evaluates the reference color based on the response difference. (Supplementary Note 3) The color evaluation system according to Supplementary Note 1 or 2, further comprising a generation unit that generates, based on the response difference and a reference spectrum that is the spectrum of the reference color, an adjusted spectrum that is a spectrum of a color whose response difference is smaller than that of the reference spectrum. (Supplementary Note 4) The color evaluation system according to any one of Supplementary Notes 1 to 3, wherein the reference color information is a reference spectrum that is a spectrum of the reference color, and the calculation unit calculates the subject response based on the reference spectrum and the subject model, and calculates the reference response based on the reference spectrum and the reference model. (Supplementary Note 5) A color evaluation system as described in Supplementary Note 4, wherein the subject model includes sensitivity functions indicating the sensitivity characteristics of each of the subject's L cones, M cones, and S cones; the reference model includes sensitivity functions indicating the sensitivity characteristics of each of the L cones, M cones, and S cones of the reference color vision person; the calculation unit calculates the subject responses indicating responses from each of the subject's L cones, M cones, and S cones based on the reference spectrum and the sensitivity function of the subject; calculates the reference responses indicating responses from each of the reference color vision person's L cones, M cones, and S cones based on the reference spectrum and the sensitivity function of the reference color vision person; and the comparison unit calculates the difference between the subject responses and the reference responses for each of the L cones, M cones, and S cones; and calculates the response difference based on a combination of the difference in the L cones, the difference in the M cones, and the difference in the S cones.(Supplementary Note 6) The color evaluation system according to Supplementary Note 4, wherein the subject model includes a sensitivity function indicating a relationship between a color spectrum and the electroencephalogram of the subject, the reference model includes a sensitivity function indicating a relationship between a color spectrum and the electroencephalogram of the reference color vision subject, and the calculation unit calculates the subject response based on the electroencephalogram of the subject based on the reference spectrum and the sensitivity function of the subject, and calculates the reference response based on the electroencephalogram of the reference color vision subject based on the reference spectrum and the sensitivity function of the reference color vision subject. (Supplementary Note 7) The color evaluation system according to any one of Supplementary Notes 1 to 3, wherein the acquisition unit acquires, as the reference color information, a steady-state visual evoked potential of the subject who viewed the reference color and a steady-state visual evoked potential of the reference color vision subject who viewed the reference color, and (Supplementary Note 8) The color evaluation system described in Supplementary Note 7, wherein the subject model includes a sensitivity function indicating a ratio of the magnitude of the steady-state visual evoked potential of the subject when the subject views a change from the reference color to a predetermined different color to the magnitude of the steady-state visual evoked potential of the subject when the subject views a change from a predetermined first gray to a predetermined second gray; the reference model includes the sensitivity function indicating a ratio of the magnitude of the steady-state visual evoked potential of the reference color vision person when the reference color vision person views a change from the reference color to the different color to the magnitude of the steady-state visual evoked potential of the reference color vision person when the reference color vision person views a change from the first gray to the second gray; and the calculation unit calculates the proportion of the subject as the subject response based on the steady-state visual evoked potential of the subject and the sensitivity function of the subject, and calculates the proportion of the reference color vision person as the reference response based on the steady-state visual evoked potential of the reference color vision person and the sensitivity function of the reference color vision person.(Supplementary Note 9) The color evaluation system according to Supplementary Note 7, wherein the subject model indicates a relationship between a sample color and a steady-state visual evoked potential of the subject who viewed the sample color, the reference model indicates a relationship between the sample color and a steady-state visual evoked potential of the reference color vision person who viewed the sample color, and the calculation unit uses the subject model to calculate, as the subject response, the sample color corresponding to the steady-state visual evoked potential of the subject acquired by the acquisition unit, and uses the reference model to calculate, as the reference response, the sample color corresponding to the steady-state visual evoked potential of the reference color vision person acquired by the acquisition unit. (Supplementary Note 10) The color evaluation system according to Supplementary Note 9, wherein the subject model includes a database indicating the relationship between the sample color and the steady-state visual evoked potential of the subject, and the reference model includes a database indicating the relationship between the sample color and the steady-state visual evoked potential of the reference color vision person. (Supplementary Note 11) The color evaluation system of Supplementary Note 9, wherein the subject model includes a trained model that receives input of the steady-state visual evoked potential of the subject and outputs the sample color, and the reference model includes a trained model that receives input of the steady-state visual evoked potential of the reference color vision subject and outputs the sample color. (Supplementary Note 12) The color evaluation system of Supplementary Note 4, wherein the subject model includes a sensitivity function that indicates a relationship between a color spectrum and an amount of change in pupil size of the subject, and the reference model includes a sensitivity function that indicates a relationship between the color spectrum and an amount of change in pupil size of the reference color vision subject.(Appendix 13) A color evaluation system as described in Appendix 4, wherein the subject model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in cerebral blood flow of the subject, the reference model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in cerebral blood flow of the reference color vision person, and the calculation unit calculates the subject response based on the amount of change in cerebral blood flow of the subject based on the reference spectrum and the sensitivity function of the subject, and calculates the reference response based on the amount of change in cerebral blood flow of the reference color vision person based on the reference spectrum and the sensitivity function of the reference color vision person. (Appendix 14) A color evaluation system as described in Appendix 4, wherein the subject model includes a sensitivity function indicating the relationship between the color spectrum and the change in amylase concentration of the subject, the reference model includes a sensitivity function indicating the relationship between the color spectrum and the change in amylase concentration of the reference color vision person, and the calculation unit calculates the subject response based on the change in amylase concentration of the subject based on the standard spectrum and the sensitivity function of the subject, and calculates the reference response based on the change in amylase concentration of the reference color vision person based on the standard spectrum and the sensitivity function of the reference color vision person. (Appendix 15) A color evaluation system as described in Appendix 4, wherein the subject model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in the gaze of the subject, the reference model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in the gaze of the reference color vision person, and the calculation unit calculates the subject response based on the amount of change in the gaze of the subject based on the reference spectrum and the sensitivity function of the subject, and calculates the reference response based on the amount of change in the gaze of the reference color vision person based on the reference spectrum and the sensitivity function of the reference color vision person.(Appendix 16) A color evaluation system as described in Appendix 4, wherein the subject model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in the skin potential of the subject, the reference model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in the skin potential of the reference color vision person, and the calculation unit calculates the subject response based on the amount of change in the skin potential of the subject based on the standard spectrum and the sensitivity function of the subject, and calculates the reference response based on the amount of change in the skin potential of the reference color vision person based on the standard spectrum and the sensitivity function of the reference color vision person. (Supplementary Note 17) A color evaluation method executed by a color evaluation system having at least one processor, comprising the steps of: acquiring reference color information regarding a reference color, a subject model indicating the perception of the color by the subject, and a reference model indicating the perception of the color by a reference color vision person; calculating a subject response indicating the perception of the reference color by the subject based on the reference color information and the subject model, and calculating a reference response indicating the perception of the reference color by the reference color vision person based on the reference color information and the reference model; and calculating the difference between the subject response and the reference response as a response difference. (Supplementary Note 18) A method for manufacturing a pigment, comprising the steps of: acquiring reference color information regarding a reference color, a subject model indicating the perception of the color by the subject, and a reference model indicating the perception of the color by a reference color vision person; calculating a subject response indicating the perception of the reference color by the subject based on the reference color information and the subject model, and calculating a reference response indicating the perception of the reference color by the reference color vision person based on the reference color information and the reference model; calculating the difference between the subject response and the reference response as a response difference; generating an adjusted spectrum, which is the spectrum of a color whose response difference is smaller than that of the reference spectrum, based on a reference spectrum, which is the spectrum of the reference color, and the response difference; and manufacturing a pigment based on the adjusted spectrum.(Supplementary Note 19) A color evaluation program that causes a computer to execute the following steps: acquiring reference color information regarding a reference color, a subject model indicating the subject's perception of the color, and a reference model indicating the reference color perception by a reference color vision person; calculating a subject response indicating the subject's perception of the reference color based on the reference color information and the subject model, and calculating a reference response indicating the reference color perception by the reference color vision person based on the reference color information and the reference model; and calculating the difference between the subject response and the reference response as a response difference.

[0066] According to Supplements 1, 17, and 19, the subject's perception of the reference color is calculated as the subject response, the reference color perception of the reference color by the reference color vision subject is calculated as the reference response, and the difference between these two responses is calculated as the response difference. This response difference quantitatively indicates the difference in perception of the reference color between the subject and the reference color vision subject. Therefore, using this response difference makes it possible to quantitatively evaluate colors (reference colors) from the perspective of color vision. In one example, this system enables people who, due to color blindness, feel that it is difficult to empathize with or share in color perception with others to enjoy colors together. It also makes it possible to develop colors that appear similar to those seen by color blind people and those with normal color vision. This provides an indicator for developing color materials such as dyes and paints, or products that utilize such color materials (e.g., apparel products, writing implements). Ultimately, it becomes possible to create a world in which color blind people and those with normal color vision can enjoy products while empathizing with each other's colors.

[0067] According to Supplementary Note 2, since the color is automatically evaluated based on the response difference, the user can easily know how the color is evaluated from the viewpoint of human color vision.

[0068] According to Supplementary Note 3, an adjusted spectrum having a smaller response difference than the reference spectrum is generated. By using this adjusted spectrum, it is possible to provide colors taking into account color vision variability. For example, it is possible to generate and provide colors that are perceived the same by people with normal color vision and people with color deficiency.

[0069] According to Supplementary Note 4, the subject's perception of the reference color is calculated as the subject response, the reference color perception of the reference color by the reference color vision subject is calculated as the reference response, and the difference between these two responses is calculated as the response difference. This response difference quantitatively indicates the difference in perception of the reference color between the subject and the reference color vision subject. Therefore, by using this response difference, it is possible to quantitatively evaluate colors (reference colors) from the perspective of color vision.

[0070] According to Supplementary Note 5, since a subject model and a reference model that mimic the actual human color vision system are used, the subject response and the reference response can be calculated more accurately, and therefore a more accurate response difference can be obtained.

[0071] According to Supplementary Note 6, since a subject model and a reference model that mimic actual human electroencephalograms are used, the subject response and the reference response can be calculated more accurately, and therefore a more accurate response difference can be obtained.

[0072] According to Supplementary Note 7, the subject response and the reference response are calculated based on the visual response of the human brain. This method provides the subject response and the reference response that more directly indicate the human perception of the reference color, and is therefore expected to provide a response difference that more accurately represents the actual perception discrepancy.

[0073] According to Supplementary Note 8, sensitivity functions that take into account the visual response of the human brain are used as the subject model and the reference model, so that the subject response and the reference response can be calculated more accurately, and therefore a more accurate response difference can be obtained.

[0074] According to Supplementary Note 9, the relationship between colors (sample colors) and steady-state visual evoked potentials (SSVEPs) is used as a subject model and a reference model, taking into account visual responses in the human brain. This allows for more accurate calculation of the subject response and the reference response. Therefore, more accurate response differences can be obtained. Furthermore, since the subject response and the reference response are represented by colors (sample colors), these responses can be obtained in an easy-to-understand or intuitive manner.

[0075] According to Appendix 10, the relationship between colors (sample colors) and steady-state visual evoked potentials (SSVEPs) is prepared in a database, so that subject responses and reference responses can be easily obtained by simply referring to the database.

[0076] According to Appendix 11, the relationship between color (sample color) and steady-state visual evoked potential (SSVEP) is prepared by a trained model, so it is expected that highly accurate subject responses and reference responses can be obtained.

[0077] According to Supplementary Note 12, since a subject model and a reference model that mimic the actual size of a human pupil are used, the subject response and the reference response can be calculated more accurately, and therefore a more accurate response difference can be obtained.

[0078] According to Supplementary Note 13, since a subject model and a reference model that mimic actual human cerebral blood flow are used, the subject response and the reference response can be calculated more accurately, and therefore a more accurate response difference can be obtained.

[0079] According to Appendix 14, the subject and reference models that mimic actual human amylase concentrations are used, allowing for more accurate calculation of the subject and reference responses, and therefore more accurate response differences.

[0080] According to Supplementary Note 15, since a subject model and a reference model that mimic actual changes in human gaze are used, the subject response and the reference response can be calculated more accurately, and therefore a more accurate response difference can be obtained.

[0081] According to Supplementary Note 16, since a subject model and a reference model that mimic actual changes in human skin potential are used, the subject response and the reference response can be calculated more accurately, and therefore a more accurate response difference can be obtained.

[0082] According to Supplementary Note 18, the perception of a reference color by a subject is calculated as a subject response, the perception of the reference color by a reference color vision person is calculated as a reference response, and the difference between these two responses is calculated as a response difference. Then, an adjusted spectrum having a smaller response difference than the reference spectrum is generated, and a pigment is manufactured based on this adjusted spectrum. By using this pigment that is expected to be perceived in the same way by both the subject and the reference color vision person, it is possible to provide colors taking color vision diversity into consideration.

[0083] 10...color evaluation system, 11...acquisition unit, 12...calculation unit, 13...comparison unit, 14...evaluation unit, 15...generation unit

Claims

1. A color evaluation system comprising: an acquisition unit that acquires reference color information regarding a reference color, a subject model that indicates the subject's perception of the color, and a reference model that indicates the reference color perception by a reference color vision person; a calculation unit that calculates a subject response that indicates the subject's perception of the reference color based on the reference color information and the subject model, and calculates a reference response that indicates the reference color perception by the reference color vision person based on the reference color information and the reference model; and a comparison unit that calculates the difference between the subject response and the reference response as a response difference.

2. The color evaluation system according to claim 1, further comprising an evaluation unit that evaluates the reference color based on the response difference.

3. The color evaluation system according to claim 1, further comprising a generation unit that generates an adjusted spectrum, which is the spectrum of a color whose response difference is smaller than that of the reference spectrum, based on a reference spectrum that is the spectrum of the reference color and the response difference.

4. A color evaluation system according to any one of claims 1 to 3, wherein the reference color information is a reference spectrum that is a spectrum of the reference color, and the calculation unit calculates the subject response based on the reference spectrum and the subject model, and calculates the reference response based on the reference spectrum and the reference model.

5. The color evaluation system of claim 4, wherein the subject model includes sensitivity functions indicating the sensitivity characteristics of each of the subject's L cones, M cones, and S cones; the reference model includes sensitivity functions indicating the sensitivity characteristics of each of the L cones, M cones, and S cones of the reference color vision person; the calculation unit calculates the subject responses indicating responses from each of the subject's L cones, M cones, and S cones based on the reference spectrum and the sensitivity function of the subject; calculates the reference responses indicating responses from each of the reference color vision person's L cones, M cones, and S cones based on the reference spectrum and the sensitivity function of the reference color vision person; and the comparison unit calculates the difference between the subject responses and the reference responses for each of the L cones, M cones, and S cones; and calculates the response difference based on a combination of the difference in the L cones, the difference in the M cones, and the difference in the S cones.

6. A color evaluation system as described in claim 4, wherein the subject model includes a sensitivity function indicating the relationship between the color spectrum and the electroencephalogram of the subject, the reference model includes a sensitivity function indicating the relationship between the color spectrum and the electroencephalogram of the reference color vision person, and the calculation unit calculates the subject response based on the electroencephalogram of the subject based on the reference spectrum and the sensitivity function of the subject, and calculates the reference response based on the electroencephalogram of the reference color vision person based on the reference spectrum and the sensitivity function of the reference color vision person.

7. A color evaluation system as described in any one of claims 1 to 3, wherein the acquisition unit acquires the steady-state visual evoked potential of the subject who viewed the reference color and the steady-state visual evoked potential of a reference color vision person who viewed the reference color as the reference color information, and the calculation unit calculates the subject response based on the steady-state visual evoked potential of the subject and the subject model, and calculates the reference response based on the steady-state visual evoked potential of the reference color vision person and the reference model.

8. The color evaluation system of claim 7, wherein the subject model includes a sensitivity function indicating the ratio of the magnitude of the steady-state visual evoked potential of the subject when the subject views a change from the reference color to a predetermined different color to the magnitude of the steady-state visual evoked potential of the subject when the subject views a change from a predetermined first gray to a predetermined second gray; the reference model includes the sensitivity function indicating the ratio of the magnitude of the steady-state visual evoked potential of the reference color vision person when the reference color vision person views a change from the reference color to the different color to the magnitude of the steady-state visual evoked potential of the reference color vision person when the reference color vision person views a change from the first gray to the second gray; and the calculation unit calculates the proportion of the subject as the subject response based on the steady-state visual evoked potential of the subject and the sensitivity function of the subject, and calculates the proportion of the reference color vision person as the reference response based on the steady-state visual evoked potential of the reference color vision person and the sensitivity function of the reference color vision person.

9. A color evaluation system as described in claim 7, wherein the subject model indicates the relationship between a sample color and the steady-state visual evoked potential of the subject who viewed the sample color, the reference model indicates the relationship between the sample color and the steady-state visual evoked potential of the reference color vision person who viewed the sample color, and the calculation unit uses the subject model to calculate, as the subject response, the sample color corresponding to the steady-state visual evoked potential of the subject acquired by the acquisition unit, and uses the reference model to calculate, as the reference response, the sample color corresponding to the steady-state visual evoked potential of the reference color vision person acquired by the acquisition unit.

10. A color evaluation system as described in claim 9, wherein the subject model includes a database indicating the relationship between the sample colors and the steady-state visual evoked potentials of the subject, and the reference model includes a database indicating the relationship between the sample colors and the steady-state visual evoked potentials of the reference color vision person.

11. A color evaluation system as described in claim 9, wherein the subject model includes a trained model that accepts input of the steady-state visual evoked potential of the subject and outputs the sample color, and the reference model includes a trained model that accepts input of the steady-state visual evoked potential of the reference color vision person and outputs the sample color.

12. A color evaluation system as described in claim 4, wherein the subject model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in pupil size of the subject, the reference model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in pupil size of the reference color vision person, and the calculation unit calculates the subject response based on the amount of change in pupil size of the subject based on the reference spectrum and the sensitivity function of the subject, and calculates the reference response based on the amount of change in pupil size of the reference color vision person based on the reference spectrum and the sensitivity function of the reference color vision person.

13. A color evaluation system as described in claim 4, wherein the subject model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in cerebral blood flow of the subject, the reference model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in cerebral blood flow of the reference color vision person, and the calculation unit calculates the subject response based on the amount of change in cerebral blood flow of the subject based on the reference spectrum and the sensitivity function of the subject, and calculates the reference response based on the amount of change in cerebral blood flow of the reference color vision person based on the reference spectrum and the sensitivity function of the reference color vision person.

14. A color evaluation system as described in claim 4, wherein the subject model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in amylase concentration of the subject, the reference model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in amylase concentration of the reference color vision person, and the calculation unit calculates the subject response based on the amount of change in amylase concentration of the subject based on the standard spectrum and the sensitivity function of the subject, and calculates the reference response based on the amount of change in amylase concentration of the reference color vision person based on the standard spectrum and the sensitivity function of the reference color vision person.

15. A color evaluation system as described in claim 4, wherein the subject model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in the subject's gaze, the reference model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in the reference color vision subject's gaze, and the calculation unit calculates the subject response based on the amount of change in the subject's gaze based on the reference spectrum and the sensitivity function of the subject, and calculates the reference response based on the amount of change in the reference color vision subject's gaze based on the reference spectrum and the sensitivity function of the reference color vision subject.

16. A color evaluation system as described in claim 4, wherein the subject model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in the skin potential of the subject, the reference model includes a sensitivity function indicating the relationship between the color spectrum and the amount of change in the skin potential of the reference color vision person, and the calculation unit calculates the subject response based on the amount of change in the skin potential of the subject based on the standard spectrum and the sensitivity function of the subject, and calculates the reference response based on the amount of change in the skin potential of the reference color vision person based on the standard spectrum and the sensitivity function of the reference color vision person.

17. A color evaluation method executed by a color evaluation system having at least one processor, comprising the steps of: acquiring reference color information regarding a reference color, a subject model indicating the perception of the color by the subject, and a reference model indicating the perception of the color by a reference color vision person; calculating a subject response indicating the perception of the reference color by the subject based on the reference color information and the subject model, and calculating a reference response indicating the perception of the reference color by the reference color vision person based on the reference color information and the reference model; and calculating a difference between the subject response and the reference response as a response difference.

18. A method for manufacturing a pigment, comprising the steps of: obtaining reference color information regarding a reference color, a subject model indicating the perception of the color by the subject, and a reference model indicating the perception of the color by a reference color vision person; calculating a subject response indicating the perception of the reference color by the subject based on the reference color information and the subject model, and calculating a reference response indicating the perception of the reference color by the reference color vision person based on the reference color information and the reference model; calculating a difference between the subject response and the reference response as a response difference; generating an adjusted spectrum, which is the spectrum of a color whose response difference is smaller than that of the reference spectrum, based on a reference spectrum, which is the spectrum of the reference color, and the response difference; and manufacturing a pigment based on the adjusted spectrum.

19. A color evaluation program that causes a computer to execute the following steps: acquiring reference color information regarding a reference color, a subject model indicating the subject's perception of the color, and a reference model indicating the reference color perception by a reference color vision person; calculating a subject response indicating the subject's perception of the reference color based on the reference color information and the subject model, and calculating a reference response indicating the reference color perception by the reference color vision person based on the reference color information and the reference model; and calculating the difference between the subject response and the reference response as a response difference.

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