Evaluation device, evaluation method, and evaluation program

Abstract

An evaluation device according to an embodiment of the present invention comprises: an observed color estimation unit that estimates a first observed color and a second observed color when illuminated by first illuminating light for each of a first object color and a second object color identified by mutually different spectral characteristics; a color similarity calculation unit that calculates a color difference based on the first observed color and the second observed color; and an effect determination unit that uses the color difference as a basis for calculating an evaluation value pertaining to metamerism when using the first illuminating light, the first object color, and the second object color.

Description

Evaluation device, evaluation method, and evaluation program

[0001] The embodiments relate to an evaluation device, an evaluation method, and an evaluation program.

[0002] It is generally known that two objects that appear to have different colors when illuminated with a certain type of illumination can, under the right conditions, appear to have the same color when illuminated with a different type of illumination. This phenomenon is called metamerism. By intentionally inducing metamerism by changing the illumination, it is possible to create effects such as changing or erasing patterns on objects that are composed of multiple colors.

[0003] M. Tsuchida, K. Hiramatsu, K. Kashino, “Designing Spectral Power Distribution of Illumination with Color Chart to Enhance Color Saturation,” in Proc. IS&T 24th Color and Imaging conference (CIC24), pp. 278-282, 2016. D. Miyazaki, I. Nakane, R. Furukawa, and S. Hiura, “Simultaneous Optimization of Illuminant and Object Colors for Metamerism,” Research Report Computer Vision and Image Media (CVIM), vol. 2016-CVIM-204, no. 13, pp. 1-8, 2016.

[0004] However, when intentionally generating metamerism, the number of combinations of visible colors reflected by an object containing paint and illuminating light is enormous, making it difficult to actually shine illuminating light on the object and conduct a comprehensive investigation of each combination. Furthermore, the exact light reflection characteristics vary depending on the paint used. For this reason, even if metamerism can be generated using a certain paint pair A in an indoor lighting environment, metamerism may not be reproduced when a different paint pair B, which appears to be the same color as the paint pair A under sunlight, is used.

[0005] In addition, even if it were possible to select multiple candidate pairs of illumination and object color that are observed as different colors under one illumination but the same color under another illumination, it was not possible to determine or evaluate which of the multiple selected candidates would maximize the level of surprise for those who see the metamerism. Note that a color characterized by the illumination and the spectral reflectance spectrum of an object surface is called an object color.

[0006] Non-Patent Document 1 studies a technology for controlling the vividness (saturation) of the apparent color of a subject by changing the spectral spectrum of an illumination light that is a combination of multiple illumination lights. This technology can, in a broad sense, control the apparent color of an object using illumination light by increasing or decreasing the saturation of a specific color among the measured colors. However, there is a limit to the extent to which the apparent color can be changed, and since the technology is not intended to generate metamerism, it is not possible to extract a combination of color and illumination that will generate metamerism.

[0007] Furthermore, Non-Patent Document 2 proposes a technique for searching for conditions that generate metamerism by combining illumination light and mixed paints, with the aim of creating trick art-like effects. This technique makes it possible to comprehensively extract conditions for generating metamerism using illumination light patterns and paint spectral reflectances. However, it is not easy to select, from the many extracted conditions, candidates for illumination light and mixed paint colors that are considered effective in surprising viewers of the phenomenon. Therefore, using the technique described above can sometimes make it difficult to use the extracted conditions for generating metamerism. In other words, it has not been possible to quantitatively evaluate (numerically evaluate) the effects of metamerism.

[0008] The present invention has been made in light of the above-mentioned circumstances, and its object is to provide a means for assisting in the selection of illumination light and object colors that will cause metamerism by conducting a simulation to determine what kind of object and illumination light should be selected in order to intentionally and effectively cause metamerism, and then numerically evaluating the degree of surprise that would be felt by a person who sees the phenomenon for the candidates selected based on the results of the simulation.

[0009] In one embodiment, the evaluation device includes an observation color estimation unit that estimates a first observation color and a second observation color when illuminated with a first illumination light, for a first object color and a second object color that are identified by different spectral characteristics from each other; a color similarity calculation unit that calculates a color difference based on the first observation color and the second observation color; and an effect determination unit that calculates, based on the color difference, an evaluation value for metamerism when the first illumination light, the first object color, and the second object color are used.

[0010] According to the embodiment, by numerically evaluating the degree of surprise of the observer based on the results of the simulation, it is possible to provide a means for assisting in the selection of object colors and illumination light that will cause metamerism.

[0011] FIG. 1 is a block diagram showing an example of the hardware configuration of an evaluation device according to a first embodiment. FIG. 2 is a block diagram showing an example of the functional configuration of the evaluation device according to the first embodiment. FIG. 3 is a flowchart showing an example of the operation of the evaluation device according to the first embodiment. FIG. 4 is a block diagram showing an example of the functional configuration of an evaluation device according to a modified example of the first embodiment. FIG. 5 is a block diagram showing an example of the functional configuration of an evaluation device according to a second embodiment. FIG. 6 is a flowchart showing an example of the operation of the evaluation device according to the second embodiment.

[0012] Hereinafter, several embodiments will be described with reference to the drawings. In the following description, components having the same functions and configurations will be given the same reference numerals.

[0013] 1. First Embodiment An evaluation device according to a first embodiment will be described.

[0014] 1.1 Hardware Configuration First, the hardware configuration of the evaluation device 10 according to the first embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing an example of the hardware configuration of the evaluation device according to the first embodiment.

[0015] The evaluation device 10 includes a control circuit 11 , a storage 12 , and a user interface 13 .

[0016] The control circuit 11 is a circuit that controls the overall components of the evaluation device 10. The control circuit 11 includes a CPU (Central Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), etc. The ROM of the control circuit 11 stores programs and the like used in various processes in the evaluation device 10. The CPU of the control circuit 11 controls the entire evaluation device 10 in accordance with the programs stored in the ROM of the control circuit 11. The RAM of the control circuit 11 is used as a working area for the CPU of the control circuit 11.

[0017] The storage 12 stores, for example, information used in various processes in the evaluation device 10 .

[0018] The user interface 13 is an interface that manages communication between a user and the control circuit 11. The user interface 13 includes an input device and an output device.

[0019] 1.2 Functional Configuration The functional configuration of the evaluation device 10 will be described with reference to Fig. 2. Fig. 2 is a block diagram showing an example of the functional configuration of the evaluation device according to the first embodiment.

[0020] The CPU of the control circuit 11 loads a program stored in the ROM of the control circuit 11 or the storage 12 into the RAM of the control circuit 11. The CPU of the control circuit 11 then interprets and executes the program loaded into the RAM of the control circuit 11. As a result, the evaluation device 10 realizes the functions of a memory unit 21, a search condition acquisition unit 22, a search list creation unit 23, an observed color estimation unit 24, a color similarity calculation unit 25, and an effect determination unit 26.

[0021] The storage unit 21 includes, for example, reflectance information 211, radiant intensity information 212, and color-matching function information 213. The reflectance information 211 includes, for example, multiple spectral reflectance spectra. The multiple spectral reflectance spectra correspond to multiple object colors under a certain illumination light, or multiple objects each having multiple object colors under the illumination light. Note that in the following description, the objects having each object color will also be simply referred to as object colors. With this configuration, the object color can be identified by the spectral reflectance spectrum. The spectral reflectance spectrum can also be referred to as the spectral characteristics of the object color. In the following description, the multiple object colors that can be identified by the reflectance information 211 will be referred to as multiple object color candidates. The radiant intensity information 212 includes, for example, the spectral radiant intensity spectra of multiple illumination lights. As a result, the illumination light can be identified by the spectral radiant intensity spectrum. In the following description, the multiple illumination lights that can be identified by the radiant intensity information 212 will be referred to as multiple illumination light candidates. The color-matching function information 213 includes color-matching functions that indicate the characteristics of the human eye. The color matching function is, for example, a function relating to the mixing ratio of the X component, the Y component, and the Z component in the XYZ color space defined by the International Commission on Illumination (CIE), such that a color is perceived as being equivalent to the color of light of a single wavelength. The XYZ color space defined by the International Commission on Illumination (CIE) is known as a general color space in which a color is represented by the X component, the Y component, and the Z component. In the following description, the spectral reflectance spectrum and the spectral radiant intensity spectrum will also be simply referred to as the spectral reflectance and the spectral radiant intensity, respectively.

[0022] The search condition acquisition unit 22 may acquire search conditions including at least one of object color information and illumination light information from outside the device. Note that the search condition acquisition unit 22 does not necessarily have to acquire search conditions. The object color information is information specifying an object color to be used to generate metamerism, selected from multiple object color candidates. More specifically, the object color information includes, for example, information specifying at least one object color of a pair of different object colors A and B in which metamerism is desired to occur. In other words, the object color information is, for example, information specifying only object color A, or information specifying the pair of object colors A and B. The illumination light information is information specifying an illumination light for generating metamerism. For example, the illumination light information is information specifying one illumination light from multiple illumination light candidates.

[0023] The search list creation unit 23 creates a comprehensive search list of pairs of object colors A and B and combinations of one illumination light, for example, based on search conditions, using the reflectance information 211 and the radiant intensity information 212. When the search condition acquisition unit 22 does not acquire search conditions, the search list creation unit 23 creates a search list including all combinations of pairs of object colors A and B and combinations of illumination light, for example, based on all pairs of object colors A and B selected from multiple object color candidates and multiple illumination light candidates. Furthermore, when the search condition acquisition unit 22 acquires, as search conditions, information specifying one or two of the three elements of object color A, object color B, and illumination light included in each combination in the search list, the search list creation unit 23 creates a search list including all combinations of elements that are not specified. More specifically, for example, if the search conditions specify object color A among the three elements, the search list creation unit 23 creates a search list including all combinations of the specified object color A with an object color B and illumination light not specified by the search conditions, based on all object colors other than object color A among the multiple object color candidates and multiple illumination light candidates. Also, for example, if the search conditions specify object color A and illumination light among the three elements, the search list creation unit 23 creates a search list based on all object colors other than object color A among the multiple object color candidates, for combinations of the specified object color A and illumination light with an object color B not specified by the search conditions. Note that if the search conditions specify a pair of object colors A and B and an illumination light, the search list creation unit 23 does not need to create a search list. That is, the search list includes only the pair of object colors A and B and the combination of illumination light specified by the search conditions.

[0024] The observation color estimation unit 24 estimates the observation colors of the object colors A and B under the illumination light for each combination of the object colors A and B and the illumination light included in the search list, for example, using the reflectance information 211 and radiant intensity information 212 stored in the storage unit 21. Note that in the first embodiment, the observation color of each object color refers to, for example, the coordinates in the XYZ color space of the object color under each illumination light. More specifically, regarding the estimation of the observation colors, the observation color estimation unit 24 calculates the coordinates in the XYZ color space of the object color under the illumination light using the spectral reflectance of each object color and the spectral radiant intensity of each illumination light. It can be said that the observation color estimation unit 24 performs a simulation of the observation colors of the object colors A and B under each illumination light for each combination in the search list. Details of the estimation of the observation colors will be described later.

[0025] The color similarity calculation unit 25 calculates the color difference Def1 between the object colors A and B under each illumination light for each combination in the search list based on the observed color estimated by the observed color estimation unit 24. The calculation of the color difference Def1 will be described later.

[0026] The effect determination unit 26 uses the color difference Def1 calculated by the color similarity calculation unit 25 to calculate, for each combination in the search list, a performance evaluation value Et that numerically predicts the degree of surprise that will be given to an observer when the combination is used in a performance, etc. The calculation of the performance evaluation value Et will be described later. Furthermore, the effect determination unit 26 selects, from the combinations included in the search list, combinations that are expected to be effective when used in a performance, for example, based on the calculated performance evaluation value Et. The effect determination unit 26 outputs metamerism information that includes the combinations selected in this manner as combinations that are expected to be effective. Note that the metamerism information may include the performance evaluation value Et corresponding to each combination, along with the selected combinations.

[0027] 1.3 Operation Next, the operation of the evaluation device 10 according to the first embodiment will be described.

[0028] 1.3.1 Overall Flow First, the overall flow of the operation of the evaluation device 10 according to the first embodiment will be described with reference to Fig. 3. Fig. 3 is a flowchart showing an example of the operation of the evaluation device according to the first embodiment.

[0029] When the operation of the evaluation device starts (START), the search condition acquisition unit 22 acquires search conditions (S11). Then, the process proceeds to S12. Note that if the search condition acquisition unit 22 does not acquire search conditions, the process of S11 is not executed.

[0030] The search list creation unit 23 creates a search list using at least one of the search conditions and the data in the storage unit 21 (S12). Then, the process proceeds to S13. Note that if the search conditions identify a pair of object colors A and B and an illumination light, the process of S12 is not executed. In this case, the search list includes only the pair of object colors A and B and the combination of illumination light identified by the search conditions.

[0031] The observation color estimation unit 24 calculates the coordinates in the XYZ color space of each object color under the illumination light based on the spectral reflectances of the two object colors included in each combination in the search list, the spectral radiant intensity of the illumination light, and the color matching function from the storage unit 21 (S13).The process then proceeds to S14.

[0032] The color similarity calculation unit 25 calculates the color difference Def1 between the object colors A and B under each illumination light (S14), and the process then proceeds to S15.

[0033] The effect determination unit 26 evaluates each combination in the search list using the calculated color difference Def1 (S15). That is, the effect determination unit 26 calculates a performance evaluation value Et. Furthermore, based on the performance evaluation value Et, the effect determination unit 26 selects a combination from the combinations included in the search list that is expected to be effective when used for performance. Furthermore, the effect determination unit 26 outputs metamerism information including the combination selected in this manner.

[0034] The operation of the evaluation device 10 is completed by the above processing.

[0035] 1.3.2 Calculation of Coordinates in XYZ Color Space Next, a method for calculating coordinates in the XYZ color space in the process of S13 will be described.

[0036] The observation color estimation unit 24 acquires, for each combination in the search list, the spectral reflectance R(λ) of each object color, the spectral radiant intensity F(λ) of each illumination light, and color matching functions for the wavelength λ from the storage unit 21. The color matching functions are color matching functions H Ｘ (λ), H Ｙ (λ), and H Ｚ (λ).

[0037] The observation color estimation unit 24 calculates the spectral reflectance R(λ), the spectral radiant intensity F(λ) of the illumination light, and the color matching function H Ｘ (λ), H Ｙ (λ), and H Ｚ Using (λ) and a constant N, the components X, Y, and Z of the XYZ color space of each object color under each illumination light are calculated, as expressed by the following equations (1), (2), and (3).

[0038]

[0039]

[0040]

[0041] The constant N is a constant expressed by the following formula (4) using, for example, the spectral irradiance I(λ) of a standard white light source. Note that the spectral irradiance I(λ) is a special case in the spectral irradiance spectrum of illumination light, and refers to the spectral irradiance spectrum of an arbitrarily determined standard white light source, such as D50 or D65. The spectral irradiance I(λ) of the standard white light source is stored, for example, in the irradiance intensity information 212. This allows the observation color estimation unit 24 to use the spectral irradiance I(λ) of the standard white light source.

[0042]

[0043] In this manner, the coordinates in the XYZ color space of each object color under each illumination light are calculated.

[0044] 1.3.3 Calculation of Color Difference The calculation of the color difference Def1 in the process of S14 will be described.

[0045] The color similarity calculation unit 25 calculates the color difference Def1 as the Euclidean distance (L2 norm) between the coordinates of each object color under each illumination light in the Lab color space. The Lab color space is a color space represented by the L component, the a component, and the b component. The Lab color space is known as a uniform color space, in which color differences perceived as equivalent in magnitude have equivalent distances in the color space. Note that the following description uses the Lab color space as an example of a uniform color space, but other uniform color spaces such as the Luv color space can also be used. Furthermore, with regard to brightness, it is also possible to use a colorimetric value Y that does not depend on the white point instead of the L value.

[0046] More specifically, the color similarity calculation unit 25 calculates the coordinates in the Lab color space of each object color under each illumination light by coordinate conversion from the XYZ color space to the Lab color space using the white point. Ａ , Y Ａ , Z Ａ ) and (X Ｂ , Y Ｂ , Z Ｂ ) are expressed as coordinates in the Lab color space (L Ａ , a Ａ , b Ａ ) and (L Ｂ , a Ｂ , b Ｂ ) and convert the value X Ａ , Y Ａ , and Z Ａ are the values ​​of the X, Y, and Z components of the object color A in the XYZ color space. Ｂ , Y Ｂ , and Z Ｂ are the values ​​of the X, Y, and Z components of the object color B in the XYZ color space. Ａ , a Ａ , and b Ａ are the values ​​of the L component, a component, and b component in the Lab color space of the object color A. Ｂ , a Ｂ , and b Ｂ are the values ​​of the L component, a component, and b component of the object color B in the Lab color space.

[0047] Then, the color similarity calculation unit 25 calculates the coordinates (L Ａ , a Ａ , b Ａ ) and (L Ｂ , a Ｂ , b Ｂ ) is used to calculate the Euclidean distance between the coordinates of the object colors A and B in the Lab color space as the color difference Def1.

[0048] The color similarity calculation unit 25 may calculate the color difference Def1 for the object colors A and B under each illumination light using the CIE DE2000 color difference formula.

[0049] In this manner, the color difference Def1 between the object colors A and B is calculated by the color similarity calculation unit 25.

[0050] 1.3.4 Evaluation by the Effect Determining Unit The evaluation of each combination in the search list in the processing of S15 will be described.

[0051] The effect determination unit 26 determines an evaluation value E based on the color difference Def1. １ The effect determination unit 26 calculates the performance evaluation value Et using the evaluation value E １ In addition to the above, one or more additional evaluation values ​​may be used to calculate the performance evaluation value Et. In the following, as an example of the additional evaluation value, four additional evaluation values ​​E ２ , E ３ , E ４ , and E ５ is explained.

[0052] Evaluation value E １ is an essential evaluation value when calculating the performance evaluation value Et. In order to realize a performance that surprises the observer, it is important that the object color A and the object color B appear to be the same color under the illumination light. １ The smaller the color difference Def1 calculated by the color similarity calculation unit 25, the larger the value of .DELTA..times ...

[0053] In order to realize a performance that will surprise the observer, it is important that the object colors A and B appear to be different colors under illumination light other than illumination light that makes the object colors A and B appear to be the same color. ２The larger the color difference Def2 in the Lab color space between the object colors A and B under the standard light source, the larger the value of the additional evaluation value E. ２ is, for example, equivalent to the color difference Def2 (E ２ =Def2) The calculation method for the color difference Def2 is the same as the calculation method for the color difference Def1, except that in the above formulas (1) to (3), the spectral radiant intensity of the standard light source is used instead of the spectral radiant intensity F(λ) of the illumination light.

[0054] Furthermore, in order to realize a performance that will surprise the viewer, it is considered effective to generate metamerism without making the viewer feel that a special light is being irradiated. ３ is a value related to the naturalness of the illumination light. ３ The closer the illumination light is to natural light (for example, a standard white light source), the larger the additional evaluation value E ３ For example, the smaller the intensity difference Def3 between the spectral radiant intensities of the illumination light and the standard white light source, the larger the value of Ef3. The effect determining unit 26 determines the intensity difference Def3 and the additional evaluation value E based on the spectral radiant intensity F(λ) of the illumination light and the spectral radiant intensity of the standard white light source. ３ The intensity difference Def3 is expressed by the following formula (5).

[0055]

[0056] Additional evaluation value E ４ is the additional evaluation value E ３ Similarly to the above, the additional evaluation value E is a value relating to the naturalness of the illumination light. ４is based on a value Def4 calculated using, for example, the coordinates in the XYZ color space of a white object under a standard white light source and the coordinates in the XYZ color space of a white object under illumination light. The white object may be, for example, an object whose spectral reflectance is 1, independent of wavelength λ. The coordinates in the XYZ color space of a white object under a standard white light source are calculated by using the spectral radiant intensity of the standard white light source instead of the spectral radiant intensity F(λ) of the illumination light in the above formulas (1) to (3), and setting the spectral reflectance R(λ) to 1. The coordinates in the XYZ color space of a white object under illumination light are calculated by using the spectral reflectance R(λ) to 1 in the above formulas (1) to (3). The value Def4 is expressed, for example, using the following formula (6) based on the coordinates (L1, a1, b1) in the Lab color space of a white object under a standard white light source and the coordinates (L2, a2, b2) in the Lab color space of a white object under illumination light. Here, the coordinates in the Lab color space of a white object under a standard white light source and a white object under illumination light are both calculated by using the standard white light as a reference white point, similar to the calculation of the coordinates in the Lab color space of object colors A and B under a standard white light source. Additional evaluation value E ４ For example, the smaller the value Def4 is, the larger the value becomes.

[0057]

[0058] Additional evaluation value E ５ is the additional evaluation value E ３ and E ４ Similarly to the above, the additional evaluation value E is a value relating to the naturalness of the illumination light. ５ is an evaluation value regarding the color rendering properties of the illumination light. ５ The higher the color rendering property, the larger the additional evaluation value E ５ is, for example, an evaluation value of color rendering properties in accordance with ISO 3664:2009. ５ can be calculated based on the spectral radiant intensity F(λ) of the illumination light, for example.

[0059] The performance evaluation value Et is the above-mentioned evaluation value E １ and additional evaluation value E ２ , E ３ , E ４ , and E５ The value k is calculated using the following equation (7) based on the above. １ , k ２ , k ３ , k ４ , and k ５ are the evaluation values ​​E １ , and additional evaluation value E ２ , E ３ , E ４ , and E ５ is a weighting constant corresponding to the value k １ is a positive number. ２ , k ３ , k ４ , and k ５ is a number equal to or greater than 0. ２ , k ３ , k ４ , and k ５ The additional evaluation value corresponding to the value of 0 among the above may not be calculated.

[0060]

[0061] The effect determination unit 26 selects combinations from the search list that effectively generate metamerism, for example, based on the effect evaluation value Et calculated as described above. More specifically, the effect determination unit 26 selects combinations in the search list as combinations that effectively generate metamerism, for example, when the effect evaluation value Et of each combination in the search list is higher than a predetermined reference value. Furthermore, the effect determination unit 26 selects a predetermined number of combinations from the combinations included in the search list in descending order of effect evaluation value Et. The effect determination unit 26 outputs metamerism information including the combinations selected as described above as combinations that are assumed to be effective.

[0062] 1.4 Effects of the First Embodiment According to the first embodiment, by numerically evaluating the degree of surprise of the observer based on the results of the simulation, it is possible to provide a means for assisting in the selection of object colors and illumination light that will cause metamerism.

[0063] The evaluation device 10 according to the first embodiment includes an observation color estimation unit 24, a color similarity calculation unit 25, and an effect determination unit 26. The observation color estimation unit 24 estimates the observation colors of object colors A and B, which are identified by their different spectral reflectance spectra when illuminated with illumination light. The color similarity calculation unit 25 calculates a color difference based on the observation colors of the object colors A and B. The effect determination unit 26 calculates a performance evaluation value Et for metamerism when using the illumination light and the object colors A and B based on the color difference calculated by the color similarity calculation unit 25. With the above configuration, the evaluation device 10 can evaluate the degree of surprise of an observer when an object color pair and illumination light are used for a performance, etc., based on the results of a simulation, without having to confirm whether the two object colors are similar to each other using actual illumination light. Therefore, for example, when there are a huge number of combinations of object color pairs and illumination lights to be used for a performance, it is possible to narrow down the combinations to those with a high performance evaluation value Et, which indicates the degree of surprise that an observer receives. This facilitates the selection of object color pairs and illumination lights.

[0064] 2. Modification of the First Embodiment In the first embodiment described above, the observation color estimation unit 24 calculates coordinates in the XYZ color space based on the spectral reflectances of object colors A and B. However, this is not limited to this. If an object having an object color emits fluorescence centered on visible light when irradiated with excitation light centered on the invisible light band, such as ultraviolet light, the evaluation device may take into account the fluorescence characteristics of the object colors A and B in addition to the spectral reflectances of the object colors A and B. The following mainly describes configurations that differ from the first embodiment.

[0065] 2.1 Functional Configuration The functional configuration of the evaluation device 10 will be described with reference to Fig. 4. Fig. 4 is a block diagram showing an example of the functional configuration of an evaluation device according to a modified example of the first embodiment.

[0066] The evaluation device 10 includes, as functional components, a memory unit 21, a search condition acquisition unit 22, a search list creation unit 23, an observed color estimation unit 24, a color similarity calculation unit 25, and an effect determination unit 26. The configurations of the search condition acquisition unit 22, the search list creation unit 23, and the color similarity calculation unit 25 can be similar to the configurations of the search condition acquisition unit 22, the search list creation unit 23, and the color similarity calculation unit 25 according to the first embodiment.

[0067] The storage unit 21 includes fluorescence characteristic information 214 in addition to reflectance information 211, radiant intensity information 212, and color-matching function information 213. The fluorescence characteristic information 214 includes an excitation spectral ratio E(λ) and a fluorescence spectral ratio FL(λ) associated with each object color. The excitation spectral ratio E(λ) is a graph showing the relative ratio of fluorescence intensity at each excitation wavelength, assuming that the fluorescence intensity at the wavelength (optimal excitation wavelength) at which an object having each object color exhibits the strongest fluorescence intensity is 1. The fluorescence spectral ratio FL(λ) indicates the fluorescence intensity at each wavelength when irradiated with light of the optimal excitation wavelength, assuming that the intensity of light of the optimal excitation wavelength is 1. Note that in the modified example of the first embodiment, the spectral reflectance R(λ) is a spectral reflectance spectrum that does not take into account the fluorescence of each object color. That is, for example, the spectral reflectance R(λ) in the modified example of the first embodiment is a spectrum based on reflected light including fluorescence. Furthermore, in the modified example of the first embodiment, the spectral radiant intensity F(λ) of each illumination light is, for example, a spectral radiant intensity spectrum of illumination light that does not include excitation wavelength components for multiple object color candidates, or in which the excitation wavelength components are negligible (that is, the excitation wavelength components are included only in minute amounts).

[0068] The observation color estimation unit 24 can use, for example, the reflectance information 211 and radiant intensity information 212 stored in the storage unit 21, as well as the fluorescence characteristic information 214, to calculate the coordinates in the XYZ color space of each object color under the illumination light, taking into account the fluorescence characteristics, for the object colors A and B included in each combination in the search list and the illumination light. In other words, when calculating the coordinates in the XYZ color space of each object color, the observation color estimation unit 24 can be said to perform correction based on the fluorescence characteristics. Hereinafter, the coordinates in the XYZ color space of each object color taking into account the fluorescence characteristics will also be referred to as the observation color. The calculation of coordinates in the XYZ color space taking into account the fluorescence characteristics will be described later.

[0069] In a modification of the first embodiment, the effect determining unit 26 may calculate the effect evaluation value Et taking into account the fluorescent light characteristics. The calculation of the effect evaluation value Et in the modification of the first embodiment will be described later.

[0070] 2.2 Operation of the Evaluation Device Pertaining to the Modification of the First Embodiment The operation of the evaluation device 10 pertaining to the modification of the first embodiment can be the same as the operation of the evaluation device pertaining to the first embodiment, except that the evaluation device 10 can estimate the observed color of the object color, calculate the color difference Def1, and calculate the rendering evaluation value Et, taking into account the fluorescent characteristics. The following mainly describes the estimation of the observed color of the object color and the calculation of the rendering evaluation value Et. Note that the calculation of the color difference Def1 is the same as in the first embodiment, except that it can be calculated based on the observed color taking into account the fluorescent characteristics, and therefore a description thereof will be omitted.

[0071] 2.2.1 Estimation of Observed Color First, estimation of observed color taking into account the fluorescence characteristics will be described.

[0072] The observation color estimation unit 24 calculates the fluorescence characteristic L(λ) based on the fluorescence characteristic information 214. The fluorescence characteristic L(λ) indicates the intensity of the fluorescence spectrum output relative to the spectral radiance spectrum of the irradiation light, including the excitation light, irradiated onto an object having each object color. The fluorescence characteristic L(λ) is expressed using the following equation (8) based on a constant P and a fluorescence spectral ratio FL(λ):

[0073]

[0074] The constant P in the above formula (8) is expressed using the following formula (9) based on the excitation spectrum ratio E(λ) of the object color.

[0075]

[0076] The observation color estimation unit 24 estimates the spectral reflectance R(λ) of the object color, the spectral radiant intensity F(λ) of the illumination light, and the color matching function H Ｘ (λ), H Ｙ (λ), and H Ｚ Using (λ), constants N and α, and the fluorescence characteristic L(λ), the components X, Y, and Z of the XYZ color space of each object color under each illumination light are calculated as shown in the following equations (10), (11), and (12). That is, the observation color estimation unit 24 estimates the observation color of each object color taking the fluorescence characteristic into account. Note that the constant N is equal to the value expressed by the above equation (4). The constant α is a positive number that determines the extent to which the influence of fluorescence is removed. The constant α depends, for example, on the degree of contribution of fluorescence to the spectral reflectance R(λ).

[0077]

[0078]

[0079]

[0080] In this manner, the coordinates in the XYZ color space of each object color under each illumination light are calculated, taking into account the fluorescent characteristic L(λ).

[0081] By estimating the observed color as described above, it is possible to improve the accuracy of estimating the observed color when the spectral reflectance R(λ) of the object color is a spectral reflectance spectrum that does not take fluorescence into consideration, for a combination of fluorescent object colors A and B and illumination light that does not contain an excitation wavelength component or in which the excitation wavelength component is negligible.

[0082] For the color of an object that does not emit fluorescence, the observed color can be estimated in the same manner as in the first embodiment.

[0083] The fluorescence characteristic L(λ) may be stored in advance in the fluorescence characteristic information 214 .

[0084] 2.2.2 Calculation of the Rendering Evaluation Value The calculation of the rendering evaluation value Et will be described.

[0085] The performance evaluation value Et in the modified example of the first embodiment is the evaluation value E １ and additional evaluation value E ２ , E ３ , E ４ , and E ５ Based on the evaluation value E １ , and the additional evaluation value E ３ , E ４ , and E ５ The calculation method of the additional evaluation value E in the modified example of the first embodiment can be the same as that in the first embodiment. ２ This section mainly explains how to calculate the above.

[0086] Additional evaluation value E in the modified example of the first embodiment ２ is a value for evaluating whether object colors A and B appear to be different colors when fluorescent characteristics are taken into consideration under a standard light source. ２ is equivalent to the color difference Def2 in the Lab color space between object colors A and B under a standard light source when taking into account the fluorescent characteristics, for example. ２ The method of calculating the color difference Def2 in the modified example of the first embodiment is similar to the method of calculating the color difference Def1 in the first embodiment, except that when calculating the coordinates in the XYZ color space of the object color under the standard light source, the spectral radiant intensity of the standard light source is used instead of the spectral radiant intensity F(λ) of the illumination light in the above equations (10) to (12).

[0087] The above-described configuration also provides the same effects as the first embodiment.

[0088] Furthermore, according to the modification of the first embodiment, it is possible to estimate the observed color with high accuracy for the color of an object that emits fluorescence.

[0089] 3 Second Embodiment Next, an evaluation device according to a second embodiment will be described.

[0090] The second embodiment differs from the first embodiment and the modified example of the first embodiment in that the object color is identified based on image data. The following mainly describes the configuration that differs from the second embodiment.

[0091] 3.1 Functional Configuration The functional configuration of the evaluation device 10 will be described with reference to Fig. 5. Fig. 5 is a block diagram showing an example of the functional configuration of the evaluation device according to the second embodiment.

[0092] The evaluation device 10 includes, as functional components, a storage unit 21, a search condition acquisition unit 22, a search list creation unit 23, an observed color estimation unit 24, a color similarity calculation unit 25, an effect determination unit 26, an image acquisition unit 27, and a spectral reflectance calculation unit 28. The configurations of the storage unit 21, observed color estimation unit 24, color similarity calculation unit 25, and effect determination unit 26 can be similar to the configurations of the storage unit 21, observed color estimation unit 24, color similarity calculation unit 25, and effect determination unit 26 according to the first embodiment.

[0093] The image acquisition unit 27 acquires a hyperspectral (HS) image, for example, from outside the device. The HS image is image data of two or more object colors captured by an HS camera when illuminated with a shooting illumination light. The HS image includes, for example, information on the spectral reflectance intensity of the actual object surface. The image acquisition unit 27 is configured to present the acquired HS image to a user via a display. The user is then configured to specify position coordinates within the HS image using operating equipment such as a mouse or keyboard. The image acquisition unit 27 displays, for example, a one-channel image relating to an arbitrary wavelength λ in the HS image as a monochrome image on the display. Furthermore, the image acquisition unit 27 displays, for example, three-channel images relating to three arbitrarily selected wavelengths λ, corresponding to RGB, on the display. The display and operating equipment are included, for example, in the user interface 13. The display may be, for example, an external display provided to be capable of communicating with the evaluation device 10.

[0094] The spectral reflectance calculation unit 28 acquires position coordinates (object color position coordinates) that identify the object color in the HS image, which are specified by the user based on the display. The user specifies, for example, two position coordinates. That is, the user specifies two object colors A and B associated with the two position coordinates. Note that each position coordinate is, for example, one pixel. For example, based on each acquired position coordinate and the HS image, the spectral reflectance calculation unit 28 acquires the spectral reflectance intensity spectrum at the position coordinate as the spectral reflectance intensity S(λ) of the object color corresponding to the position coordinate. The spectral reflectance calculation unit 28 also acquires information (standard spectral reflectance intensity information) regarding the spectral reflectance intensity Is(λ) of a standard white plate when illuminated with illumination light equivalent to the imaging illumination light used to capture the HS image. The standard spectral reflectance information is, for example, the spectral reflectance intensity Is(λ) of a standard white plate when illuminated with illumination light equivalent to the imaging illumination light used to capture the HS image. Furthermore, if the HS image acquired by the image acquisition unit 27 is an image of a standard white board in addition to two or more object colors, the spectral reflectance calculation unit 28 acquires, for example, the position coordinates of the standard white board specified by the user as standard spectral reflectance intensity information. Then, the spectral reflectance calculation unit 28 acquires the spectral reflectance Is(λ) of the standard white board based on the HS image and the position coordinates of the standard white board. The spectral reflectance calculation unit 28 calculates the spectral reflectance R(λ) of each object color using the following equation (13) based on the spectral reflectance S(λ) and spectral reflectance Is(λ) of the object color. The spectral reflectance calculation unit 28 also transmits the calculated spectral reflectance R(λ) of each object color to the storage unit 21. The transmitted spectral reflectance R(λ) of each object color is then stored in the reflectance information 211 as the spectral reflectance of the new object color. Furthermore, the spectral reflectance calculation unit 28 transmits information specifying the object colors A and B designated by the user based on the HS image as object color information to the search condition acquisition unit 22, for example.

[0095]

[0096] The search condition acquisition unit 22 receives object color information from the spectral reflectance calculation unit 28. The search condition acquisition unit 22 can also acquire illumination light information from outside the device. Note that the search condition acquisition unit 22 does not necessarily have to acquire illumination light information.

[0097] When the search condition acquisition unit 22 does not acquire illumination light information as a search condition, the search list creation unit 23 creates a search list based on a pair of object colors A and B specified by the user and a plurality of illumination light candidates for the combination of illumination light. When the search condition acquisition unit 22 acquires illumination light information, the search list creation unit 23 does not need to create a search list. That is, the search list includes only the pair of object colors A and B specified by the user and the combination of illumination light specified by the illumination light information.

[0098] 3.2 Operation of the Evaluation Device According to the Second Embodiment The operation of the evaluation device 10 according to the second embodiment will be described with reference to Fig. 6. Fig. 6 is a flowchart showing an example of the operation of the evaluation device according to the second embodiment.

[0099] First, the image acquisition unit 27 acquires an HS image from an external source. The acquired HS image is then presented to the user. The spectral reflectance calculation unit 28 acquires the position coordinates of the object color specified by the user and standard reflection intensity information. The spectral reflectance calculation unit 28 then calculates the spectral reflectances R(λ) of the object colors A and B based on the HS image, the position coordinates of the object color, and the standard reflection intensity information (S21). The spectral reflectance calculation unit 28 then transmits the spectral reflectances R(λ) of each object color calculated as described above to the storage unit 21. The spectral reflectances R(λ) of each object color are stored in the reflectance information 211.

[0100] The processes of S22 to S26 are substantially the same as the processes of S11 to S15 in the first embodiment. Note that when the search condition acquisition unit 22 acquires illumination light as a search condition, the search list is not created in S23. In this case, the search list includes only the pair of object colors A and B specified by the user and the combination of illumination light specified by the illumination light information.

[0101] This completes the operation of the evaluation device 10 according to the second embodiment.

[0102] The second embodiment also provides the same effects as the first embodiment.

[0103] Furthermore, the spectral reflectance of an object is generally not self-evident. According to the second embodiment, even when the spectral reflectance is unknown, by using an HS image of an object exhibiting the object color desired to be used in a performance, etc., it is possible to quantitatively and numerically evaluate the degree of surprise of an observer when an object color pair and illumination light are used in a performance, etc. Furthermore, the evaluation device 10 according to the second embodiment is useful for interactively narrowing down candidates, for example, by using a graphical user interface based on the HS image to allow a user to reselect object color pairs to be used in a performance from a large number of object colors, such as a color sample, while checking the performance evaluation value Et.

[0104] 4. Others: The present invention is not limited to the above-described embodiments, and various modifications can be made in the implementation stage without departing from the spirit of the invention. Furthermore, the embodiments may be implemented in appropriate combinations, in which case the combined effects can be obtained. Furthermore, the above-described embodiments include various inventions, and various inventions can be extracted by combining selected elements from the disclosed elements. For example, if the problem can be solved and the desired effect can be obtained even if some elements are deleted from all elements shown in the embodiments, the configuration from which these elements are deleted can be extracted as an invention.

[0105] REFERENCE SIGNS LIST 10...Evaluation device 11...Control circuit 12...Storage 13...User interface 21...Memory unit 22...Search condition acquisition unit 23...Search list creation unit 24...Observation color estimation unit 25...Color similarity calculation unit 26...Effect determination unit 27...Image acquisition unit 28...Spectral reflectance calculation unit 211...Reflectance information 212...Radiant intensity information 213...Color matching function information

Claims

1. An evaluation device comprising: an observation color estimation unit that estimates a first observation color and a second observation color when illuminated with a first illumination light for a first object color and a second object color identified by mutually different spectral characteristics; a color similarity calculation unit that calculates a color difference based on the first observation color and the second observation color; and an effect assessment unit that calculates, based on the color difference, an evaluation value for metamerism when the first illumination light, the first object color, and the second object color are used.

2. The evaluation device according to claim 1, wherein the observation color estimation unit estimates the first observation color and the second observation color by taking into account the fluorescence characteristics of an object having the first object color and the fluorescence characteristics of an object having the second object color.

3. An evaluation method comprising: estimating a first observation color and a second observation color when illuminated with a first illumination light for a first object color and a second object color identified by mutually different spectral characteristics; calculating a color difference based on the first observation color and the second observation color; and calculating an evaluation value for metamerism when the first illumination light, the first object color, and the second object color are used based on the color difference.

4. A program for causing each unit of the evaluation device according to claim 1 or 2 to function.