Member for calibration, housing device, calibration device, calibration method, and program

Abstract

A member for calibration according to the present invention is used to calibrate a spectroscopic imaging device comprising a spectral filter that has a specific wavelength region. This member for calibration has a background surface that constitutes the background of a subject. In the specific wavelength region, a first spectral reflectance that is the spectral reflectance of light reflected by the subject and a second spectral reflectance that is the spectral reflectance of light reflected by the background surface have a relationship with each other.

Description

Calibration member, housing device, calibration device, calibration method, and program

[0001] The technology of the present disclosure relates to a calibration member, a housing device, a calibration device, a calibration method, and a program.

[0002] Japanese Patent Laid-Open Publication No. 2006-292582 discloses a multiband image processing device that acquires a spectral image of a subject. The multiband image processing device includes an image acquisition unit that acquires an image of a subject in a state where a plurality of objects with known spectral characteristics are placed near the subject, and an image processing unit that performs predetermined processing on the image based on spatial variations in the spectral characteristics of the plurality of objects obtained from the image.

[0003] Japanese Patent Application Laid-Open No. 2018-009988 discloses a measuring device for evaluating particle characteristics of a coated surface containing a lustrous material. The measuring device includes a chromaticity distribution acquisition unit that acquires an in-plane chromaticity distribution of an object under at least two or more illumination conditions or light receiving conditions, and a particle characteristic evaluation unit that calculates a particle characteristic evaluation value for evaluating particle characteristics based on the amount of variation in the in-plane chromaticity distribution.

[0004] Japanese Patent Application Laid-Open Publication No. 2001-144972 discloses a multispectral image recording and processing device that captures and records an image of a subject in a subject imaging and recording area illuminated by a light source. The multispectral image recording and processing device includes a subject support unit, a light source unit, an imaging means, a polarized multispectral image acquisition unit, and a spectral reflectance estimation unit. The subject support unit supports the subject in the subject imaging and recording area. The light source unit is disposed a fixed distance from a predetermined position in a plane including the predetermined position in a desired azimuth direction centered on the predetermined position in the subject imaging and recording area, and illuminates the subject imaging and recording area. The imaging means is disposed a fixed distance from the predetermined position in a plane including the predetermined position in a desired azimuth direction centered on the predetermined position, and captures a multiband image of the subject. The angular multispectral image acquisition unit obtains an angular multispectral image having a spectral reflectance distribution of the subject, with the light source position and the imaging position as parameters, from a plurality of multiband images captured and recorded under a plurality of imaging and recording conditions in which the light source position determined by the azimuth direction of the light source unit and the imaging position determined by the azimuth direction of the imaging means are respectively changed. The spectral reflectance estimation unit interpolates or synthesizes the spectral reflectance distributions with the light source position and the imaging position as parameters, and estimates the spectral reflectance distribution of the subject under image reproduction conditions with a desired light source position, number of light sources, or imaging position, using the image data of the angular multispectral image obtained by the angular multispectral image acquisition unit.

[0005] Japanese Patent Laid-Open Publication No. 2010-130157 discloses a multispectral image processing device including a color conversion means for performing color conversion on a multiband image having four or more bands obtained by combining multiple input images input by multiple image input means having different bands. The color conversion means includes a spectral sensitivity characteristic information correction means for correcting spectral sensitivity characteristic information, which is the spectral sensitivity characteristic of the image input means, based on the ratio of exposure amount information included in the data of the multiple input images, and a device-independent color image conversion means for converting the multiband image into a device-independent color image using the corrected spectral sensitivity characteristic information and shooting illumination light information, which is the spectral characteristic of the illumination light used to shoot the input images.

[0006] One embodiment of the technology disclosed herein provides a calibration member, a housing device, a calibration device, a calibration method, and a program that can improve measurement accuracy for the color of a subject, compared to when the background surface is a white surface, for example.

[0007] A first aspect of the technology of the present disclosure is a calibration member used to calibrate a spectral imaging device equipped with a spectral filter having a specific wavelength range, wherein the calibration member has a background surface that forms the background of a subject, and in the wavelength range, a first spectral reflectance that is the spectral reflectance of light reflected by the subject and a second spectral reflectance that is the spectral reflectance of light reflected by the background surface are related to each other.

[0008] A second aspect of the technology of the present disclosure is a calibration member according to the first aspect, wherein the relationship is such that the difference between the first spectral reflectance and the second spectral reflectance is within a first range.

[0009] A third aspect of the technology of the present disclosure is a calibration member according to the second aspect, wherein the first range is a range from 0.5 times the reflectance to 2 times the reflectance of the first spectral reflectance.

[0010] A fourth aspect of the technology of the present disclosure is a calibration member according to the second or third aspect, wherein the first range is set based on a third spectral reflectance, which is the spectral reflectance of light reflected by a first reference plate.

[0011] A fifth aspect of the technique of the present disclosure is the calibration member according to the fourth aspect, wherein the first reference plate has a reflective surface that reflects light, and the reflective surface is a white surface.

[0012] A sixth aspect of the technology of the present disclosure is a calibration member according to the fourth or fifth aspect, wherein the difference between the first spectral reflectance and the second spectral reflectance is smaller than the difference between the first spectral reflectance and the third spectral reflectance.

[0013] A seventh aspect of the technology of the present disclosure is a calibration member according to any one of the fourth to sixth aspects, wherein the second spectral reflectance is lower than the third spectral reflectance.

[0014] An eighth aspect of the technology of the present disclosure is a calibration member according to any one of the fourth to seventh aspects, wherein the first spectral reflectance is lower than the third spectral reflectance.

[0015] A ninth aspect of the technology of the present disclosure is a calibration member according to any one of the fourth to eighth aspects, wherein the second spectral reflectance falls within a second range of spectral reflectance set based on the first spectral reflectance and the third spectral reflectance.

[0016] A tenth aspect of the technique of the present disclosure is the calibration member according to the ninth aspect, wherein when the first spectral reflectance is a, the second spectral reflectance is b, and the third spectral reflectance is c, the second range is a range defined by the following formula (1): a / 2≦b≦(c+a) / 2 (1)

[0017] An eleventh aspect of the technique of the present disclosure is the calibration member according to the ninth aspect, wherein when the first spectral reflectance is a, the second spectral reflectance is b, and the third spectral reflectance is c, the second range is a range defined by the following formula (2): 3a / 4≦b≦(c+3a) / 4 (2)

[0018] A twelfth aspect of the technology of the present disclosure is a calibration member according to any one of the first to eleventh aspects, wherein the first spectral reflectance is a spectral reflectance based on spectral reflectances measured at multiple locations on a subject.

[0019] A thirteenth aspect of the technology of the present disclosure is a calibration member according to any one of the fourth to eleventh aspects and the twelfth aspect dependent on the fourth aspect, wherein the specific wavelength range includes a plurality of wavelength ranges, and in each wavelength range, the difference between the first spectral reflectance and the second spectral reflectance is smaller than the difference between the first spectral reflectance and the third spectral reflectance.

[0020] A fourteenth aspect of the technology of the present disclosure is a calibration member according to any one of the first to thirteenth aspects, wherein the background surface is a calibration member having a surface roughness corresponding to that of the subject.

[0021] A fifteenth aspect of the technology of the present disclosure is a calibration member according to any one of the first to fourteenth aspects, wherein the spectral reflectance of the background surface is higher in a first near-infrared range of the near-infrared range than in a first visible range of the visible range.

[0022] A sixteenth aspect of the technology of the present disclosure is a housing device comprising a calibration member according to any one of the first to fifteenth aspects and a housing that covers an imaging space in which the calibration member and a subject are placed.

[0023] A seventeenth aspect of the technology of the present disclosure is a calibration device comprising a calibration member according to any one of the first to fifteenth aspects, a spectroscopic imaging device, a light source, and a housing, wherein the housing covers an imaging space in which the calibration member and a subject are placed, and the imaging condition when imaging the subject with the spectroscopic imaging device is a first condition in which a first component of the incident light entering the spectroscopic imaging device becomes light irradiated from the light source and reflected by the subject and the calibration member.

[0024] An eighteenth aspect of the technique of the present disclosure is a calibration device according to the seventeenth aspect, further comprising a processor, the processor outputting warning information when the imaging conditions deviate from the first conditions.

[0025] A 19th aspect of the technology of the present disclosure is a calibration device that includes a calibration member according to any one of the first to fifteenth aspects and a processor, wherein the processor acquires first imaging data obtained by imaging the calibration member with a spectroscopic imaging device, acquires second imaging data obtained by imaging the calibration member and a subject with the spectroscopic imaging device, and calibrates the second imaging data based on the first imaging data.

[0026] A twentieth aspect of the technology of the present disclosure is a calibration method including a first acquisition step of acquiring first imaging data obtained by imaging a calibration member relating to any one of the first to fifteenth aspects using a spectroscopic imaging device, a second acquisition step of acquiring second imaging data obtained by imaging the calibration member and a subject using the spectroscopic imaging device, and a calibration step of calibrating the second imaging data based on the first imaging data.

[0027] A 21st aspect of the technology of the present disclosure is a program for causing a computer to execute processing including a first acquisition step of acquiring first imaging data obtained by imaging a calibration member relating to any one of the first to fifteenth aspects using a spectroscopic imaging device, a second acquisition step of acquiring second imaging data obtained by imaging the calibration member and the subject using the spectroscopic imaging device, and a calibration step of calibrating the second imaging data based on the first imaging data.

[0028] 1 is a block diagram showing an example of a color measurement device according to the present embodiment. FIG. 1 is a graph showing examples of a first spectral reflectance, a second spectral reflectance, and a third spectral reflectance. FIG. 2 is a graph showing a first example of the second spectral reflectance. FIG. 3 is a graph showing a second example of the second spectral reflectance. FIG. 4 is a block diagram showing an example of a color setting method for setting the color of a background surface. FIG. 5 is a block diagram showing an example of a color measurement method according to the present embodiment. FIG. 6 is a block diagram showing an example of a mode of incident light in the color measurement method according to the present embodiment. FIG. 7 is a perspective view showing an example of an image capture device according to the present embodiment. FIG. 8 is an exploded perspective view showing an example of a pupil division filter. FIG. 9 is a block diagram showing an example of a hardware configuration of the image capture device. FIG. 10 is an explanatory diagram showing an example of a configuration of a photoelectric conversion element. FIG. 11 is a block diagram showing an example of a functional configuration for executing spectral image generation processing. FIG. 12 is a block diagram showing an example of an operation of an output value acquisition unit and an interference removal processing unit. FIG. 13 is a block diagram showing an example of a hardware configuration of a processing device according to the present embodiment and an example of a functional configuration for executing color measurement processing. FIG. 14 is a block diagram showing an example of an operation of an image data acquisition unit, a calibration image generation unit, and a color derivation unit. FIG. 15 is a flowchart showing an example of the flow of spectral image generation processing. FIG. 16 is a flowchart showing an example of the flow of color measurement processing. FIG. 17 is a block diagram showing an example of a color measurement method according to a first comparative example. FIG. 18 is a block diagram showing an example of a color measurement method according to a second comparative example. FIG. 19 is a block diagram showing an example of a mode of incident light in the color measurement method according to the second comparative example.

[0029] Hereinafter, examples of embodiments of a calibration member, a housing device, a calibration device, a calibration method, and a program according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0030] First, the terms used in the following description will be explained.

[0031] RGB is an abbreviation for "Red Green Blue". LED is an abbreviation for "light emitting diode". EL is an abbreviation for "Electro Luminescence". CMOS is an abbreviation for "Complementary Metal Oxide Semiconductor". CCD is an abbreviation for "Charge Coupled Device". I / F is an abbreviation for "Interface". RAM is an abbreviation for "Random Access Memory". CPU is an abbreviation for "Central Processing Unit". GPU is an abbreviation for "Graphics Processing Unit". EEPROM is an abbreviation for "Electrically Erasable and Programmable Read Only Memory". HDD is an abbreviation for "Hard Disk Drive". TPU is an abbreviation for "Tensor processing unit". SSD is an abbreviation for "Solid State Drive". USB is an abbreviation for "Universal Serial Bus." ASIC is an abbreviation for "Application Specific Integrated Circuit." FPGA is an abbreviation for "Field-Programmable Gate Array." PLD is an abbreviation for "Programmable Logic Device." SoC is an abbreviation for "System-on-a-Chip." IC is an abbreviation for "Integrated Circuit."

[0032] In the description of this specification, "uniform" refers to "uniform" in the sense of including, in addition to completely "uniform," an error that is generally acceptable in the technical field to which the technology of the present disclosure belongs and that does not violate the spirit of the technology of the present disclosure. In the description of this specification, "same" refers to "same" in the sense of including, in addition to completely "same," an error that is generally acceptable in the technical field to which the technology of the present disclosure belongs and that does not violate the spirit of the technology of the present disclosure. In the description of this specification, "orthogonal" refers to "orthogonal" in the sense of including, in addition to completely "orthogonal," an error that is generally acceptable in the technical field to which the technology of the present disclosure belongs and that does not violate the spirit of the technology of the present disclosure. In the description of this specification, "straight line" refers to "straight line" in the sense of including, in addition to completely "straight line," an error that is generally acceptable in the technical field to which the technology of the present disclosure belongs and that does not violate the spirit of the technology of the present disclosure.

[0033] First, a comparative example of this embodiment will be described.

[0034] 18 shows an example of a color measurement method according to a first comparative example. The image capture device 200 used in the color measurement method according to the first comparative example is an RGB camera. An RGB camera is a camera capable of generating wavelength band images in each of the red, green, and blue wavelength bands.

[0035] 18 , the color of the subject 2 is measured in the following manner. That is, first, as shown in mode I, light source 202 irradiates light L8 onto a white reference plate 204 (hereinafter referred to as "white reference plate 204"), and incident light Lb including light L9 reflected by the white reference plate 204 is captured by imaging device 200. As a result, a reference image 220 is obtained. Next, as shown in mode J, light source 202 irradiates light L8 onto the subject 2, and incident light Lb including light L10 reflected by the subject 2 is captured by imaging device 200. As a result, a subject image 222 is obtained.

[0036] Then, in a processing device 210 communicably connected to the imaging device 200, calibration of the subject image 222 is performed based on the reference image 220, thereby generating a calibration image 224, and measuring the color of the subject 2 based on the calibration image 224. As a result, a color measurement result 226, which is the result of measuring the color of the subject 2, is obtained.

[0037] In the color measurement method of the first comparative example, even if, for example, there is unevenness in the light L8 irradiated from the light source 202 or the amount of light around the imaging device 200 is reduced, the subject image 222 is calibrated based on the reference image 220, and the color of the subject 2 is measured while eliminating the effects of unevenness in the light L8 and the effects of reduced light around the imaging device 200.

[0038] However, the color measurement method according to the first comparative example is a method that assumes that the subject 2 is imaged in an ideal imaging environment, and in a real imaging environment, external light other than the light L8 emitted from the light source 202 and the like have an effect.

[0039] 19 shows an example of a color measurement method according to a second comparative example. In the color measurement method according to the second comparative example, a housing 206 is used to prevent ambient light and the like from affecting the imaging environment. The housing 206 is configured to cover an imaging space 208. A light source 202, an incident portion 200A of the imaging device 200, and a subject 2 are arranged in the imaging space 208. The inner surfaces of the housing 206 (i.e., a bottom surface 206A, a side surface 206B, and a top surface 206C) are white.

[0040] In the color measurement method according to the second comparative example, the color of the subject 2 is measured in the following manner. That is, first, as shown in aspect K, light source 202 irradiates bottom surface 206A with light L8, and incident light Lb including light L11 reflected by bottom surface 206A is captured by imaging device 200. As a result, reference image 220 is obtained. Next, as shown in aspect L, subject 2 is placed on bottom surface 206A, light source 202 irradiates subject 2 with light L8, and incident light Lb including light L12 reflected by subject 2 is captured by imaging device 200. As a result, subject image 222 is obtained.

[0041] Then, in a processing device 210 communicably connected to the imaging device 200, calibration of the subject image 222 is performed based on the reference image 220, thereby generating a calibration image 224, and measuring the color of the subject 2 based on the calibration image 224. As a result, a color measurement result 226, which is the result of measuring the color of the subject 2, is obtained.

[0042] 20 illustrates a problem with the color measurement method according to the second comparative example. In the color measurement method according to the second comparative example, when a reference image 220 is obtained as shown in aspect M, the incident light Lb includes light L13 that is irradiated from the light source 202 onto the bottom surface 206A, reflected by the bottom surface 206A and the top surface 206C, and then reflected again by the bottom surface 206A. On the other hand, when a subject image 222 is obtained as shown in aspect N, the incident light Lb includes light L14 that is irradiated from the light source 202 onto the subject 2, reflected by the subject 2 and the top surface 206C, and then reflected again by the subject 2 (hereinafter referred to as "re-reflected light L14"). Because the re-reflected light L14 is light that is reflected twice by the subject 2, in aspect N, the color of the subject 2 is measured as darker than the actual color of the subject 2.

[0043] Furthermore, in the color measurement method according to the second comparative example, as shown in aspect O, when a subject image 222 is obtained, the incident light Lb includes not only light L15 that is irradiated from the light source 202 onto the subject 2 and reflected by the subject 2, but also light L16 that is reflected from the area of ​​the bottom surface 206A surrounding the subject 2 (hereinafter referred to as "ambient reflected light L16"). Therefore, in the case of aspect O, the inclusion of the ambient reflected light L16 in the incident light Lb may cause the color of the subject 2 to be measured as lighter than the actual color of the subject 2, or flare may occur due to the ambient reflected light L16.

[0044] As such, the color measurement method of the second comparative example has the problem that the measurement accuracy for the color of the subject 2 is reduced compared to the color measurement method of the first comparative example, because the incident light Lb changes between when the subject 2 is not present and when the subject 2 is present.

[0045] The inventors conducted extensive research into multispectral cameras instead of RGB cameras and found that the same problems as those of the RGB cameras described above also occur with multispectral cameras. The multispectral camera referred to here refers to a camera capable of generating spectral images in each wavelength range of a spectral filter. The present embodiment described below provides, as an example, a color measurement method that can solve the above problems when using a multispectral camera.

[0046] Next, the present embodiment will be described.

[0047] 1 shows a color measurement device 110 according to this embodiment. The color measurement device 110 includes a light source 112, a housing 114, a calibration member 116, an image capture device 10, and a processing device 90.

[0048] The light source 112 is, for example, an LED light source, a laser light source, an incandescent light bulb, etc. The light emitted from the light source 112 is unpolarized. The light source 112 is, for example, disposed at an upper portion inside the housing 114.

[0049] The housing 114 is configured to cover the imaging space 118. The light source 112, the calibration member 116, the incident portion 10A of the imaging device 10, and the subject 2 are arranged in the imaging space 118. The inner surfaces of the housing 114 (i.e., the bottom surface 114A, the side surface 114B, and the top surface 114C) are white. In this specification, white is defined as the color perceived by a person viewing the surface of an object when all colors of visible light are diffusely reflected by the object. The inner surface of the housing 114 has light diffusing properties that diffuse light. The housing 114 is an example of a "housing" according to the technology of the present disclosure.

[0050] As an example, the calibration member 116 is a plate material that is rectangular in plan view. The calibration member 116 is disposed on the bottom surface 114A. Here, an example is given in which the calibration member 116 is a plate material, but the shape of the calibration member 116 may be a shape other than a plate. The calibration member 116 and the housing 114 constitute a housing device 120. The housing device 120 may include a light source 112. The calibration member 116 is an example of a "calibration member" according to the technology of the present disclosure. The housing device 120 is an example of a "housing device" according to the technology of the present disclosure.

[0051] The calibration member 116 has a background surface 116A. The background surface 116A is the surface facing the imaging device 10 (i.e., the upper surface). The subject 2 is placed on the background surface 116A. The subject 2 may be of any type. Furthermore, the color of the subject 2 may be any color. In the following, an example will be described in which the color of the subject 2 is a color other than white.

[0052] The background surface 116A forms the background of the subject 2 when the subject 2 is placed on the calibration member 116. As will be described in detail later, the background surface 116A has a color that corresponds to the color of the subject 2. The surfaces of the calibration member 116 other than the background surface 116A may be the same color as the background surface 116A, or may be a color different from the background surface 116A. The following description will be given taking as an example a case where the surfaces of the calibration member 116 other than the background surface 116A are the same color as the background surface 116A.

[0053] Furthermore, background surface 116A has a surface roughness that corresponds to that of subject 2. The surface roughness may be adjusted by processing background surface 116A or by changing the size of the particles that form background surface 116A. By having background surface 116A have a surface roughness that corresponds to that of subject 2, the directionality of light reflected by background surface 116A can be matched to the directionality of light reflected by subject 2.

[0054] The imaging device 10 is, for example, a multispectral camera. Here, an example in which the imaging device 10 is a multispectral camera is given, but the imaging device 10 may also be a spectral camera such as a hyperspectral camera. The following description will be given using an example in which the imaging device 10 is a multispectral camera. The imaging device 10 is an example of a "spectral imaging device" according to the technology of the present disclosure.

[0055] The imaging device 10 includes an optical system 26 and an image sensor 28. The optical system 26 includes a first lens 30, a pupil division filter 16, and a second lens 32. The first lens 30, the pupil division filter 16, and the second lens 32 are arranged in this order along the optical axis OA of the optical system 26, from the subject 2 side to the image sensor 28 side.

[0056] The pupil division filter 16 has spectral filters 20A to 20C. Each of the spectral filters 20A to 20C is a bandpass filter that transmits light in a specific wavelength range. The spectral filters 20A to 20C have different wavelength ranges. Specifically, the spectral filter 20A transmits light in a first wavelength range λ １ and the spectral filter 20B has a second wavelength range λ ２ and the spectral filter 20C has a third wavelength range λ ３ The spectral filter is an example of a "spectral filter" according to the technology of the present disclosure.

[0057] Hereinafter, when there is no need to distinguish between the spectral filters 20A to 20C, each of the spectral filters 20A to 20C will be referred to as a "spectral filter 20." The spectral filter 20 is an example of a "spectral filter" according to the technology of the present disclosure. １ , second wavelength range λ ２ , and the third wavelength region λ ３ When there is no need to distinguish between the first wavelength region λ １ , second wavelength range λ ２ , and the third wavelength region λ ３ are referred to as "wavelength range λ."

[0058] As will be described in detail later, the imaging device 10 generates spectral images 72A to 72C corresponding to the respective wavelength ranges λ based on a captured image (not shown) obtained by capturing an image of the subject 2. The spectral image 72A is generated in the first wavelength range λ １ The spectral image 72B corresponds to the second wavelength range λ ２ The spectral image 72C corresponds to the third wavelength range λ ３ Hereinafter, when there is no need to distinguish between the spectral images 72A to 72C, each of the spectral images 72A to 72C will be referred to as a "spectral image 72."

[0059] In this embodiment, as an example, a case will be described in which three spectral images 72 are generated based on light dispersed into three wavelength ranges λ. However, three wavelength ranges λ are merely an example, and the present invention can be applied to two or more wavelength ranges λ.

[0060] The imaging device 10 has a zoom function. When the subject 2 is imaged by the imaging device 10, the angle of view of the imaging device 10 is adjusted by the zoom function. The angle of view of the imaging device 10 is set to an angle of view in which the imaging range of the imaging device 10 is filled with the subject 2 and the calibration member 116. By adjusting the angle of view in this manner, the imaging conditions when the subject 2 is imaged by the imaging device 10 are set to specific conditions under which a main component of light incident on the imaging device 10 (hereinafter referred to as "incident light") becomes light irradiated from the light source 112 and reflected by the subject 2 and the calibration member 116. The main component is an example of a "first component" according to the technology of the present disclosure. The specific condition is an example of a "first condition" according to the technology of the present disclosure.

[0061] The processing device 90 is communicatively connected to the imaging device 10. The processing device 90 is, for example, an information processing device such as a personal computer or a server. The processing device 90 includes a display device 108. The display device 108 is, for example, a liquid crystal display or an EL display. The processing device 90 generates a multispectral image 74 based on the plurality of spectral images 72 and displays the generated multispectral image 74 on the display device 108. Furthermore, as will be described in detail later, the processing device 90 measures the color of the subject 2 based on the plurality of spectral images 72 and displays a color measurement result 136, which is the measurement result, on the display device 108.

[0062] 2 shows a graph illustrating an example of the spectral reflectance of the white reference plate 122, the calibration member 116, and the subject 2. The white reference plate 122 has a reflective surface 122A that reflects light. The white reference plate 122 is a white plate material, and the reflective surface 122A is a white surface. The reflective surface 122A is formed of a uniform white color. Similarly, the background surface 116A is formed of a uniform color.

[0063] Graph G1 is a graph showing a first spectral reflectance a, which is the spectral reflectance of light reflected by the subject 2. Graph G2 is a graph showing a second spectral reflectance b, which is the spectral reflectance of light reflected by the background surface 116A of the calibration member 116. Graph G3 is a graph showing a third spectral reflectance c, which is the spectral reflectance of light reflected by the reflective surface 122A of the white reference plate 122. The first spectral reflectance a is an example of the "first spectral reflectance" according to the technology of the present disclosure. The second spectral reflectance b is an example of the "second spectral reflectance" according to the technology of the present disclosure. The third spectral reflectance c is an example of the "third spectral reflectance" according to the technology of the present disclosure.

[0064] For example, the first spectral reflectance a may be a spectral reflectance based on the spectral reflectance measured at multiple locations on the subject 2. When the first spectral reflectance a is a spectral reflectance based on the spectral reflectance measured at multiple locations on the subject 2, the accuracy of the first spectral reflectance a is improved compared to when the first spectral reflectance a is a spectral reflectance measured at one location on the subject 2. The first spectral reflectance a may be an average value of the spectral reflectances measured at multiple locations on the subject 2, or a representative value (e.g., the highest value, the median value, or the lowest value). The number of multiple locations may be any number. Furthermore, the locations of the multiple locations may be anywhere on the subject 2. The subject 2 may be multiple objects. Each location may be a location on each of the subject 2. The first spectral reflectance a may be a spectral reflectance measured at one location on the subject 2.

[0065] Furthermore, for example, the second spectral reflectance b may be a spectral reflectance based on the spectral reflectance measured at multiple locations on the background surface 116A. Similarly, the third spectral reflectance c may be a spectral reflectance based on the spectral reflectance measured at multiple locations on the reflecting surface 122A.

[0066] FIG. 2 shows the first wavelength range λ １ and the second wavelength region λ ２ 1 shows an example of the relationship between the first spectral reflectance a and the second spectral reflectance b for the first wavelength range λ １ The first spectral reflectance a in the first wavelength range λ may be an average value or a representative value (for example, a maximum value, a median value, or a minimum value). １The second spectral reflectance b in the second wavelength range λ may be an average value or a representative value (for example, a maximum value, a central value, or a minimum value). ２ The first spectral reflectance a in the second wavelength range λ may be an average value or a representative value (for example, a maximum value, a median value, or a minimum value). ２ The second spectral reflectance b in may be an average value or a representative value (for example, a maximum value, a median value, or a minimum value).

[0067] Since the background surface 116A has a color corresponding to the color of the subject 2, the second spectral reflectance b corresponds to the first spectral reflectance a. Specifically, in the example shown in FIG. 2, the first wavelength range λ １ In the second wavelength range λ, the first spectral reflectance a and the second spectral reflectance b have a relationship with each other. ２ In the above equation, the first spectral reflectance a and the second spectral reflectance b have a relationship with each other.

[0068] Here, the first wavelength range λ １ and the second wavelength range λ ２ In the example, the first spectral reflectance a and the second spectral reflectance b have a relationship with each other, but the first spectral reflectance a and the second spectral reflectance b are in the second wavelength range λ ２ and the third wavelength region λ ３ (See FIG. 1 ). Hereinafter, the first wavelength range λ １ and the second wavelength range λ ２ In the following description, an example will be given in which the first spectral reflectance a and the second spectral reflectance b have a relationship with each other.

[0069] First wavelength range λ １ In the above, as an example of the relationship between the first spectral reflectance a and the second spectral reflectance b, the difference between the first spectral reflectance a and the second spectral reflectance b is within a first range (not shown). ２ In the above, an example of the first spectral reflectance a and the second spectral reflectance b having a relationship to each other is when the difference between the first spectral reflectance a and the second spectral reflectance b is within a first range.

[0070] The first range is set based on, for example, the third spectral reflectance c. Specifically, the first range is set as a range of spectral reflectances lower than the third spectral reflectance c. The first range is, for example, a range from 0.5 times the first spectral reflectance a to 2 times the reflectance a. That is, the lower limit of the first range is 0.5 times the first spectral reflectance a, and the upper limit of the first range is 2 times the first spectral reflectance a. For example, if the lower limit of the first range is set to less than 0.5 times the first spectral reflectance a, the first spectral reflectance a and the second spectral reflectance b will no longer have a relationship. Furthermore, for example, if the upper limit of the first range is set to a reflectance greater than 2 times the first spectral reflectance a, the first spectral reflectance a and the second spectral reflectance b will no longer have a relationship.

[0071] In addition, the first wavelength range λ １ and the second wavelength range λ ２ In the first wavelength range λ, there is a difference between the first spectral reflectance a and the second spectral reflectance b. １ and the second wavelength range λ ２ In the first wavelength range λ, the second spectral reflectance b may be higher than the first spectral reflectance a, or may be lower than the first spectral reflectance a. １ and the second wavelength range λ ２ In the first wavelength range λ, the difference between the first spectral reflectance a and the second spectral reflectance b is smaller than the difference between the first spectral reflectance a and the third spectral reflectance c. １ and the second wavelength range λ ２ In this case, the first spectral reflectance a and the second spectral reflectance b are lower than the third spectral reflectance c.

[0072] In addition, the first wavelength range λ １ and the second wavelength range λ ２ In the formula (1), the second spectral reflectance b falls within a second range of spectral reflectances set based on the first spectral reflectance a and the third spectral reflectance c. For example, the second range is a range defined by formula (1). In FIG. 2, the second range defined by formula (1) is shown as second range R1: a / 2≦b≦(c+a) / 2 (1)

[0073] According to formula (1), the lower limit of the second range R1 is defined as half the value of the first spectral reflectance a, and the upper limit of the second range R1 is defined as half the value of the sum of the third spectral reflectance c and the first spectral reflectance a. In this case, the influence of the second spectral reflectance b on color measurement error can be reduced by half compared to when the lower limit of the second range R1 is defined by the first spectral reflectance a and the upper limit of the second range R1 is defined as the sum of the third spectral reflectance c and the first spectral reflectance a. For example, when the third spectral reflectance c is 1 and the first spectral reflectance a is 0.1, the lower limit of the second range R1 is 0.05 and the upper limit of the second range R1 is 0.55.

[0074] Furthermore, for example, the second range is more preferably the range defined by formula (2). In FIG. 2, the second range defined by formula (2) is shown as second range R2: 3a / 4≦b≦(c+3a) / 4 (2)

[0075] According to equation (2), the lower limit of the second range R2 is defined as ¾ of the first spectral reflectance a, and the upper limit of the second range R2 is defined as ¼ of the sum of the third spectral reflectance c and a spectral reflectance three times the first spectral reflectance a. In this case, the influence of the second spectral reflectance b on color measurement error can be reduced to ¼ compared to when the lower limit of the second range R2 is defined by the first spectral reflectance a and the upper limit of the second range R2 is defined as the sum of the third spectral reflectance c and the first spectral reflectance a. For example, if the third spectral reflectance c is 1 and the first spectral reflectance a is 0.1, the lower limit of the second range R2 is 0.075 and the upper limit of the second range R2 is 0.325.

[0076] 3 and 4 are graphs schematically illustrating examples of the second spectral reflectance b. As an example, as shown in graph G4 of Fig. 3 and graph G5 of Fig. 4, the second spectral reflectance b may be higher in the first near-infrared range of the near-infrared range than in the first visible range of the visible range.

[0077] The first visible range may be the entire wavelength range of the visible range or a part of the wavelength range. Similarly, the first near-infrared range may be the entire wavelength range of the near-infrared range or a part of the wavelength range. The visible range and the near-infrared range may be continuous, separated, or partially overlapping.

[0078] In the example shown in Fig. 3, the second spectral reflectance b increases linearly (i.e., continuously) from a specific wavelength as the wavelength increases, and has a peak in the first near-infrared range. In the example shown in Fig. 4, the second spectral reflectance b increases nonlinearly (i.e., discontinuously) at a specific wavelength, and has a peak in the first near-infrared range.

[0079] 3 and 4 , when the second spectral reflectance b has a peak in the first near-infrared range, for example, when the subject 2 is a subject that exhibits a higher spectral reflectance in the near-infrared range than in the visible range, such as a plant, the accuracy of measuring the color of the subject 2 can be improved. That is, the accuracy of measuring the color of the subject 2 is improved compared to when the second spectral reflectance b is the same in the first visible range and the first near-infrared range.

[0080] 5 shows an example of the flow of a method for setting the color of the background surface 116A (hereinafter referred to as the "color setting method"). In the color setting method shown in FIG. 5, first, as shown in step A, the subject 2 is imaged by the imaging device 124. This results in a captured image 126. The imaging device 124 used to image the subject 2 may be a multispectral camera or an RGB camera. Furthermore, the member 128 placed on the back of the subject 2 may be any type.

[0081] Next, as shown in step B, a first spectral reflectance a is measured based on the captured image 126. The first spectral reflectance a may be a spectral reflectance based on the spectral reflectances measured at multiple locations on the subject 2. Alternatively, the first spectral reflectance a may be an average value of the spectral reflectances measured at multiple locations on the subject 2, or may be a representative value (e.g., the highest value, the median value, or the lowest value).

[0082] Next, as shown in step C, a second spectral reflectance b corresponding to the first spectral reflectance a is determined based on the first spectral reflectance a. Then, the color having the second spectral reflectance b is set as the color of the background surface 116A.

[0083] An example of a color measurement method according to this embodiment is shown in Fig. 6. The color measurement method according to this embodiment uses the color measurement device 110 described above.

[0084] In the color measurement method according to this embodiment, the color of the subject 2 is measured in the following manner. That is, first, as shown in aspect D, with the calibration member 116 placed on the bottom surface 114A of the housing 114, light L1 is irradiated from the light source 112 onto the background surface 116A, and incident light La, including light L2 reflected by the background surface 116A, is captured by the imaging device 10. This results in a reference image 130. Next, as shown in aspect E, the subject 2 is placed on the background surface 116A, light L1 is irradiated from the light source 112 onto the subject 2, and incident light La, including light L3 reflected by the subject 2, is captured by the imaging device 10. This results in a subject image 132.

[0085] Then, in a processing device 90 communicably connected to the imaging device 10, calibration of the subject image 132 is performed based on the reference image 130, thereby generating a calibration image 134, and measuring the color of the subject 2 based on the calibration image 134. As a result, a color measurement result 136, which is the result of measuring the color of the subject 2, is obtained.

[0086] 7 shows an example of a specific aspect of incident light La incident on imaging device 10 in the color measurement method according to this embodiment. In the color measurement method according to this embodiment, when reference image 130 is obtained as shown in aspect F, incident light La includes light L4 that is irradiated from light source 112 onto background surface 116A, reflected by background surface 116A and top surface 114C, and then reflected again by background surface 116A. In addition, in the color measurement method according to this embodiment, when subject image 132 is obtained as shown in aspect G, incident light La includes light L5 that is irradiated from light source 112 onto subject 2, reflected by subject 2 and top surface 114C, and then reflected again by subject 2.

[0087] Here, the second spectral reflectance b, which is the spectral reflectance of the background surface 116A, corresponds to the first spectral reflectance a, which is the spectral reflectance of the subject 2. Therefore, the wavelength range of the incident light La is prevented from changing between when the subject 2 is present and when it is not present. This makes it possible to avoid measuring the color of the subject 2 as darker than the actual color of the subject 2, as occurs in the color measurement method according to the second comparative example (see aspect N in FIG. 20 ).

[0088] Furthermore, in the color measurement method according to this embodiment, as shown in aspect H, when a subject image 132 is obtained, the incident light La includes not only light L6 irradiated from the light source 112 onto the subject 2 and reflected by the subject 2, but also light L7 irradiated from the light source 112 onto the subject 2 and reflected by the area of ​​the background surface 116A surrounding the subject 2 (hereinafter referred to as "ambient reflected light L7").

[0089] As described above, the second spectral reflectance b, which is the spectral reflectance of the background surface 116A, corresponds to the first spectral reflectance a, which is the spectral reflectance of the subject 2. Therefore, the wavelength range of the ambient reflected light L7 is prevented from changing between when the subject 2 is present and when it is not present. This makes it possible to avoid the color of the subject 2 being measured as lighter than the actual color of the subject 2 or the amount of flare changing, as occurs in the color measurement method according to the second comparative example (see aspect O in FIG. 20 ).

[0090] Next, the imaging device 10 according to this embodiment will be described in detail.

[0091] 8 , an image capture device 10 includes a lens device 12 and an image capture device body 14. The lens device 12 has the above-described pupil division filter 16. The image capture device 10 is a multispectral camera that captures light that has been dispersed into multiple wavelength bands λ by the pupil division filter 16, thereby generating and outputting multiple spectral images 72A-72C.

[0092] As an example, as shown in FIG. 9, the pupil division filter 16 has a frame 18, spectral filters 20A to 20C, and polarizing filters 22A to 22C.

[0093] The frame 18 has openings 24A to 24C. The openings 24A to 24C are formed in a line around the optical axis OA. Hereinafter, when there is no need to distinguish between the openings 24A to 24C, each of the openings 24A to 24C will be referred to as an "opening 24." The spectral filters 20A to 20C are provided in the openings 24A to 24C, respectively, and are thereby arranged in a line around the optical axis OA.

[0094] Polarizing filters 22A to 22C are provided corresponding to spectral filters 20A to 20C, respectively. Specifically, polarizing filter 22A is provided in opening 24A and overlaps spectral filter 20A. Polarizing filter 22B is provided in opening 24B and overlaps spectral filter 20B. Polarizing filter 22C is provided in opening 24C and overlaps spectral filter 20C.

[0095] Each of the polarizing filters 22A to 22C is an optical filter that transmits light that vibrates in a specific direction. The polarizing filters 22A to 22C have polarization axes with different polarization angles. Specifically, the polarizing filter 22A has a first polarization angle α １ and the polarizing filter 22B has a second polarization angle α ２ and the polarizing filter 22C has a third polarization angle α ３ The polarization axis may be referred to as a transmission axis. For example, the first polarization angle α １ is set to 0°, and the second polarization angle α ２ is set to 45°, and the third polarization angle α ３ is set to 90°.

[0096] Hereinafter, when there is no need to distinguish between the polarizing filters 22A to 22C, each of the polarizing filters 22A to 22C will be referred to as a "polarizing filter 22." １ , the second polarization angle α ２ , and the third polarization angle α ３ When it is not necessary to distinguish between the first polarization angle α １ , the second polarization angle α ２ , and the third polarization angle α ３ are referred to as "polarization angles α."

[0097] 9, the number of the openings 24 is three, corresponding to the number of the wavelength bands λ, but the number of the openings 24 may be greater than the number of the wavelength bands λ (i.e., the number of the spectral filters 20). Furthermore, unused openings 24 of the openings 24 may be blocked by a shielding member (not shown). Furthermore, although the spectral filters 20 have different wavelength bands λ in the example shown in FIG. 9, the spectral filters 20 may include spectral filters 20 having the same wavelength band λ.

[0098] 10 , the lens device 12 includes an optical system 26, and the imaging device body 14 includes an image sensor 28. The optical system 26 includes the pupil division filter 16, a first lens 30, and a second lens 32.

[0099] The first lens 30 causes light emitted from the light source 112 and reflected by the subject 2 to be incident on the pupil division filter 16. The second lens 32 causes the light that has passed through the pupil division filter 16 to form an image on the light receiving surface 34A of the photoelectric conversion element 34 provided in the image sensor 28.

[0100] The pupil division filter 16 is disposed at the pupil position of the optical system 26. The pupil position refers to the diaphragm surface that limits the brightness of the optical system 26. The pupil position here includes nearby positions, and nearby positions refer to the range from the entrance pupil to the exit pupil. The configuration of the pupil division filter 16 is as described using Figure 9. For convenience, Figure 10 shows a state in which a plurality of spectral filters 20 and a plurality of polarizing filters 22 are linearly arranged in a direction perpendicular to the optical axis OA.

[0101] The image sensor 28 includes a photoelectric conversion element 34 and a signal processing circuit 36. The image sensor 28 is, for example, a CMOS image sensor. In the present embodiment, a CMOS image sensor is used as the image sensor 28, but the technology of the present disclosure is not limited thereto. For example, the technology of the present disclosure can be applied even if the image sensor 28 is another type of image sensor, such as a CCD image sensor.

[0102] As an example, Fig. 10 shows a schematic configuration of a photoelectric conversion element 34. Also, as an example, Fig. 11 specifically shows the configuration of a portion of the photoelectric conversion element 34. The photoelectric conversion element 34 has a pixel layer 38, a polarizing filter layer 40, and a spectral filter layer 42. Note that the configuration of the photoelectric conversion element 34 shown in Fig. 11 is just an example, and the technology of the present disclosure is applicable even if the photoelectric conversion element 34 does not have the spectral filter layer 42.

[0103] The pixel layer 38 has a plurality of pixels 44. The plurality of pixels 44 are arranged in a matrix and form the light receiving surface 34A of the photoelectric conversion element 34. Each pixel 44 is a physical pixel having a photodiode (not shown), which photoelectrically converts received light and outputs an electrical signal according to the amount of received light.

[0104] Hereinafter, the pixels 44 provided in the photoelectric conversion element 34 will be referred to as "physical pixels 44" to distinguish them from pixels that form the spectral image. Also, the pixels that form the spectral image 72 will be referred to as "image pixels."

[0105] The photoelectric conversion element 34 outputs the electrical signals output from the plurality of physical pixels 44 as imaging data to the signal processing circuit 36. The signal processing circuit 36 ​​digitizes the analog imaging data input from the photoelectric conversion element 34. The imaging data is image data representing a captured image 70.

[0106] The plurality of physical pixels 44 form a plurality of pixel blocks 46. Each pixel block 46 is formed by two vertical and two horizontal rows, for a total of four physical pixels 44. For convenience, in Fig. 10, the four physical pixels 44 forming each pixel block 46 are shown as being linearly arranged in a direction perpendicular to the optical axis OA, but the four physical pixels 44 are arranged adjacent to each other in the vertical and horizontal directions of the photoelectric conversion element 34 (see Fig. 11).

[0107] The polarizing filter layer 40 has multiple types of polarizers 48A to 48D. Each of the polarizers 48A to 48D is an optical filter that transmits light vibrating in a specific direction. The polarizers 48A to 48D have polarization axes with different polarization angles. Specifically, the polarizer 48A has a first polarization angle θ １and the polarizer 48B has a second polarization angle θ ２ and the polarizer 48C has a third polarization angle θ ３ and the polarizer 48D has a fourth polarization angle θ ４ As an example, the first polarization angle θ １ is set to 0°, and the second polarization angle θ ２ is set to 45°, and the third polarization angle θ ３ is set to 90°, and the fourth polarization angle θ ４ is set to 135°.

[0108] Hereinafter, when there is no need to distinguish between the polarizers 48A to 48D, the polarizers 48A to 48D will be referred to as "polarizers 48." The polarizer 48 is an example of a "polarizer" according to the technology of the present disclosure. In addition, the first polarization angle θ １ , second polarization angle θ ２ , third polarization angle θ ３ , and the fourth polarization angle θ ４ When there is no need to distinguish between the first polarization angle θ １ , second polarization angle θ ２ , third polarization angle θ ３ , and the fourth polarization angle θ ４ are referred to as "polarization angle θ."

[0109] The spectral filter layer 42 has a B filter 50A, a G filter 50B, and an R filter 50C. The B filter 50A is a blue-pass filter that transmits the most light in the blue wavelength range among light in a plurality of wavelength ranges. The G filter 50B is a green-pass filter that transmits the most light in the green wavelength range among light in a plurality of wavelength ranges. The R filter 50C is a red-pass filter that transmits the most light in the red wavelength range among light in a plurality of wavelength ranges. The B filter 50A, G filter 50B, and R filter 50C are assigned to each pixel block 46.

[0110] For convenience, Fig. 10 shows the B filter 50A, G filter 50B, and R filter 50C arranged in a line along a direction perpendicular to the optical axis OA, but as an example, as shown in Fig. 11, the B filter 50A, G filter 50B, and R filter 50C are arranged in a matrix in a predetermined pattern arrangement. In the example shown in Fig. 11, the B filter 50A, G filter 50B, and R filter 50C are arranged in a matrix in a Bayer array, which is an example of a predetermined pattern arrangement. Note that the predetermined pattern arrangement may be an RGB stripe array, an R / G checkerboard array, an X-Trans (registered trademark) array, a honeycomb array, or the like, in addition to the Bayer array.

[0111] Hereinafter, when it is not necessary to distinguish between the B filter 50A, the G filter 50B, and the R filter 50C, they will each be referred to as "filters 50."

[0112] 10 , the imaging device body 14 includes, in addition to the image sensor 28, a control driver 52, an input / output I / F 54, a computer 56, and a communication device 58. The signal processing circuit 36, the control driver 52, the computer 56, and the communication device 58 are connected to the input / output I / F 54.

[0113] The computer 56 has a processor 60, a storage 62, and a RAM 64. The processor 60 controls the entire imaging device 10. The processor 60 is, for example, an arithmetic processing device including a CPU and a GPU, and the GPU operates under the control of the CPU and is responsible for executing image-related processing. Here, an arithmetic processing device including a CPU and a GPU is given as an example of the processor 60, but this is merely one example, and the processor 60 may be one or more CPUs that integrate a GPU function, or one or more CPUs that do not integrate a GPU function.

[0114] The processor 60, storage 62, and RAM 64 are connected via a bus 66, which is connected to the input / output I / F 54. The storage 62 is a non-transitory storage medium and stores various parameters and programs. For example, the storage 62 is a flash memory (e.g., an EEPROM). However, this is merely an example, and an HDD or the like may also be used as the storage 62 in addition to the flash memory. The RAM 64 temporarily stores various information and is used as a work memory. Examples of the RAM 64 include a DRAM and / or an SRAM.

[0115] The processor 60 reads out a necessary program from the storage 62 and executes the read program on the RAM 64. The processor 60 controls the control driver 52 and the signal processing circuit 36 ​​in accordance with the program executed on the RAM 64. The control driver 52 controls the photoelectric conversion element 34 under the control of the processor 60.

[0116] The communication device 58 is connected to the processor 60 via the input / output I / F 54 and the bus 66. The communication device 58 is also connected to the processing device 90 so as to be able to communicate with it via a wired or wireless connection. The communication device 58 is responsible for exchanging information with the processing device 90. For example, the communication device 58 transmits data to the processing device 90 in response to a request from the processor 60. The communication device 58 also receives data transmitted from the processing device 90 and outputs the received data to the processor 60 via the bus 66.

[0117] 12 , a spectral image generation program 80 is stored in the storage 62. The processor 60 reads the spectral image generation program 80 from the storage 62 and executes the read spectral image generation program 80 on the RAM 64. The processor 60 executes a spectral image generation process for generating a plurality of spectral images 72 in accordance with the spectral image generation program 80 executed on the RAM 64. The spectral image generation process is realized by the processor 60 operating as an output value acquisition unit 82 and an interference removal processing unit 84 in accordance with the spectral image generation program 80.

[0118] 13 , when imaging data output from the image sensor 28 is input to the processor 60, the output value acquisition unit 82 acquires an output value Y of each physical pixel 44 based on the imaging data. The output value Y of each physical pixel 44 corresponds to the luminance value of each pixel included in the captured image 70 represented by the imaging data.

[0119] Here, the output value Y of each physical pixel 44 is a value including interference (i.e., crosstalk). １ , second wavelength range λ ２ , and the third wavelength region λ ３ Since light in each wavelength range λ is incident, the output value Y is １ A value according to the amount of light in the second wavelength region λ ２ and the third wavelength range λ ３ The value is a mixture of values ​​according to the amount of light.

[0120] To obtain the spectral image 72, the processor 60 needs to perform a process of separating and extracting values ​​corresponding to each wavelength range λ from the output value Y for each physical pixel 44, that is, an interference removal process that removes interference, on the output value Y. Therefore, in this embodiment, to obtain the spectral image 72, the interference removal processing unit 84 performs the interference removal process on the output value Y of each physical pixel 44 acquired by the output value acquisition unit 82.

[0121] Here, the interference removal process will be described. The output value Y of each physical pixel 44 includes, for red, green, and blue, the luminance values ​​for each polarization angle θ as components of the output value Y. The output value Y of each physical pixel 44 is expressed by equation (3).

[0122] However, Y θ１＿Ｒ is the red output value Y, and the polarization angle is the first polarization angle θ １ The luminance value of the component, Y θ２＿Ｒ is the red output value Y, and the polarization angle is the second polarization angle θ ２ The luminance value of the component, Y θ３＿Ｒ is the red output value Y, and the polarization angle is the third polarization angle θ ３The luminance value of the component, Y θ４＿Ｒ is the output value Y of red, and the polarization angle is the fourth polarization angle θ ４ is the luminance value of the component.

[0123] Also, Y θ１＿Ｇ is the green output value Y, and the polarization angle is the first polarization angle θ １ The luminance value of the component, Y θ２＿Ｇ is the green output value Y, and the polarization angle is the second polarization angle θ ２ The luminance value of the component, Y θ３＿Ｇ is the green output value Y, and the polarization angle is the third polarization angle θ ３ The luminance value of the component, Y θ４＿Ｇ is the green output value Y, and the polarization angle is the fourth polarization angle θ ４ is the luminance value of the component.

[0124] Also, Y θ１＿Ｂ is the blue output value Y, and the polarization angle is the first polarization angle θ １ The luminance value of the component, Y θ２＿Ｂ is the blue output value Y, and the polarization angle is the second polarization angle θ ２ The luminance value of the component, Y θ３＿Ｂ is the blue output value Y, and the polarization angle is the third polarization angle θ ３ The luminance value of the component, Y θ４＿Ｂ is the output value Y of blue, and the polarization angle is the fourth polarization angle θ ４ is the luminance value of the component.

[0125] The pixel value X of each image pixel forming the spectral image 72 is determined by the first polarization angle α １ A first wavelength range λ １ The brightness value X of the polarized light (hereinafter referred to as "first wavelength range polarized light") λ１ and the second polarization angle α ２ A second wavelength range λ ２ The brightness value X of the polarized light (hereinafter referred to as "second wavelength range polarized light") λ２ and the third polarization angle α ３ A third wavelength range λ ３ The brightness value X of the polarized light (hereinafter referred to as "third wavelength range polarized light") λ３ and as components of the pixel value X. The pixel value X of each image pixel is expressed by equation (4).

[0126] The output value Y of each physical pixel 44 is expressed by equation (5).

[0127] In equation (5), A is an interference matrix. The interference matrix A (not shown) is a matrix that indicates the characteristics of interference. The interference matrix A is determined in advance based on a plurality of known values, such as the spectrum of the incident light, the spectral transmittance of the first lens 30, the spectral transmittance of the second lens 32, the spectral transmittances of the plurality of spectral filters 20, and the spectral sensitivity of the image sensor 28.

[0128] The interference cancellation matrix, which is the generalized inverse matrix of the interference matrix A, is defined as A ＋ In this case, the pixel value X of each image pixel is expressed by equation (6).

[0129] Interference cancellation matrix A ＋ Similarly to the interference matrix A, the interference cancellation matrix A is a matrix defined based on the spectrum of the incident light, the spectral transmittance of the first lens 30, the spectral transmittance of the second lens 32, the spectral transmittances of the plurality of spectral filters 20, the spectral sensitivity of the image sensor 28, etc. ＋ is stored in advance in the storage 62.

[0130] The interference cancellation processor 84 uses the interference cancellation matrix A stored in the storage 62 ＋ and the output value Y of each physical pixel 44 acquired by the output value acquisition unit 82, and ＋ and the output value Y of each physical pixel 44, the pixel value X of each image pixel is output according to equation (6).

[0131] Here, as described above, the pixel value X of each image pixel is the luminance value X of the first wavelength band polarized light. λ１ and the brightness value X of the second wavelength band polarized light. λ２ and the brightness value X of the third wavelength band polarized light. λ３ and are included as components of the pixel value X.

[0132] The spectral image 72A of the captured image 70 is a spectral image of the first wavelength range λ １ The brightness value of the light X λ１ (i.e., the brightness values ​​X λ１The spectral image 72B of the captured image 70 is an image based on the second wavelength range λ ２ The brightness value of the light X λ２ (i.e., the brightness values ​​X λ２ The spectral image 72C of the captured image 70 is an image based on the third wavelength range λ ３ The brightness value of the light X λ３ (i.e., the brightness values ​​X λ３ (Image based on ).

[0133] In this way, the interference removal processing is performed by the interference removal processing unit 84, and the captured image 70 is converted into a first wavelength band polarized light luminance value X λ１ and a spectral image 72A corresponding to the second wavelength band polarized light intensity value X λ２ and a spectral image 72B corresponding to the third wavelength band polarized light luminance value X λ３ That is, the captured image 70 is separated into spectral images 72 for each wavelength range λ of the plurality of spectral filters 20.

[0134] Next, the processing device 90 according to this embodiment will be described in detail.

[0135] 14, the processing device 90 includes a computer 92. The computer 92 includes a processor 94, a storage 96, and a RAM 98. The processor 94, the storage 96, and the RAM 98 are realized by hardware similar to the above-described processor 60, the storage 62, and the RAM 64 (see FIG. 10).

[0136] A color measurement program 100 is stored in the storage 96. The processor 94 reads the color measurement program 100 from the storage 96 and executes the read color measurement program 100 on the RAM 98. The processor 94 executes a color measurement process to obtain a color measurement result 136 in accordance with the color measurement program 100 executed on the RAM 98. The color measurement process is realized by the processor 94 operating as an image data acquisition unit 102, a calibration image generation unit 104, and a color derivation unit 106 in accordance with the color measurement program 100. The processing device 90 is an example of a "calibration device" and a "color measurement device" according to the technology of the present disclosure. The color measurement program 100 is an example of a "program" according to the technology of the present disclosure.

[0137] 15 , when a reference image 130 is obtained, the imaging device 10 transmits reference image data representing the reference image 130 to the processing device 90. Furthermore, when a subject image 132 is obtained, the imaging device 10 transmits subject image data representing the subject image 132 to the processing device 90. The reference image data is an example of "first imaging data" according to the technology of the present disclosure. The subject image data is an example of "second imaging data" according to the technology of the present disclosure.

[0138] The image data acquisition unit 102 acquires the reference image data received by the processing device 90. Then, the image data acquisition unit 102 acquires the reference image 130 based on the reference image data. The reference image 130 includes a first wavelength band λ １ a spectral image 72A in the second wavelength range λ (hereinafter referred to as the “reference spectral image 72A”), ２ Hereinafter, when there is no need to distinguish between the reference spectral image 72A and the reference spectral image 72B, the reference spectral image 72A and the reference spectral image 72B will be referred to as the "reference spectral image 72."

[0139] The image data acquisition unit 102 also acquires the object image data received by the processing device 90. Then, the image data acquisition unit 102 acquires the object image 132 based on the object image data. The object image 132 includes a first wavelength band λ１ a spectral image 72A (hereinafter referred to as the “subject spectral image 72A”) in the second wavelength range λ ２ The spectral image 72A includes the spectral image 72B of the object (hereinafter referred to as the "object spectral image 72B"). Hereinafter, when there is no need to distinguish between the object spectral image 72A and the object spectral image 72B, the object spectral image 72A and the object spectral image 72B will be referred to as the "object spectral image 72."

[0140] The calibration image generating unit 104 generates a calibration image 134 by performing calibration on the subject image 132 based on the reference image 130. Specifically, the calibration image generating unit 104 generates a calibration image 134 by calibrating the subject image 132 based on the first wavelength band λ １ Similarly, the calibration image generating unit 104 generates a calibration spectral image 134A, which is a calibrated spectral image, by dividing the pixel values ​​of the subject spectral image 72A by the pixel values ​​of the reference spectral image 72A for the second wavelength range λ ２ The pixel values ​​of the subject spectral image 72B are divided by the pixel values ​​of the reference spectral image 72B to generate a calibrated spectral image 134B. In this way, the processing device 90 calibrates the subject image data based on the reference image data.

[0141] The calibration image generating unit 104 may perform calibration on a partial image region of the subject spectral image 72. For example, when the processing device 90 receives an instruction from a user specifying an image region for color measurement (hereinafter referred to as a "user instruction"), the calibration image generating unit 104 may perform calibration on the image region of the subject spectral image 72 that corresponds to the user instruction.

[0142] Furthermore, for example, when an image region including the image of the subject 2 (hereinafter referred to as the "subject image region") is extracted by performing image processing on the subject image 132, the calibration image generation unit 104 may perform calibration on the subject image region of the subject spectral image 72. The calibration image generation unit 104 may also perform calibration on a portion of the subject image region. The image region of the subject spectral image 72 that has been calibrated by the calibration image generation unit 104 corresponds to the calibration spectral image 134A and the calibration spectral image 134B.

[0143] In addition, when a user instruction is accepted by the imaging device 10, the imaging device 10 may transmit to the processing device 90 reference image data indicating the image area in the reference image 130 that corresponds to the user instruction, and subject image data indicating the image area in the subject image 132 that corresponds to the user instruction.

[0144] The color deriving unit 106 calculates the color in the first wavelength range λ generated by the calibration image generating unit 104. １ and a calibration spectral image 134A in the second wavelength range λ ２ The color of the object 2 is derived based on the calibration spectral image 134B. Specifically, the color derivation unit 106 derives the color CL of the object 2 for each image pixel based on equation (7). CL=(X λ１ -X λ２ ) ÷ (X λ１ +X λ２ ) ... (7)

[0145] However, X λ１ is the first wavelength range λ １ is the pixel value X of each image pixel forming the calibration spectral image 134A, and X λ２ is the second wavelength range λ ２ The pixel value X of each image pixel forming the calibration spectral image 134B is then calculated. A color measurement result 136 is then generated based on the colors derived by the color derivation unit 106.

[0146] The color measurement result 136 generated by the color measurement process described above may be displayed on the display device 108 (see FIG. 1) of the processing device 90. Furthermore, measurement data indicating the color measurement result 136 may be transmitted to an external device (not shown) communicatively connected to the processing device 90, and the color measurement result 136 may be used by the external device. Furthermore, the color measurement result 136 may include an image indicating the measured color, or may include numerical values ​​and / or graphs indicating the measured color.

[0147] Next, the operation of this embodiment will be described. First, the spectral image generation process according to this embodiment will be described. Fig. 16 shows an example of the flow of the spectral image generation process according to this embodiment.

[0148] 16 , first, in step ST10, the output value acquisition unit 82 acquires the output value Y of each physical pixel 44 based on the imaging data output from the image sensor 28 (see FIG. 10 ). After the processing of step ST10 is executed, the spectral image generation processing proceeds to step ST12.

[0149] In step ST12, the interference cancellation processor 84 uses the interference cancellation matrix A stored in the storage 62 ＋ and the output value Y of each physical pixel 44 acquired in step ST10 are acquired, and the acquired interference cancellation matrix A ＋ and the output value Y of each physical pixel 44, the pixel value X of each image pixel is output (see FIG. 10). By performing the interference removal process in step ST12, the captured image 70 is converted into the luminance value X of the first wavelength band polarized light. λ１ and a spectral image 72A corresponding to the second wavelength band polarized light intensity value X λ２ and a spectral image 72B corresponding to the third wavelength band polarized light luminance value X λ３ After the processing of step ST12 is executed, the spectral image generation processing ends.

[0150] Next, the color measurement process according to this embodiment will be described. Fig. 17 shows an example of the flow of the color measurement process according to this embodiment.

[0151] 17 , first, in step ST20, the image data acquisition unit 102 acquires reference image data and object image data. Then, the image data acquisition unit 102 acquires the reference image 130 indicated by the reference image data and the object image 132 indicated by the object image data. After the processing of step ST20 is executed, the color measurement processing proceeds to step ST22.

[0152] In step ST22, the calibration image generating unit 104 calibrates the subject image 132 based on the reference image 130 for the reference image 130 and the subject image 132 acquired in step ST20, thereby generating a calibration image 134 (for example, a calibration image in the first wavelength range λ １ and the calibration spectral image 134A in the second wavelength range λ ２ After the process of step ST22 is executed, the color measurement process proceeds to step ST24.

[0153] In step ST24, the color deriving unit 106 calculates the first wavelength range λ generated in step ST22. １ and a calibration spectral image 134A in the second wavelength range λ ２ The color of the subject 2 is derived based on the calibration spectral image 134B and the calibration spectral image 134C. This results in a color measurement result 136. After the process of step ST24 is executed, the color measurement process ends.

[0154] The calibration method and color measurement method described above as the operation of the processing device 90 are examples of a "calibration method" and a "color measurement method" according to the technology of the present disclosure. Step ST20 is an example of a "first acquisition step" and a "second acquisition step" according to the technology of the present disclosure. Step ST22 is an example of a "calibration step" according to the technology of the present disclosure. Step ST24 is an example of a "color measurement step" according to the technology of the present disclosure.

[0155] As described above in detail, in this embodiment, the calibration member 116 is used when measuring the color of the subject 2 (see FIG. 1). The calibration member 116 has a background surface 116A that forms the background of the subject 2. In each wavelength range λ, the first spectral reflectance a, which is the spectral reflectance of light reflected by the subject 2, and the second spectral reflectance b, which is the spectral reflectance of light reflected by the background surface 116A, are related to each other (see FIG. 2).

[0156] Therefore, the wavelength range of the incident light is suppressed from changing between when the subject 2 is not present and when the subject 2 is present (see FIG. 7). This makes it possible to avoid the color of the subject 2 being measured as darker than the actual color of the subject 2, as in the color measurement method according to the second comparative example (see FIG. 20). In addition, the wavelength range of the ambient reflected light L7 is suppressed from changing between when the subject 2 is not present and when the subject 2 is present. This makes it possible to avoid the color of the subject 2 being measured as lighter than the actual color of the subject 2, or changes in the amount of flare, as in the color measurement method according to the second comparative example. As a result, for example, the measurement accuracy for the color of the subject 2 can be improved compared to when the background surface 116A is a white surface.

[0157] In the above embodiment, the color measurement process is executed by the processing device 90, but it may also be executed by the imaging device 10. Alternatively, a part of the color measurement process may be executed by the imaging device 10, and the remaining part of the color measurement process may be executed by the processing device 90.

[0158] Furthermore, in the above embodiment, the housing device 120 is used in an orientation in which the imaging device 10 is disposed on the top of the housing 114 and the calibration member 116 is disposed on the bottom of the housing 114, but the orientation of the housing device 120 may be other than the above. For example, the housing device 120 may be used in an orientation in which the imaging device 10 is disposed on the bottom of the housing 114 and the calibration member 116 is disposed on the top of the housing 114, or the housing device 120 may be used in an orientation in which the imaging device 10 and the calibration member 116 face each other horizontally.

[0159] Furthermore, for example, when the housing device 120 is used in an orientation in which the calibration member 116 is placed on top of the housing 114, or in which the imaging device 10 and the calibration member 116 face each other horizontally, the subject 2 may be fixed to the background surface 116A.

[0160] In the above embodiment, a plurality of calibration members 116 having different spectral reflectances may be used for the housing 114. Each calibration member 116 may be replaceable with respect to the housing 114, or may be switchable with respect to the housing 114. Then, from the plurality of calibration members 116, a calibration member 116 having a second spectral reflectance b corresponding to the first spectral reflectance a may be selected.

[0161] In the above embodiment, the processor 60 of the imaging device 10 may output warning information when the imaging conditions deviate from the specific conditions. The warning information may be information for notifying the user to adjust the angle of view. The notification may include at least one of a sound notification, a vibration notification, and a light notification. The output of the warning information allows the user to recognize that the imaging conditions deviate from the specific conditions.

[0162] Furthermore, when adjusting the angle of view of the imaging device 10, a reference plate (not shown) may be placed within a portion of the imaging range of the imaging device 10, and when the subject 2 and / or the calibration member 116 is placed, the processor 60 may determine whether the imaging conditions have deviated from the specific conditions based on changes in the captured image 70 obtained by the imaging device 10.

[0163] In addition, in the above embodiment, the processor 60 is exemplified for the imaging device 10, but instead of the processor 60, or together with the processor 60, at least one other CPU, at least one GPU, and / or at least one TPU may be used.

[0164] In addition, in the above embodiment, the processor 94 is exemplified as the processing device 90, but instead of the processor 94, or together with the processor 94, at least one other CPU, at least one GPU, and / or at least one TPU may be used.

[0165] In the above embodiment, the imaging device 10 has been described with reference to an example in which the spectral image generation program 80 is stored in the storage 62. However, the technology of the present disclosure is not limited to this. For example, the spectral image generation program 80 may be stored in a portable, non-transitory, computer-readable storage medium (hereinafter simply referred to as a "non-transitory storage medium") such as an SSD or a USB memory. The spectral image generation program 80 stored in the non-transitory storage medium may be installed in the computer 56 of the imaging device 10.

[0166] Alternatively, the spectral image generation program 80 may be stored in a storage device such as another computer or server device connected to the imaging device 10 via a network, and the spectral image generation program 80 may be downloaded and installed on the computer 56 of the imaging device 10 in response to a request from the imaging device 10.

[0167] Furthermore, it is not necessary to store the entire spectral image generation program 80 in a storage device such as another computer or server device connected to the imaging device 10, or in the storage 62; only a portion of the spectral image generation program 80 may be stored therein.

[0168] In the above embodiment, the processing device 90 has been described with reference to an example in which the color measurement program 100 is stored in the storage 96, but the technology of the present disclosure is not limited to this. For example, the color measurement program 100 may be stored in a non-transitory storage medium. The color measurement program 100 stored in the non-transitory storage medium may be installed in the computer 92 of the processing device 90.

[0169] In addition, the color measurement program 100 may be stored in a storage device such as another computer or server device connected to the processing device 90 via a network, and the color measurement program 100 may be downloaded in response to a request from the processing device 90 and installed on the computer 92 of the processing device 90.

[0170] Furthermore, it is not necessary to store the entire color measurement program 100 in a memory device of another computer or server device connected to the processing device 90, or in the storage 96; only a portion of the color measurement program 100 may be stored.

[0171] Furthermore, although the imaging device 10 has a built-in computer 56 , the technology of the present disclosure is not limited to this. For example, the computer 56 may be provided outside the imaging device 10 .

[0172] Furthermore, although the processing device 90 has a built-in computer 92 , the technology of the present disclosure is not limited to this, and for example, the computer 92 may be provided outside the processing device 90 .

[0173] In addition, in the above embodiment, the imaging device 10 is exemplified as a computer 56 including a processor 60, a storage 62, and a RAM 64, but the technology of the present disclosure is not limited to this, and a device including an ASIC, an FPGA, and / or a PLD may be applied instead of the computer 56. Furthermore, instead of the computer 56, a combination of a hardware configuration and a software configuration may be used.

[0174] In addition, in the above embodiment, the processing device 90 is exemplified as a computer 92 including a processor 94, a storage 96, and a RAM 98, but the technology of the present disclosure is not limited to this, and a device including an ASIC, an FPGA, and / or a PLD may be applied instead of the computer 92. Furthermore, instead of the computer 92, a combination of a hardware configuration and a software configuration may be used.

[0175] Furthermore, the following various processors can be used as hardware resources for executing the various processes described in the above embodiments. Examples of processors include a CPU, which is a general-purpose processor that functions as a hardware resource for executing various processes by executing software, i.e., a program. Examples of processors include dedicated electronic circuits, such as FPGAs, PLDs, and ASICs, which are processors with a circuit configuration designed specifically for executing specific processes. Each processor has built-in or connected memory, and each processor uses the memory to execute various processes.

[0176] The hardware resources that execute various processes may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resources that execute various processes may be a single processor.

[0177] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes various processes. Second, there is a system that uses a processor that realizes the functions of the entire system, including multiple hardware resources that execute various processes, on a single IC chip, as typified by SoC. In this way, various processes are realized using one or more of the above-mentioned various processors as hardware resources.

[0178] Furthermore, the hardware structure of these various processors can be, more specifically, electronic circuits that combine circuit elements such as semiconductor devices. The above-described gaze detection process is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the process.

[0179] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0180] In this specification, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0181] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0182] The following additional notes are provided regarding the above-described embodiments.

[0183] and a color measurement method comprising: a first acquisition step of acquiring first imaging data obtained by imaging the calibration member according to claim 1 with the spectral imaging device; a second acquisition step of acquiring second imaging data obtained by imaging the calibration member and the subject with the spectral imaging device; a calibration step of calibrating the second imaging data based on the first imaging data; and a color measurement step of measuring the color of the subject based on the calibrated second imaging data. (Supplementary Note 3) A program for causing a computer to execute a process including: a first acquisition step of acquiring first imaging data obtained by imaging the calibration member described in claim 1 using the spectroscopic imaging device; a second acquisition step of acquiring second imaging data obtained by imaging the calibration member and the subject using the spectroscopic imaging device; a calibration step of calibrating the second imaging data based on the first imaging data; and a color measurement step of measuring the color of the subject based on the calibrated second imaging data.

Claims

1. A calibration member used for calibrating a spectral imaging device equipped with a spectral filter having a specific wavelength range, the calibration member has a background surface that constitutes a background of the subject, In the wavelength range, a first spectral reflectance, which is a spectral reflectance of light reflected by the subject, and a second spectral reflectance, which is a spectral reflectance of light reflected by the background surface, have a relationship with each other, and the background surface has a surface roughness corresponding to that of the subject. Calibration materials.

2. The relationship is a relationship in which a difference between the first spectral reflectance and the second spectral reflectance is within a first range. The calibration member according to claim 1 .

3. The first range is a range from 0.5 times the reflectance to 2 times the reflectance of the first spectral reflectance. The calibration member according to claim 2 .

4. The first range is set based on a third spectral reflectance, which is the spectral reflectance of light reflected by the first reference plate. The calibration member according to claim 2 .

5. the first reference plate has a reflective surface that reflects the light, The reflective surface is a white surface. The calibration member according to claim 4 .

6. A difference between the first spectral reflectance and the second spectral reflectance is smaller than a difference between the first spectral reflectance and the third spectral reflectance. The calibration member according to claim 4 .

7. The second spectral reflectance is lower than the third spectral reflectance. The calibration member according to claim 4 .

8. The first spectral reflectance is lower than the third spectral reflectance. The calibration member according to claim 4 .

9. The second spectral reflectance falls within a second range of spectral reflectances that is set based on the first spectral reflectance and the third spectral reflectance. The calibration member according to claim 4 .

10. When the first spectral reflectance is a, the second spectral reflectance is b, and the third spectral reflectance is c, The second range is a range defined by formula (1) a / 2≦b≦(c+a) / 2...(1) The calibration member according to claim 9 .

11. When the first spectral reflectance is a, the second spectral reflectance is b, and the third spectral reflectance is c, The second range is a range defined by formula (2). 3a / 4≦b≦(c+3a) / 4...(2) The calibration member according to claim 9 .

12. The first spectral reflectance is a spectral reflectance based on the spectral reflectance measured at a plurality of points on the subject. The calibration member according to claim 1 .

13. The specific wavelength range includes a plurality of wavelength ranges, In each of the wavelength ranges, a difference between the first spectral reflectance and the second spectral reflectance is smaller than a difference between the first spectral reflectance and the third spectral reflectance. The calibration member according to claim 4 .

14. The spectral reflectance of the background surface is higher in a first near-infrared range of the near-infrared range than in a first visible range of the visible range. The calibration member according to claim 1 .

15. A calibration member according to any one of claims 1 to 14, a housing for covering an imaging space in which the calibration member and the subject are placed; and A housing device comprising:

16. A calibration device comprising: a calibration member according to any one of claims 1 to 14; the spectroscopic imaging device; a light source; and a housing; the housing covers an imaging space in which the calibration member and the subject are placed, An imaging condition when the subject is imaged by the spectroscopic imaging device is a first condition in which a first component of incident light incident on the spectroscopic imaging device is light irradiated from the light source and reflected by the subject and the calibration member. Calibration device.

17. A method for controlling a computer-implemented program comprising: The processor outputs warning information when the imaging condition deviates from the first condition.

17. The calibration device of claim 16.

18. A calibration member according to any one of claims 1 to 14, and a processor, The processor, acquiring first imaging data obtained by imaging the calibration member with the spectroscopic imaging device; acquiring second imaging data obtained by imaging the calibration member and the subject by the spectroscopic imaging device; Calibrating the second imaging data based on the first imaging data Calibration device.

19. A first acquisition step of acquiring first imaging data obtained by imaging a calibration member according to any one of claims 1 to 14 by the spectroscopic imaging device; a second acquisition step of acquiring second imaging data obtained by imaging the calibration member and the subject by the spectroscopic imaging device; a calibration step of calibrating the second imaging data based on the first imaging data; A calibration method comprising:

20. A first acquisition step of acquiring first imaging data obtained by imaging a calibration member according to any one of claims 1 to 14 by the spectroscopic imaging device; a second acquisition step of acquiring second imaging data obtained by imaging the calibration member and the subject by the spectroscopic imaging device; a calibration step of calibrating the second imaging data based on the first imaging data; A program for causing a computer to execute a process including the steps of: