WO2024047944A1

WO2024047944A1 - Member for calibration, housing device, calibration device, calibration method, and program

Info

Publication number: WO2024047944A1
Application number: PCT/JP2023/017201
Authority: WO
Inventors: 慶延岸根; 和佳岡田; 睦川中子; 高志椚瀬; 友也平川
Original assignee: 富士フイルム株式会社
Priority date: 2022-08-29
Filing date: 2023-05-02
Publication date: 2024-03-07

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 parts, housing device, calibration device, calibration method, and program

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

Japanese Unexamined Patent Publication No. 2006-292582 discloses a multiband image processing device that acquires a spectral image of a subject. A multiband image processing device includes an image acquisition unit that acquires an image of a plurality of objects with known spectral characteristics placed near the object, and an image acquisition unit that acquires an image of a plurality of objects with known spectral characteristics obtained from the images. and an image processing unit that performs predetermined processing on the image based on spatial variations in the image.

JP 2018-009988A discloses a measurement device that evaluates particle characteristics of a painted surface containing a glitter material. The measurement device includes a chromaticity distribution acquisition means that acquires the in-plane chromaticity distribution of the object under at least two or more illumination conditions or light reception conditions, and a particle characteristic based on the amount of variation in the in-plane chromaticity distribution. and particle characteristic evaluation means for calculating a particle characteristic evaluation value for evaluating.

Japanese Unexamined Patent Publication No. 2001-144972 discloses a multispectral image recording/processing device that images and records a subject in a subject image recording area illuminated by a light source. The multispectral image recording/processing device includes a subject support section, a light source section, an imaging means, an angular multispectral image acquisition section, and a spectral reflectance estimation section. The subject support section supports the subject in the subject image recording area. The light source section is arranged in a desired azimuth direction centered on a predetermined position in a plane that includes a predetermined position of the subject imaging recording area, and is spaced a certain distance from the predetermined position, and is directed toward the subject imaging recording area. illuminate. The imaging means is arranged in a desired azimuth direction centered on a predetermined position in a plane including the predetermined position, and spaced apart from the predetermined position by a certain distance, and captures a multiband image of the subject. The declination multispectral image acquisition unit captures and records a plurality of multiband images 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. From this, a polarization multispectral image having the spectral reflectance distribution of the subject is obtained using the light source position and the imaging position as parameters. The spectral reflectance estimation unit interpolates or synthesizes the spectral reflectance distribution using the light source position and the imaging position as parameters to obtain the spectral reflectance of the subject under image reproduction conditions at the desired light source position, number of light sources, or imaging position. The distribution is estimated using the image data of the declination multispectral image obtained by the declination multispectral image acquisition unit.

Japanese Unexamined Patent Publication No. 2010-130157 discloses a color conversion method that performs color conversion of a multiband image having four or more bands obtained by combining a plurality of input images input by a plurality of image input means having mutually different bands. A multispectral image processing apparatus comprising means is disclosed. The color conversion means includes a spectral sensitivity characteristic information correction means for correcting spectral sensitivity characteristic information, which is a spectral sensitivity characteristic of the image input means, based on a ratio of exposure information included in data of a plurality of input images; A device-independent method that converts a multiband image into a device-independent color image using the spectral sensitivity characteristic information obtained when the input image was photographed and the photographing illumination light information, which is the spectral characteristics of the illumination light when the input image was photographed. and color image conversion means.

One embodiment of the technology of the present disclosure includes, for example, a calibration member, a housing device, a calibration device, and a housing device that can improve measurement accuracy for the color of a subject compared to when the background surface is a white surface. Providing calibration methods and programs.

A first aspect of the technology of the present disclosure is a calibration member used for calibration of a spectral imaging device equipped with a spectral filter having a specific wavelength range, wherein the calibration member is a background that constitutes a background of a subject. The first spectral reflectance, which is the spectral reflectance of the light reflected by the subject, and the second spectral reflectance, which is the spectral reflectance of the light reflected by the background surface, have a relationship with each other in the wavelength range. It is a calibration member having.

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. This is a calibration member.

A third aspect of the technology of the present disclosure is the calibration member according to the second aspect, wherein the first range is from a reflectance of 0.5 times to a reflectance of twice the first spectral reflectance. This is a calibration member that has a range of .

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

A fifth aspect of the technology of the present disclosure is the calibration member according to the fourth aspect, in which the first reference plate has a reflective surface that reflects light, and the reflective surface is a white surface. It is.

A sixth aspect according to the technology of the present disclosure is that in the calibration member according to the fourth aspect or the fifth aspect, the difference between the first spectral reflectance and the second spectral reflectance is the same as the difference between the first spectral reflectance and the second spectral reflectance. This is a calibration member smaller than the difference with the third spectral reflectance.

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

An eighth aspect according to the technology of the present disclosure is the calibration member according to any one of the fourth to seventh aspects, in which the first spectral reflectance is lower than the third spectral reflectance. It is a member for use.

A ninth aspect according to the technology of the present disclosure is the calibration member according to any one of the fourth to eighth aspects, in which the second spectral reflectance is equal to the first spectral reflectance and the third spectral reflectance. This is a calibration member that falls within a second range of spectral reflectance set based on reflectance.

A tenth aspect according to the technology of the present disclosure is a calibration member according to the ninth aspect, in which the first spectral reflectance is a, the second spectral reflectance is b, and the third spectral reflectance is c. In this case, the second range is a calibration member that is a range defined by equation (1).
a/2≦b≦(c+a)/2...(1)

An eleventh aspect according to the technology of the present disclosure is that in the calibration member according to the ninth aspect, the first spectral reflectance is a, the second spectral reflectance is b, and the third spectral reflectance is c. In this case, the second range is a calibration member that is a range defined by equation (2).
3a/4≦b≦(c+3a)/4...(2)

A twelfth aspect of the technology of the present disclosure is a calibration member according to any one of the first to eleventh aspects, in which the first spectral reflectance is measured at multiple locations on the subject. This is a calibration member that is a spectral reflectance based on the calculated spectral reflectance.

A thirteenth aspect according to the technology of the present disclosure is a calibration member according to any one of the fourth aspect to the eleventh aspect, and the twelfth aspect subordinate to the fourth aspect. The 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. It is a member.

A fourteenth aspect according to the technology of the present disclosure is a calibration member according to any one of the first to thirteenth aspects, in which the background surface has a surface roughness corresponding to the subject. It is.

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

A sixteenth aspect according to the technology of the present disclosure includes 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 arranged. It is a housing device equipped with.

A seventeenth aspect according to the technology of the present disclosure includes the calibration member according to any one of the first to fifteenth aspects, a spectral imaging device, a light source, and a housing. covers the imaging space in which the calibration member and the subject are placed, and the imaging conditions when imaging the subject with the spectroscopic imaging device are such that the first component of the incident light that enters the spectroscopic imaging device is from the light source. This is the first condition of the calibration device in which the light is irradiated and reflected by the subject and the calibration member.

An 18th aspect according to the technology of the present disclosure is a calibration device according to the 17th aspect, which includes a processor, and the processor outputs warning information when the imaging condition deviates from the first condition.

A nineteenth aspect according to the technology of the present disclosure includes the calibration member according to any one of the first to fifteenth aspects, and a processor, the processor comprising: a calibration member according to any one of the first to fifteenth aspects; First imaging data obtained by imaging is acquired, second imaging data is obtained by imaging the calibration member and the subject by a spectroscopic imaging device, and second imaging data is acquired based on the first imaging data. This is a calibration device that performs calibration on 2 imaged data.

A 20th aspect of the technology of the present disclosure is a 20th aspect of the technology of the present disclosure, in which the first imaging data obtained when the calibration member according to any one of the 1st to 15th aspects is imaged by a spectroscopic imaging device. a first acquisition step of acquiring, a second acquisition step of acquiring second imaging data obtained by imaging the calibration member and the subject with a spectroscopic imaging device, and a second acquisition step of acquiring second imaging data based on the first imaging data. This is a calibration method comprising a calibration step of performing calibration for.

A twenty-first aspect of the technology of the present disclosure provides first imaging data obtained when the calibration member according to any one of the first to fifteenth aspects is imaged by a spectroscopic imaging device. a first acquisition step of acquiring, a second acquisition step of acquiring second imaging data obtained by imaging the calibration member and the subject with a spectroscopic imaging device, and a second acquisition step of acquiring second imaging data based on the first imaging data. This is a program for causing a computer to execute a process including a calibration process for calibrating the data.

FIG. 1 is a block diagram showing an example of a color measuring device according to the present embodiment. It is a graph which shows an example of a 1st spectral reflectance, a 2nd spectral reflectance, and a 3rd spectral reflectance. It is a graph which shows the 1st example of 2nd spectral reflectance. It is a graph which shows the 2nd example of 2nd spectral reflectance. FIG. 2 is a block diagram illustrating an example of a color setting method for setting the color of a background surface. FIG. 2 is a block diagram illustrating an example of a color measurement method according to the present embodiment. FIG. 2 is a block diagram showing an example of the aspect of incident light in the color measurement method according to the present embodiment. It is a perspective view showing an example of an imaging device concerning this embodiment. It is an exploded perspective view showing an example of a pupil division filter. FIG. 2 is a block diagram showing an example of the hardware configuration of an imaging device. FIG. 2 is an explanatory diagram showing an example of the configuration of a photoelectric conversion element. FIG. 2 is a block diagram illustrating an example of a functional configuration for executing spectral image generation processing. FIG. 2 is a block diagram illustrating an example of the operation of an output value acquisition section and an interference removal processing section. FIG. 2 is a block diagram illustrating an example of the hardware configuration of a processing device according to the present embodiment and an example of a functional configuration for executing color measurement processing. FIG. 2 is a block diagram illustrating an example of the operations of an image data acquisition section, a calibration image generation section, and a color derivation section. 2 is a flowchart illustrating an example of the flow of spectral image generation processing. 3 is a flowchart showing an example of the flow of color measurement processing. FIG. 2 is a block diagram illustrating an example of a color measurement method according to a first comparative example. FIG. 7 is a block diagram illustrating an example of a color measurement method according to a second comparative example. FIG. 7 is a block diagram illustrating an example of an aspect of incident light in a color measurement method according to a second comparative example.

Hereinafter, an example of an embodiment 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.

First, the words used in the following explanation will be explained.

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."

In the description of this specification, "uniform" means not only complete "uniform" but also an error that is generally allowed in the technical field to which the technology of the present disclosure belongs, and is contrary to the spirit of the technology of the present disclosure. It refers to "uniform" in the sense that it includes some degree of error. In the description of this specification, "same" means not only "the same" but also an error that is generally allowed in the technical field to which the technology of the present disclosure belongs, and which is contrary to the spirit of the technology of the present disclosure. It refers to "the same" in the sense that it includes a certain degree of error. In the description of this specification, "orthogonal" means not only complete "orthogonal" but also an error that is generally allowed in the technical field to which the technology of the present disclosure belongs, and is contrary to the spirit of the technology of the present disclosure. This refers to "orthogonal" in the sense that it includes a degree of error that does not occur. In the description of this specification, a "straight line" refers to an error that is generally allowed in the technical field to which the technology of the present disclosure belongs, in addition to a perfect "straight line," and is contrary to the spirit of the technology of the present disclosure. It refers to a ``straight line'' that includes a certain amount of error.

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

FIG. 18 shows an example of a color measurement method according to the first comparative example. The imaging device 200 used in the color measurement method according to the first comparative example is an RGB camera. The RGB camera refers to a camera that can generate wavelength range images in each of red, green, and blue wavelength ranges.

In the color measurement method shown in FIG. 18, the color of the subject 2 is measured in the following manner. That is, first, as shown in Aspect I, light L8 is irradiated from the light source 202 onto a white reference plate 204 (hereinafter referred to as "white reference plate 204"), and the incident light including light L9 reflected by the white reference plate 204 is emitted. The light Lb is imaged by the imaging device 200. As a result, a reference image 220 is obtained. Subsequently, as shown in aspect J, light L8 is irradiated from the light source 202 to the subject 2, and the incident light Lb including the light L10 reflected by the subject 2 is imaged by the imaging device 200. As a result, a subject image 222 is obtained.

Then, in the processing device 210 communicably connected to the imaging device 200, a calibration image 224 is generated by performing calibration on the subject image 222 based on the reference image 220, and a calibration image 224 is generated based on the calibration image 224. Color is measured. As a result, a color measurement result 226, which is the result of measuring the color of the subject 2, is obtained.

In the color measurement method according to the first comparative example, even if the light L8 emitted from the light source 202 is uneven or the amount of light around the imaging device 200 is reduced, the color measurement method based on the reference image 220 By performing the calibration on the image 222, the color of the subject 2 is measured while eliminating the influence of unevenness of the light L8, the influence of a decrease in the amount of light around the imaging device 200, and the like.

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 an actual imaging environment, light other than the light L8 emitted from the light source 202 It is affected by ambient light, etc.

FIG. 19 shows an example of a color measurement method according to the second comparative example. In the color measurement method according to the second comparative example, a housing 206 is used to prevent disturbance light and the like from affecting the imaging environment. The housing 206 is configured to cover the imaging space 208. In the imaging space 208, the light source 202, the entrance section 200A of the imaging device 200, and the subject 2 are arranged. The inner surfaces of the housing 206 (ie, the bottom surface 206A, the side surfaces 206B, and the top surface 206C) are white surfaces.

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 L8 is irradiated from the light source 202 onto the bottom surface 206A, and incident light Lb including light L11 reflected from the bottom surface 206A is imaged by the imaging device 200. As a result, a reference image 220 is obtained. Subsequently, as shown in aspect L, the subject 2 is placed on the bottom surface 206A, the light L8 is irradiated from the light source 202 to the subject 2, and the incident light Lb including the light L12 reflected by the subject 2 is captured by the imaging device 200. Imaged. As a result, a subject image 222 is obtained.

FIG. 20 shows problems with the color measurement method according to the second comparative example. In the color measurement method according to the second comparative example, as shown in aspect M, when the reference image 220 is obtained, the incident light Lb is irradiated from the light source 202 to the bottom surface 206A and reflected by the bottom surface 206A and the top surface 206C. This includes light L13 that is reflected again on the bottom surface 206A. On the other hand, as shown in aspect N, when the subject image 222 is obtained, the incident light Lb includes light that is irradiated from the light source 202 to the subject 2, reflected by the subject 2 and the top surface 206C, and then reflected again by the subject 2. Light L14 (hereinafter referred to as "re-reflected light L14") is included. Since the re-reflected light L14 is light that has been reflected twice by the subject 2, in the case of aspect N, the color of the subject 2 is measured to be darker than the actual color of the subject 2.

In addition, in the color measurement method according to the second comparative example, as shown in aspect O, when the subject image 222 is obtained, the incident light Lb includes light irradiated from the light source 202 to the subject 2 and reflected by the subject 2. In addition to L15, light L16 reflected from the area around the subject 2 on the bottom surface 206A (hereinafter referred to as "peripheral reflected light L16") is also included. Therefore, in the case of aspect O, the peripheral reflected light L16 is included in the incident light Lb, so that the color of the subject 2 is measured to be lighter than the actual color of the subject 2, and the peripheral reflected light L16 causes flare. Occurs.

In this way, in the color measurement method according to the second comparative example, the incident light Lb changes between the case where there is no subject 2 and the case where there is subject 2, so that the color measurement method according to the first comparative example is different. , there is a problem that measurement accuracy for the color of the subject 2 is reduced.

As a result of intensive study on multispectral cameras instead of RGB cameras, the inventors confirmed that the same problems as the above-mentioned RGB cameras occur with multispectral cameras. The multispectral camera referred to here refers to a camera that can generate 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 a multispectral camera is used.

Next, this embodiment will be described.

FIG. 1 shows a color measuring device 110 according to this embodiment. The color measurement device 110 includes a light source 112, a housing 114, a calibration member 116, an imaging device 10, and a processing device 90.

The light source 112 is, for example, an LED light source, a laser light source, or an incandescent light bulb. The light emitted from the light source 112 is non-polarized. The light source 112 is arranged, for example, at the top inside the housing 114.

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

The calibration member 116 is, for example, a rectangular plate in plan view. The calibration member 116 is arranged on the bottom surface 114A. Here, an example is given in which the calibration member 116 is a plate, but the calibration member 116 may have 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 “casing device” according to the technology of the present disclosure.

The calibration member 116 has a background surface 116A. The background surface 116A is a surface facing the imaging device 10 (that is, an upper surface). The subject 2 is placed on the background surface 116A. The subject 2 may be of any kind. Moreover, the color of the subject 2 may be any color. Hereinafter, an example in which the color of the subject 2 is a color other than white will be described.

The background surface 116A constitutes the background of the subject 2 when the subject 2 is placed on the calibration member 116. The background surface 116A has a color corresponding to the color of the subject 2, as will be described in detail later. The surfaces of the calibration member 116 other than the background surface 116A may have the same color as the background surface 116A, or may have a different color from the background surface 116A. Hereinafter, an example in which the surface of the calibration member 116 other than the background surface 116A has the same color as the background surface 116A will be described.

Further, the background surface 116A has a surface roughness corresponding to that of the subject 2. The surface roughness may be adjusted by processing the background surface 116A, or by changing the size of particles forming the background surface 116A. Since the background surface 116A has a surface roughness corresponding to that of the subject 2, the directionality of the light reflected on the background surface 116A can be matched to the directionality of the light reflected on the subject 2.

The imaging device 10 is, for example, a multispectral camera. Although an example in which the imaging device 10 is a multispectral camera is given here, the imaging device 10 may be a spectral camera such as a hyperspectral camera. Hereinafter, an example in which the imaging device 10 is a multispectral camera will be described. The imaging device 10 is an example of a "spectral imaging device" according to the technology of the present disclosure.

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 splitting filter 16, and a second lens 32. The first lens 30, the pupil splitting filter 16, and the second lens 32 are arranged along the optical axis OA of the optical system 26 from the subject 2 side to the image sensor 28 side. The lenses 32 are arranged in this order.

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 has a first wavelength range λ ₁ , the spectral filter 20B has a second wavelength range λ ₂ , and the spectral filter 20C has a third wavelength range λ _3. has. The spectral filter is an example of a "spectral filter" according to the technology of the present disclosure.

Hereinafter, unless it is necessary to separately explain 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. In addition, if it is not necessary to separately explain the first wavelength range λ ₁ , the second wavelength range λ ₂ , and the third wavelength range λ ₃ , the first wavelength range λ ₁ , the second wavelength range λ ₂ , and Each of the third wavelength ranges λ ₃ is referred to as a "wavelength range λ".

As will be described in detail later, in the imaging device 10, spectral images 72A to 72C corresponding to each wavelength range λ are generated based on a captured image (not shown) obtained by imaging the subject 2. The spectral image 72A is a spectral image corresponding to the first wavelength range λ ₁ , the spectral image 72B is a spectral image corresponding to the second wavelength range λ ₂ , and the spectral image 72C is a spectral image corresponding to the third wavelength range λ ₃ . This is the corresponding spectral image. Hereinafter, unless it is necessary to explain the spectral images 72A to 72C separately, each of the spectral images 72A to 72C will be referred to as a "spectral image 72."

In the present embodiment, a case will be described as an example in which three spectral images 72 are generated based on light separated into three wavelength ranges λ. However, the three wavelength ranges λ are just an example, and the present invention is applicable to two or more wavelength ranges λ.

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 such that 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 way, the imaging conditions when the subject 2 is imaged by the imaging device 10 are as follows: is set to a specific condition under which the light is emitted 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.

The processing device 90 is communicably 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 the color measurement result 136, which is the measurement result, on the display device 108.

FIG. 2 shows a graph showing 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 uniform white color. Similarly, the background surface 116A is formed of a uniform color.

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

For example, the first spectral reflectance a may be a spectral reflectance based on spectral reflectances measured at multiple locations on the subject 2. If the first spectral reflectance a is a spectral reflectance based on spectral reflectances measured at multiple locations on the subject 2, the first spectral reflectance a is The accuracy of the first spectral reflectance a is improved compared to the case where it is a measured spectral reflectance. The first spectral reflectance a may be an average value of spectral reflectances measured at a plurality of locations on the subject 2, or may be a representative value (for example, a maximum value, a central value, or a minimum value). Further, the number of the plurality of locations may be any number. Furthermore, the positions of the plurality of places may be any position on the subject 2. Further, the subject 2 may be a plurality of subjects. Each location may be a location on each subject 2. Note that the first spectral reflectance a may be a spectral reflectance measured at one location on the subject 2.

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

FIG. 2 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 and the second wavelength range λ ₂ . The first spectral reflectance a in the first wavelength range λ ₁ may be an average value or a representative value (for example, a maximum value, a central value, or a minimum value). Similarly, the second spectral reflectance b in the first wavelength range λ ₁ may be an average value or a representative value (for example, the highest value, the center value, or the lowest value). Further, the first spectral reflectance a in the second wavelength range λ ₂ may be an average value or a representative value (for example, a maximum value, a central value, or a minimum value). Similarly, the second spectral reflectance b in the second wavelength range λ ₂ may be an average value or a representative value (for example, the highest value, the center value, or the lowest value).

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 spectral reflectance a and the second spectral reflectance b have a relationship with each other in the first wavelength range λ ₁ . Similarly, in the second wavelength range λ ₂ , the first spectral reflectance a and the second spectral reflectance b have a relationship with each other.

Here, an example is given in which the first spectral reflectance a and the second spectral reflectance b have a relationship with each other in the first wavelength range λ ₁ and the second wavelength range λ ₂ . The index a and the second spectral reflectance b may have a relationship with each other in the second wavelength range λ ₂ and the third wavelength range λ ₃ (see FIG. 1). Hereinafter, an example will be described in which the first spectral reflectance a and the second spectral reflectance b have a relationship with each other in the first wavelength range λ ₁ and the second wavelength range λ ₂ .

As an example of the relationship between the first spectral reflectance a and the second spectral reflectance b in the first wavelength range λ ₁ , the difference between the first spectral reflectance a and the second spectral reflectance b is , within the first range (not shown). Similarly, in the second wavelength range λ ₂ , as an example of the relationship between the first spectral reflectance a and the second spectral reflectance b, the first spectral reflectance a and the second spectral reflectance b The difference is within the first range.

The first range is set, for example, based on the third spectral reflectance c. Specifically, the first range is set as a range of spectral reflectance lower than the third spectral reflectance c. The first range is, for example, a range from a reflectance 0.5 times to a reflectance twice the first spectral reflectance a. In other words, a reflectance that is 0.5 times the first spectral reflectance a is the lower limit of the first range, and a reflectance that is twice the first spectral reflectance a is the upper limit of the first range. be. For example, if the lower limit of the first range is set to less than 0.5 times the spectral reflectance of the first spectral reflectance a, then the first spectral reflectance a and the second spectral reflectance b becomes irrelevant. For example, even if the upper limit of the first range is set to a reflectance that exceeds twice the spectral reflectance of the first spectral reflectance a, the first spectral reflectance a and the second spectral reflectance rate b becomes irrelevant.

Further, in the first wavelength range λ ₁ and the second wavelength range λ ₂ , the first spectral reflectance a and the second spectral reflectance b have a difference. In the first wavelength range λ ₁ and the second wavelength range λ ₂ , the second spectral reflectance b may be higher than the first spectral reflectance a, or may be lower than the first spectral reflectance a. In the first wavelength range λ ₁ and the second wavelength range λ ₂ , the difference between the first spectral reflectance a and the second spectral reflectance b is greater than the difference between the first spectral reflectance a and the third spectral reflectance c. It's also small. Furthermore, in the first wavelength range λ ₁ and the second wavelength range λ ₂ , the first spectral reflectance a and the second spectral reflectance b are lower than the third spectral reflectance c.

Further, in the first wavelength range λ ₁ and the second wavelength range λ ₂ , the second spectral reflectance b is the second spectral reflectance set based on the first spectral reflectance a and the third spectral reflectance c. falls within the range. For example, the second range is a range defined by equation (1). In FIG. 2, the second range defined by equation (1) is shown as second range R1.
a/2≦b≦(c+a)/2...(1)

According to formula (1), the lower limit of the second range R1 is defined by half the first spectral reflectance a, and the upper limit of the second range R1 is defined by the third spectral reflectance c and the first spectral reflectance. It is defined as half the sum of a. In this case, 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 by the sum of the third spectral reflectance c and the first spectral reflectance a, In comparison, the degree of influence of the second spectral reflectance b on the color measurement error can be reduced to 1/2. 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 0.05. It will be 55.

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

According to formula (2), the lower limit value of the second range R2 is defined by the 3/4 value of the first spectral reflectance a, and the upper limit value of the second range R2 is defined by the third spectral reflectance c and the first spectral reflectance c. It is defined by the value of 1/4 of the sum of the spectral reflectance a and the spectral reflectance that is three times the spectral reflectance a. In this case, 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 by the sum of the third spectral reflectance c and the first spectral reflectance a, In comparison, the degree of influence of the second spectral reflectance b on color measurement errors can be reduced to 1/4. 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 0.075. It becomes 325.

3 and 4 show graphs schematically showing an example of the second spectral reflectance b. As an example, as shown in graph G4 in FIG. 3 and graph G5 in FIG. 4, the second spectral reflectance b is higher in the first near-infrared region of the near-infrared region than in the first visible region of the visible region. may be high.

The first visible range may be the entire wavelength range of the visible range, or may be a part of the wavelength range. Similarly, the first near-infrared region may be the entire wavelength region of the near-infrared region, or may be a part of the wavelength region. The visible region and the near-infrared region may be continuous, may be separated, or may partially overlap.

In the example shown in FIG. 3, the second spectral reflectance b increases linearly (that is, continuously) as the wavelength becomes longer from a specific wavelength, and has a peak in the first near-infrared region. In the example shown in FIG. 4, the second spectral reflectance b increases nonlinearly (that is, discontinuously) at a specific wavelength and has a peak in the first near-infrared region.

As shown in FIGS. 3 and 4, when the second spectral reflectance b has a peak in the first near-infrared region, for example, the subject 2, such as a plant, has a higher spectral reflectance in the near-infrared region than in the visible region. In the case where the subject 2 is a subject shown in FIG. That is, for example, the accuracy of measuring the color of the subject 2 is improved compared to a case where the second spectral reflectance b is the same in the first visible region and the first near-infrared region.

FIG. 5 shows an example of the flow of a method for setting the color of the background surface 116A (hereinafter referred to as "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. As a result, a captured image 126 is obtained. 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 surface of the subject 2 may be of any type.

Subsequently, as shown in step B, the first spectral reflectance a is measured based on the captured image 126. The first spectral reflectance a may be a spectral reflectance based on spectral reflectances measured at multiple locations on the subject 2. Further, the first spectral reflectance a may be an average value of spectral reflectances measured at a plurality of locations on the subject 2, or may be a representative value (for example, a maximum value, a central value, or a minimum value).

Subsequently, 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.

FIG. 6 shows an example of the color measurement method according to this embodiment. The above-described color measuring device 110 is used in the color measuring method according to this embodiment.

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 disposed on the bottom surface 114A of the housing 114, light L1 is irradiated from the light source 112 onto the background surface 116A, and light L2 is reflected from the background surface 116A. The incident light La including the above is imaged by the imaging device 10. As a result, a reference image 130 is obtained. Subsequently, as shown in aspect E, the subject 2 is placed on the background surface 116A, the light source 112 irradiates the subject 2 with light L1, and the incident light La including the light L3 reflected by the subject 2 is transmitted to the imaging device 10. imaged by. As a result, a subject image 132 is obtained.

Then, in the processing device 90 communicably connected to the imaging device 10 , a calibration image 134 is generated by calibrating the subject image 132 based on the reference image 130 . Color is measured. As a result, a color measurement result 136, which is the result of measuring the color of the subject 2, is obtained.

FIG. 7 shows a specific example of the incident light La that enters the imaging device 10 in the color measurement method according to the present embodiment. In the color measurement method according to the present embodiment, as shown in aspect F, when the reference image 130 is obtained, the incident light La is irradiated from the light source 112 onto the background surface 116A and the background surface 116A and the top surface 114C. It includes light L4 that has been reflected and then reflected again on the background surface 116A. Further, in the color measurement method according to the present embodiment, as shown in aspect G, when the subject image 132 is obtained, the incident light La is irradiated from the light source 112 to the subject 2 and the subject 2 and the top surface 114C. The light L5 that has been reflected and then reflected again by the subject 2 is included.

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 suppressed from changing between the case where the subject 2 is not present and the case where the subject 2 is present. As a result, it is possible to avoid measuring the color of the object 2 darker than the actual color of the object 2, as in the color measurement method according to the second comparative example (see aspect N in FIG. 20). can.

In addition, in the color measurement method according to the present embodiment, as shown in aspect H, when the subject image 132 is obtained, the incident light La includes light L6 that is irradiated onto the subject 2 from the light source 112 and reflected by the subject 2. In addition to this, light L7 (hereinafter referred to as "peripheral reflected light L7") that is irradiated onto the subject 2 from the light source 112 and reflected on the area around the subject 2 on the background surface 116A is also included.

Here, 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 peripheral reflected light L7 is suppressed from changing between the case where the subject 2 is not present and the case where the subject 2 is present. As a result, as in the color measurement method according to the second comparative example (see aspect O in FIG. 20), the color of the subject 2 may be measured to be lighter than the actual color of the subject 2, or the amount of flare may change. You can avoid doing that.

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

As shown in FIG. 8 as an example, the imaging device 10 includes a lens device 12 and an imaging device body 14. The lens device 12 includes the pupil splitting filter 16 described above. The imaging device 10 is a multispectral camera that generates and outputs a plurality of spectral images 72A to 72C by capturing light that has been split into a plurality of wavelength ranges λ by the pupil splitting filter 16.

As shown in FIG. 9 as an example, the pupil division filter 16 includes a frame 18, spectral filters 20A to 20C, and polarization filters 22A to 22C.

The frame 18 has openings 24A to 24C. The openings 24A to 24C are formed in line around the optical axis OA. Hereinafter, unless it is necessary to separately explain 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 apertures 24A to 24C, respectively, so that they are arranged side by side around the optical axis OA.

The polarizing filters 22A to 22C are provided corresponding to the spectral filters 20A to 20C, respectively. Specifically, the polarizing filter 22A is provided in the aperture 24A, and is overlapped with the spectral filter 20A. The polarizing filter 22B is provided in the aperture 24B and overlapped with the spectral filter 20B. The polarizing filter 22C is provided in the aperture 24C and is overlapped with the spectral filter 20C.

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

Hereinafter, unless it is necessary to explain the polarizing filters 22A to 22C separately, each of the polarizing filters 22A to 22C will be referred to as a "polarizing filter 22." Furthermore, if it is not necessary to separately explain the first polarization angle α ₁ , the second polarization angle α ₂ , and the third polarization angle α ₃ , the first polarization angle α ₁ , the second polarization angle α ₂ , and Each of the third polarization angles α ₃ is referred to as a “polarization angle α”.

In the example shown in FIG. 9, the number of apertures 24 is three, corresponding to the number of wavelength ranges λ, but the number of apertures 24 is equal to the number of wavelength ranges λ. (that is, the number of spectral filters 20). Furthermore, unused openings 24 among the plurality of openings 24 may be covered by a shielding member (not shown). Further, in the example shown in FIG. 9, the plurality of spectral filters 20 have mutually different wavelength ranges λ, but the plurality of spectral filters 20 may include spectral filters 20 having the same wavelength range λ.

As shown in FIG. 10 as an example, 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 a pupil splitting filter 16, a first lens 30, and a second lens 32.

The first lens 30 causes the light emitted from the light source 112 and reflected by the subject 2 to enter the pupil division filter 16 . The second lens 32 forms an image of the light that has passed through the pupil splitting filter 16 onto a light receiving surface 34A of a photoelectric conversion element 34 provided in the image sensor 28.

The pupil splitting filter 16 is placed at the pupil position of the optical system 26. The pupil position refers to the aperture surface that limits the brightness of the optical system 26. The pupil position here includes a nearby position, and the nearby position refers to the range from the entrance pupil to the exit pupil. The configuration of the pupil division filter 16 is as described using FIG. 9. In FIG. 10, for convenience, a plurality of spectral filters 20 and a plurality of polarizing filters 22 are shown arranged in a straight line along a direction perpendicular to the optical axis OA.

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 this embodiment, a CMOS image sensor is exemplified as the image sensor 28, but the technology of the present disclosure is not limited to this. For example, the image sensor 28 may be another type of image sensor such as a CCD image sensor. The technology of the present disclosure is realized.

As an example, FIG. 10 shows a schematic configuration of the photoelectric conversion element 34. Furthermore, as an example, FIG. 11 specifically shows the configuration of a part of the photoelectric conversion element 34. The photoelectric conversion element 34 includes 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 an example, and the technology of the present disclosure is applicable even if the photoelectric conversion element 34 does not include the spectral filter layer 42.

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

Hereinafter, the pixel 44 provided in the photoelectric conversion element 34 will be referred to as a "physical pixel 44" in order to distinguish it from the pixel forming a spectral image. Furthermore, the pixels forming the spectral image 72 are referred to as "image pixels."

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

A plurality of physical pixels 44 form a plurality of pixel blocks 46. Each pixel block 46 is formed by a total of four physical pixels 44, two in the vertical direction and two in the horizontal direction. In FIG. 10, for convenience, the four physical pixels 44 forming each pixel block 46 are shown arranged in a straight line along the direction perpendicular to the optical axis OA, but the four physical pixels 44 are arranged adjacent to the photoelectric conversion element 34 in the vertical and horizontal directions (see FIG. 11).

The polarizing filter layer 40 has multiple types of polarizers 48A to 48D. Each polarizer 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, polarizer 48A has a first polarization angle θ ₁ , polarizer 48B has a second polarization angle θ ₂ , and polarizer 48C has a third polarization angle θ ₃ . , and the polarizer 48D has a fourth polarization angle _θ4 . As an example, the first polarization angle θ ₁ is set to 0°, the second polarization angle θ ₂ is set to 45°, and the third polarization angle θ ₃ is set to 90°. , the fourth polarization angle θ ₄ is set to 135°.

Hereinafter, unless it is necessary to explain the polarizers 48A to 48D separately, each of the polarizers 48A to 48D will be referred to as a "polarizer 48." The polarizer 48 is an example of a "polarizer" according to the technology of the present disclosure. In addition, if it is not necessary to separately explain the first polarization angle θ ₁ , the second polarization angle θ ₂ , the third polarization angle θ ₃ , and the fourth polarization angle θ ₄ , the first polarization angle θ ₁ , the The second polarization angle θ ₂ , the third polarization angle θ ₃ , and the fourth polarization angle θ ₄ are each referred to as “polarization angle θ”.

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

In FIG. 10, for convenience, the B filter 50A, the G filter 50B, and the R filter 50C are shown arranged in a straight line along the direction orthogonal to the optical axis OA, but as an example, as shown in FIG. The B filter 50A, the G filter 50B, and the R filter 50C are arranged in a matrix in a predetermined pattern arrangement. In the example shown in FIG. 11, the B filter 50A, the G filter 50B, and the R filter 50C are arranged in a matrix in a Bayer arrangement, as an example of a predetermined pattern arrangement. Note that the predetermined pattern arrangement may be an RGB stripe arrangement, an R/G checkered arrangement, an X-Trans (registered trademark) arrangement, a honeycomb arrangement, or the like other than the Bayer arrangement.

Hereinafter, unless it is necessary to explain the B filter 50A, G filter 50B, and R filter 50C separately, the B filter 50A, the G filter 50B, and the R filter 50C will be referred to as "filters 50", respectively.

As shown in FIG. 10 as an example, the imaging device body 14 includes a control driver 52, an input/output I/F 54, a computer 56, and a communication device 58 in addition to the image sensor 28. A signal processing circuit 36, a control driver 52, a computer 56, and a communication device 58 are connected to the input/output I/F 54.

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 processing regarding images. Here, an arithmetic processing unit including a CPU and a GPU is cited as an example of the processor 60, but this is just an example, and the processor 60 may be one or more CPUs with integrated GPU functions. , one or more CPUs without integrated GPU functionality.

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

The processor 60 reads a necessary program from the storage 62 and executes the read program on the RAM 64. Processor 60 controls control driver 52 and signal processing circuit 36 according to a program executed on RAM 64. The control driver 52 controls the photoelectric conversion element 34 under the control of the processor 60.

The communication device 58 is connected to the processor 60 via the input/output I/F 54 and the bus 66. Further, the communication device 58 is communicably connected to the processing device 90 by wire or wirelessly. The communication device 58 is in charge of exchanging information with the processing device 90 . For example, the communication device 58 transmits data in response to a request from the processor 60 to the processing device 90. 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.

As an example, as shown in FIG. 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 to generate a plurality of spectral images 72 according to a spectral image generation program 80 executed on the RAM 64 . The spectral image generation process is realized by the processor 60 operating as the output value acquisition section 82 and the interference removal processing section 84 according to the spectral image generation program 80.

As an example, as shown in FIG. 13, when the imaging data output from the image sensor 28 is input to the processor 60, the output value acquisition unit 82 calculates the output value Y of each physical pixel 44 based on the imaging data. get. The output value Y of each physical pixel 44 corresponds to the luminance value of each pixel included in the captured image 70 indicated by the captured image data.

Here, the output value Y of each physical pixel 44 is a value that includes interference (that is, crosstalk). That is, since light in each wavelength range λ of the first wavelength range λ ₁ , the second wavelength range λ ₂ , and the third wavelength range λ ₃ is incident on each physical pixel 44, the output value Y is The value is a mixture of a value corresponding to the light amount in the wavelength range λ ₁ , a value depending on the light amount in the second wavelength range λ ₂ , and a value depending on the light amount in the third wavelength range λ ₃ .

In order to obtain the spectral image 72, the processor 60 performs a process of separating and extracting a value corresponding to each wavelength range λ from the output value Y for each physical pixel 44, that is, a process of removing interference, which is a process of removing interference. Processing needs to be performed on the output value Y. Therefore, in this embodiment, in order to obtain the spectrum image 72, the interference removal processing section 84 performs interference removal processing on the output value Y of each physical pixel 44 obtained by the output value acquisition section 82.

Here, the interference removal process will be explained. The output value Y of each physical pixel 44 includes each brightness value for each polarization angle θ for red, green, and blue as a component of the output value Y. The output value Y of each physical pixel 44 is expressed by equation (3).

However, Y _{θ1_R} is the brightness value of the red component of the output value Y whose polarization angle is the first polarization angle θ ₁ , and Y _{θ2_R} is the brightness value of the component of the output value Y that is red and whose polarization angle is the second polarization angle θ. ₂ , Y _{θ3_R} is the brightness value of the red component of the output value Y whose polarization angle is the third polarization angle θ 3, and Y _{θ4_R} is the brightness value of the red component of the output value Y whose polarization angle is the third polarization angle θ ₃ . is the brightness value of the component whose fourth polarization angle is _θ4 .

Further, Y _{θ1_G} is the luminance value of the green component of the output value Y whose polarization angle is the first polarization angle θ ₁ , and Y _{θ2_G} is the luminance value of the component of the output value Y that is green and whose polarization angle is the second polarization angle θ. ₂ , Y _{θ3_G} is the luminance value of the component of the output value Y that is green and has a polarization angle of the third polarization angle θ 3, and Y _{θ4_G} is the luminance value of the component that is green and has the polarization angle of the third polarization angle θ ₃ of the output value Y. is the brightness value of the component whose fourth polarization angle is _θ4 .

Further, Y _{θ1_B} is the luminance value of the blue component of the output value Y whose polarization angle is the first polarization angle θ ₁ , and Y _{θ2_B} is the luminance value of the blue component of the output value Y whose polarization angle is the second polarization angle θ. ₂ , Y _{θ3_B} is the luminance value of the blue component of the output value Y whose polarization angle is the third polarization angle θ ₃ , and Y _{θ4_B} is the polarization angle of the blue component of the output value Y. is the brightness value of the component whose fourth polarization angle is _θ4 .

The pixel value X of each image pixel forming the spectral image 72 is the brightness value X λ1 of polarized light in a first wavelength range λ ₁ having a first polarization angle α ₁ (hereinafter referred to as “first wavelength range polarized light” ₎ . , the brightness value X _λ2 of polarized light in a second wavelength range λ ₂ having a second polarization angle α ₂ (hereinafter referred to as “second wavelength range polarized light”), and a third wavelength range λ having a third polarization angle α ₃ The pixel value X includes the luminance value X _λ3 of the polarized light of No. ₃ (hereinafter referred to as "third wavelength range polarized light") as a component of the pixel value X. The pixel value X of each image pixel is expressed by equation (4).

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

In equation (5), A is an interference matrix. The interference matrix A (not shown) is a matrix indicating characteristics of interference. The interference matrix A includes a plurality of known information 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 transmittance of the plurality of spectral filters 20, and the spectral sensitivity of the image sensor 28. predefined based on the value of .

When the interference cancellation matrix, which is the general inverse of the interference matrix A, is A ⁺ , the pixel value X of each image pixel is expressed by equation (6).

Similar to the interference matrix A, the interference removal matrix A ⁺ also includes the spectrum of the incident light, the spectral transmittance of the first lens 30, the spectral transmittance of the second lens 32, the spectral transmittance of the plurality of spectral filters 20, and the image sensor. This is a matrix defined based on the spectral sensitivity, etc. of No. 28. The interference cancellation matrix A ⁺ is stored in advance in the storage 62.

The interference cancellation processing unit 84 acquires 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 uses the acquired interference cancellation matrix A ⁺ Based on the output value Y of each physical pixel 44, the pixel value X of each image pixel is output using equation (6).

Here, as described above, the pixel value X of each image pixel is the brightness value X _λ1 of the first wavelength range polarized light, the brightness value X _λ2 of the second wavelength range polarized light, and the brightness value X _λ3 of the third wavelength range polarized light. are included as components of the pixel value X.

The spectral image 72A of the captured image 70 is an image corresponding to the brightness value X _λ1 of light in the first wavelength range λ ₁ (that is, an image based on the brightness value X _λ1 ). The spectral image 72B of the captured image 70 is an image corresponding to the brightness value X _λ2 of light in the second wavelength range λ ₂ (that is, an image based on the brightness value X _λ2 ). The spectral image 72C of the captured image 70 is an image corresponding to the brightness value X _λ3 of light in the third wavelength range λ ₃ (that is, an image based on the brightness value X _λ3 ).

In this way, by performing the interference removal process by the interference removal processing unit 84, the captured image 70 is divided into the spectrum image 72A corresponding to the brightness value X _λ1 of the first wavelength band polarized light and the brightness of the second wavelength band polarized light. It is separated into a spectral image 72B corresponding to the value X _λ2 and a spectral image 72C corresponding to the luminance value X _λ3 of the third wavelength band polarized light. That is, the captured image 70 is separated into spectral images 72 for each wavelength range λ of the plurality of spectral filters 20.

Next, the processing device 90 according to this embodiment will be explained in detail.

As shown in FIG. 14 as an example, the processing device 90 includes a computer 92. Computer 92 includes a processor 94, storage 96, and RAM 98. The processor 94, storage 96, and RAM 98 are realized by the same hardware as the above-described processor 60, storage 62, and RAM 64 (see FIG. 10).

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. Processor 94 executes color measurement processing to obtain color measurement results 136 according to color measurement program 100 executed on 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 according to 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.

As an example, as shown in FIG. 15, when the reference image 130 is obtained, the imaging device 10 transmits reference image data indicating the reference image 130 to the processing device 90. Furthermore, when the subject image 132 is obtained, the imaging device 10 transmits subject image data indicating 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.

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

Further, the image data acquisition unit 102 acquires the subject image data received by the processing device 90. The image data acquisition unit 102 then acquires a subject image 132 based on the subject image data. The object image 132 includes a spectrum image 72A in a first wavelength range λ ₁ (hereinafter referred to as "object spectrum image 72A") and a spectrum image 72B in a second wavelength range λ ₂ (hereinafter referred to as "object spectrum image 72B"). ) is included. Hereinafter, unless it is necessary to separately explain the subject spectrum image 72A and the subject spectrum image 72B, the subject spectrum image 72A and the subject spectrum image 72B will be referred to as "the subject spectrum image 72."

The calibration image generation unit 104 generates a calibration image 134 by calibrating the subject image 132 based on the reference image 130. Specifically, the calibration image generation unit 104 divides the pixel value of the subject spectrum image 72A by the pixel value of the reference spectrum image 72A for the first wavelength range λ ₁ , thereby generating a calibration image that is a calibrated spectrum image. A spectral image 134A is generated. Similarly, the calibration image generation unit 104 divides the pixel values of the object spectrum image 72B by the pixel values of the reference spectrum image 72B for the second wavelength range λ ₂ , thereby generating a calibration spectrum image that is a calibrated spectrum image. 134B. In this way, the processing device 90 performs calibration of the subject image data based on the reference image data.

Note that the calibration image generation unit 104 may calibrate a part of the image area of the subject spectrum image 72. For example, when the processing device 90 receives an instruction from a user specifying an image area in which color is to be measured (hereinafter referred to as a "user instruction"), the calibration image generation unit 104 selects one of the subject spectrum images 72. Calibration may be performed on an image area corresponding to a user instruction.

For example, when image processing is performed on the subject image 132 to extract an image area that includes the subject 2 as an image (hereinafter referred to as "subject image area"), the calibration image generation unit 104 Calibration may be performed on the subject image region of the subject spectrum image 72. Further, the calibration image generation unit 104 may perform calibration on a part of the image area of the subject image area. The image regions of the subject spectrum image 72 that have been calibrated by the calibration image generation unit 104 correspond to the calibration spectral image 134A and the calibration spectral image 134B.

Further, when the user instruction is accepted by the imaging device 10, the imaging device 10 generates reference image data indicating an image area corresponding to the user instruction in the reference image 130 and corresponding to the user instruction in the subject image 132. The subject image data indicating the image area to be photographed may be transmitted to the processing device 90.

The color derivation unit 106 derives the color of the subject 2 based on the calibration spectrum image 134A in the first wavelength range λ ₁ and the calibration spectrum image 134B in the second wavelength range λ ₂ generated by the calibration image generation unit 104. do. Specifically, the color derivation unit 106 derives the color CL of the subject 2 for each image pixel based on equation (7).
CL=(X _λ1 -X _λ2 )÷(X _λ1 +X _λ2 )...(7)

However, X _λ1 is the pixel value X of each image pixel forming the calibration spectrum image 134A in the first wavelength range λ ₁ , and X _λ2 is the pixel value X of each image pixel forming the calibration spectrum image 134B in the second wavelength range λ _2. This is the pixel value X of the pixel. Then, a color measurement result 136 is generated based on the color derived by the color derivation unit 106.

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. Further, measurement data indicating the color measurement result 136 may be transmitted to an external device (not shown) communicably connected to the processing device 90, and the color measurement result 136 may be used by the external device. Further, the color measurement results 136 may include an image indicating the measured color, or may include numerical values and/or graphs indicating the measured color.

Next, the operation of this embodiment will be explained. First, spectral image generation processing according to this embodiment will be explained. FIG. 16 shows an example of the flow of spectral image generation processing according to this embodiment.

In the spectral image generation process shown in FIG. 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 (FIG. reference). After the process of step ST10 is executed, the spectral image generation process moves to step ST12.

In step ST12, the interference cancellation processing unit 84 acquires the interference cancellation matrix A ⁺ stored in the storage 62 and the output value Y of each physical pixel 44 acquired in step ST10, and obtains the interference cancellation matrix A The pixel value X of each image pixel is output based on ⁺ and the output value Y of each physical pixel 44 (see FIG. 10). By executing the interference removal process in step ST12, the captured image 70 is divided into a spectrum image 72A corresponding to the brightness value X _λ1 of the first wavelength band polarized light and a spectrum corresponding to the brightness value X _λ2 of the second wavelength band polarized light. It is separated into an image 72B and a spectrum image 72C corresponding to the luminance value X _λ3 of the third wavelength band polarized light. After the process of step ST12 is executed, the spectral image generation process ends.

Next, color measurement processing according to this embodiment will be explained. FIG. 17 shows an example of the flow of color measurement processing according to this embodiment.

In the color measurement process shown in FIG. 17, first, in step ST20, the image data acquisition unit 102 acquires reference image data and subject image data. The image data acquisition unit 102 then acquires a reference image 130 indicated by the reference image data and a subject image 132 indicated by the subject image data. After the process of step ST20 is executed, the color measurement process moves to step ST22.

In step ST22, the calibration image generation unit 104 performs calibration on the subject image 132 based on the reference image 130 with respect to the reference image 130 and the subject image 132 acquired in step ST20. A calibration spectrum image 134A in one wavelength range λ ₁ and a calibration spectrum image 134B in a second wavelength range λ ₂ are generated. After the process of step ST22 is executed, the color measurement process moves to step ST24.

In step ST24, the color deriving unit 106 calculates the color of the subject 2 based on the calibration spectrum image 134A in the first wavelength range λ ₁ and the calibration spectrum image 134B in the second wavelength range λ ₂ generated in step ST22. Derive. As a result, a color measurement result 136 is obtained. After the process of step ST24 is executed, the color measurement process ends.

Note that the calibration method and color measurement method described as the functions of the processing device 90 described above are examples of the "calibration method" and the "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.

As detailed above, 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 constitutes the background of the subject 2. In each wavelength range λ, the first spectral reflectance a, which is the spectral reflectance of the light reflected by the subject 2, and the second spectral reflectance b, which is the spectral reflectance of the light reflected by the background surface 116A, are related to each other. (See Figure 2).

Therefore, the wavelength range of the incident light is suppressed from changing between when there is no subject 2 and when there is subject 2 (see FIG. 7). Thereby, it is possible to avoid measuring the color of the subject 2 darker than the actual color of the subject 2, as in the color measurement method according to the second comparative example (see FIG. 20). Further, the wavelength range of the peripheral reflected light L7 is suppressed from changing between the case where the subject 2 is not present and the case where the subject 2 is present. As a result, it is possible to avoid cases where the color of the subject 2 is measured to be lighter than the actual color of the subject 2 or the amount of flare changes, as in the color measurement method according to the second comparative example. can. As a result, the accuracy of measuring the color of the subject 2 can be improved compared to, for example, when the background surface 116A is a white surface.

Note that 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. Further, part of the color measurement process may be executed by the imaging device 10, and the remaining process of the color measurement process may be executed by the processing device 90.

Furthermore, in the embodiment described above, the housing device 120 is used in such a direction that the imaging device 10 is placed at the top of the housing 114 and the calibration member 116 is placed at the bottom of the housing 114. The orientation 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 at the bottom of the housing 114 and the calibration member 116 is disposed at the top of the housing 114. The housing device 120 may be used in an orientation in which the two faces are horizontally opposed.

Furthermore, for example, when the housing device 120 is used in a direction in which the calibration member 116 is arranged on the top of the housing 114 or in a direction in which the imaging device 10 and the calibration member 116 face each other in the horizontal direction, the subject 2 may be fixed to the background surface 116A.

Furthermore, 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, a calibration member 116 having a second spectral reflectance b corresponding to the first spectral reflectance a may be selected from among the plurality of calibration members 116.

Furthermore, in the embodiment described above, the processor 60 of the imaging device 10 may output warning information when the imaging conditions deviate from specific conditions. The warning information may be information for notifying the user that the angle of view should be adjusted. The notification may include at least one of sound notification, vibration notification, and light notification. By outputting the warning information, it is possible to make the user or the like recognize that the imaging conditions have deviated from the specific conditions.

Further, when adjusting the angle of view of the imaging device 10, a reference plate (not shown) is placed in a part of the imaging range of the imaging device 10, and the subject 2 and/or the calibration member 116 are placed. In this case, the processor 60 may determine whether the imaging conditions have deviated from the specific conditions based on a change in the captured image 70 obtained by the imaging device 10.

Further, in the above embodiment, the processor 60 is illustrated in 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 also be used.

Further, in the above embodiment, the processor 94 is illustrated as an example of 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 also be used.

Further, in the above embodiment, the imaging device 10 has been described using an example in which the spectral image generation program 80 is stored in the storage 62, but 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 "non-transitory storage medium") such as an SSD or a USB memory. The spectral image generation program 80 stored in a non-transitory storage medium may be installed on the computer 56 of the imaging device 10.

In addition, the spectral image generation program 80 is 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 is downloaded in response to a request from the imaging device 10. may be installed in the computer 56 of the imaging device 10.

Further, it is not necessary to store all of the 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, but only a part of the spectral image generation program 80 can be stored. You can leave it.

Furthermore, in the above embodiment, the processing device 90 has been described using 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. Color measurement program 100 stored on a non-transitory storage medium may be installed on computer 92 of processing device 90.

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

Further, it is not necessary to store the entire color measurement program 100 in a storage device such as another computer or server device connected to the processing device 90, or in the storage 96, but only a part of the color measurement program 100 may be stored. You can leave it there.

Further, although the imaging device 10 has a built-in computer 56, the technology of the present disclosure is not limited to this, and for example, the computer 56 may be provided outside the imaging device 10.

Further, 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.

Further, in the above embodiment, the computer 56 including the processor 60, the storage 62, and the RAM 64 is illustrated as an example of the imaging device 10, but the technology of the present disclosure is not limited to this, and instead of the computer 56, an ASIC, A device including an FPGA and/or a PLD may also be applied. Further, instead of the computer 56, a combination of hardware configuration and software configuration may be used.

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

Additionally, the following various processors can be used as hardware resources for executing the various processes described in the above embodiments. Examples of the processor include a CPU, which is a general-purpose processor that functions as a hardware resource that executes various processes by executing software, that is, a program. Examples of the processor include a dedicated electronic circuit such as an FPGA, a PLD, or an ASIC, which is a processor having a circuit configuration specifically designed to execute a specific process. Each processor has a built-in memory or is connected to it, and each processor uses the memory to perform various processes.

Hardware resources that execute various processes may be configured with one of these various processors, or a combination of two or more processors of the same type or different types (for example, a combination of multiple FPGAs, or a CPU and FPGA). Furthermore, the hardware resource that executes various processes may be one processor.

As an example of a configuration using one processor, firstly, one processor is configured by a combination of one or more CPUs and software, and this processor functions as a hardware resource that executes various processes. Second, there is a form of using a processor, as typified by an SoC, in which a single IC chip realizes the functions of an entire system including a plurality of hardware resources that execute various processes. In this way, various types of processing are realized using one or more of the various types of processors described above as hardware resources.

Furthermore, as the hardware structure of these various processors, more specifically, an electronic circuit that is a combination of circuit elements such as semiconductor elements can be used. Further, the above line of sight detection processing is just 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 main idea.

The descriptions and illustrations described above are detailed explanations of the parts related to the technology of the present disclosure, and are merely examples of the technology of the present disclosure. For example, the above description regarding the configuration, function, operation, and effect is an example of the configuration, function, operation, and effect of the part related to the technology of the present disclosure. Therefore, unnecessary parts may be deleted, new elements may be added, or replacements may be made to the written and illustrated contents described above without departing from the gist of the technology of the present disclosure. Needless to say. In addition, in order to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the descriptions and illustrations shown above do not include parts that require particular explanation in order to enable implementation of the technology of the present disclosure. Explanations regarding common technical knowledge, etc. that do not apply are omitted.

In this specification, "A and/or B" has the same meaning as "at least one of A and B." That is, "A and/or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, even when three or more items are expressed by connecting them with "and/or", the same concept as "A and/or B" is applied.

All documents, patent applications, and technical standards mentioned herein are incorporated herein by reference to the same extent as if each individual document, patent application, and technical standard was specifically and individually indicated to be incorporated by reference. Incorporated by reference into this book.

Regarding the above embodiments, the following additional notes are further disclosed.

(Additional note 1)
comprising the calibration member according to claim 1 and a processor,
The processor includes:
obtaining first imaging data obtained by imaging the calibration member by 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 image data based on the first image data;
A color measurement device that measures the color of the subject based on the second image data that has been calibrated.
(Additional note 2)
a first acquisition step of acquiring first imaging data obtained by imaging the calibration member according to claim 1 with the spectroscopic imaging device;
a second acquisition step of acquiring second imaging data obtained by imaging the calibration member and the subject with the spectroscopic imaging device;
a calibration step of calibrating the second image data based on the first image data;
a color measurement step of measuring the color of the subject based on the second image data that has been calibrated;
A color measurement method comprising:
(Appendix 3)
a first acquisition step of acquiring first imaging data obtained by imaging the calibration member according to claim 1 with the spectroscopic imaging device;
a second acquisition step of acquiring second imaging data obtained by imaging the calibration member and the subject with the spectroscopic imaging device;
a calibration step of calibrating the second image data based on the first image data;
a color measurement step of measuring the color of the subject based on the second image data that has been calibrated;
A program that causes a computer to perform processing, including processing.

Claims

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 the background of the subject,
In the wavelength range, a first spectral reflectance that is the spectral reflectance of the light reflected by the subject and a second spectral reflectance that is the spectral reflectance of the light reflected by the background surface have a relationship with each other. Calibration parts.
The calibration member according to claim 1, wherein the relationship is such that a difference between the first spectral reflectance and the second spectral reflectance is within a first range.
The calibration member according to claim 2, wherein the first range is from a reflectance 0.5 times the first spectral reflectance to a reflectance twice the first spectral reflectance.
The calibration member according to claim 2 or 3, wherein the first range is set based on a third spectral reflectance that is a spectral reflectance of light reflected by the first reference plate.
The first reference plate has a reflective surface that reflects the light,
The calibration member according to claim 4, wherein the reflective surface is a white surface.
The calibration member according to claim 4 or 5, 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. .
The calibration member according to any one of claims 4 to 6, wherein the second spectral reflectance is lower than the third spectral reflectance.
The calibration member according to any one of claims 4 to 7, wherein the first spectral reflectance is lower than the third spectral reflectance.
The second spectral reflectance falls within a second range of spectral reflectances set based on the first spectral reflectance and the third spectral reflectance. Calibration parts.
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.
When the first spectral reflectance is a, the second spectral reflectance is b, and the third spectral reflectance is c,
The second range is defined by formula (2): 3a/4≦b≦(c+3a)/4 (2)
The calibration member according to claim 9.
The calibration member according to any one of claims 1 to 11, wherein the first spectral reflectance is a spectral reflectance based on spectral reflectances measured at a plurality of locations on the subject.
The specific wavelength range includes a plurality of wavelength ranges,
In each of the wavelength ranges, 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. , and the calibration member according to any one of claims 12 and 12 depending on claim 4.
The calibration member according to any one of claims 1 to 13, wherein the background surface has a surface roughness corresponding to that of the subject.
15. The spectral reflectance of the background surface is higher in a first near-infrared region of the near-infrared region than in a first visible region of the visible region. Calibration parts.
A calibration member according to any one of claims 1 to 15,
a housing that covers an imaging space in which the calibration member and the subject are arranged;
A housing device comprising:
The calibration member according to any one of claims 1 to 15, the spectral imaging device, a light source, and a housing,
The housing covers an imaging space in which the calibration member and the subject are arranged,
The imaging conditions for imaging the subject with the spectroscopic imaging device are such that the first component of the incident light that enters the spectroscopic imaging device is light irradiated from the light source and reflected by the subject and the calibration member. The first condition is a calibration device.
Equipped with a processor,
The calibration device according to claim 17, wherein the processor outputs warning information when the imaging condition deviates from the first condition.
comprising the calibration member according to any one of claims 1 to 15 and a processor,
The processor includes:
obtaining first imaging data obtained by imaging the calibration member by the spectroscopic imaging device;
acquiring second imaging data obtained by imaging the calibration member and the subject by the spectroscopic imaging device;
A calibration device that calibrates the second image data based on the first image data.
a first acquisition step of acquiring first imaging data obtained by imaging the calibration member according to any one of claims 1 to 15 with the spectroscopic imaging device;
a second acquisition step of acquiring second imaging data obtained by imaging the calibration member and the subject with the spectroscopic imaging device;
A calibration method comprising: a calibration step of calibrating the second image data based on the first image data.
a first acquisition step of acquiring first imaging data obtained by imaging the calibration member according to any one of claims 1 to 15 with the spectroscopic imaging device;
a second acquisition step of acquiring second imaging data obtained by imaging the calibration member and the subject with the spectroscopic imaging device;
a calibration step of calibrating the second image data based on the first image data; and a program for causing a computer to execute a process.