Spectrometer, spectrometric result display method, and spectrometric result display program

Abstract

To provide a spectrometer, a spectrometric result display method, and a spectrometric result display program that can more accurately detect color information held by an object and can display the detected color information in an intuitively understandable manner.SOLUTION: A spectrometer comprises: a spectrometric unit that performs spectrometry on an object to acquire a spectral image; a display unit; and a control unit that generates Lab visualization information from the spectral image, and displays the Lab visualization information on the display unit. The Lab visualization information is preferably an L image obtained by converting an L value into luminance for each pixel, an a image obtained by converting an a value into luminance for each pixel, and a b image obtained by converting a b value into luminance for each pixel.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a spectroscopic measurement device, a method for displaying a result of spectroscopic measurement, and a program for displaying a result of spectroscopic measurement. [Background technology]

[0002] A color unevenness inspection device that acquires a spectral image of an object and inspects the object for color unevenness is being considered for application in a variety of fields because it can quantitatively evaluate color unevenness of the object.

[0003] For example, Patent Document 1 discloses a skin color unevenness display device that includes a calculation means for calculating the color difference between adjacent pixels for each pixel of a skin image of a subject, and a display means for displaying the occurrence frequency of the calculated color difference values ​​in a graph or chart. In this color unevenness display device, an RGB image of the skin is first acquired by a digital camera, and this RGB image is converted into an L*a*b* image. Next, the color difference of adjacent pixels is calculated from the L*a*b* image. Then, the calculated color difference values ​​are divided into groups based on the values, and the composition ratio of each group is graphed and displayed. This allows the degree of color unevenness to be intuitively recognized. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2022-157667 A Summary of the Invention [Problem to be solved by the invention]

[0005] RGB images can only express a part of the color gamut visible to the human eye. For this reason, the L*a*b* image obtained by the color unevenness display device described in Patent Document 1 may lack the color information that the object originally possesses. This may result in the color unevenness inspection device being unable to accurately detect the color unevenness of the object. On the other hand, there is also a challenge in displaying the color unevenness detection results in an easy-to-understand manner and conveying them intuitively to the user, even when the detected color unevenness is minute, for example.

[0006] Therefore, it is necessary to realize a spectroscopic measurement device that can detect color information of an object more accurately and display the detected color information in a manner that allows the user to intuitively understand it. [Means for solving the problem]

[0007] A spectroscopic measurement device according to an application example of the present invention includes: a spectroscopic measurement unit that performs spectroscopic measurement of an object and acquires a spectroscopic image; A display unit; a control unit that generates Lab visualization information from the spectroscopic image and displays the Lab visualization information on the display unit; Equipped with.

[0008] A spectroscopic measurement result display method according to an application example of the present invention includes: A method for displaying a spectroscopic measurement result of an object on a display unit, comprising: acquiring a spectral image of the object; generating Lab visualization information from the spectroscopic images; displaying the Lab visualization information on the display unit; has.

[0009] A spectroscopic measurement result display program according to an application example of the present invention includes: A spectroscopic measurement result display program that causes a computer to perform a process of displaying a spectroscopic measurement result of an object on a display unit, On the computer, A spectroscopic image acquisition process for acquiring a spectroscopic image of the object; A Lab information generation process for generating Lab visualization information from the spectroscopic image; A Lab information display process for displaying the Lab visualization information on the display unit; Have them carry out the procedure. [Brief description of the drawings]

[0010] [Figure 1] 1 is a schematic diagram showing a spectroscopic measurement device according to a first embodiment. [Diagram 2] 2 is a functional block diagram of the spectroscopic measurement device shown in FIG. 1. [Diagram 3] 3 is a diagram illustrating an example of a hardware configuration for implementing the functions of each functional unit included in the spectroscopic measurement device of FIG. 2. [Figure 4] 4 is a flowchart showing the configuration of a spectroscopic measurement result display method according to the first embodiment. [Diagram 5] 13 is an example of a display screen including a preview image displayed in a preview image obtaining step and a Lab image displayed in a Lab image displaying step. [Figure 6] 13 is an example of an input screen for supporting input of an environmental setting value in an environmental setting value receiving step. [Figure 7] 13 is an example of an input screen for assisting input of normalization parameters in the normalization processing step. [Figure 8] 13 is a flowchart showing the configuration of a spectroscopic measurement result display method according to a modified example of the first embodiment. [Figure 9] 13 is an example of a display screen including a preview image and a setting field that are displayed in a preview image obtaining step in a modified example of the first embodiment. [Figure 10] 13 is an example of a display screen including an L image displayed in a Lab image display step in a modified example of the first embodiment. [Figure 11] 13 is an example of a display screen including an L image after image processing has been performed in the image processing step. [Figure 12] 13 is an example of a display screen including an L image after image processing has been performed in the image processing step. [Figure 13]10 is a flowchart showing the configuration of a spectroscopic measurement result display method according to a second embodiment. [Figure 14] 13 is an example of a display screen including a preview image displayed in a preview image obtaining step and a Lab histogram displayed in a Lab histogram display step in the second embodiment. [Figure 15] FIG. 13 is a conceptual diagram showing an example of the differences between an L histogram, a histogram, and b histogram. [Figure 16] 13 is a flowchart showing the configuration of a spectroscopic measurement result display method according to a modified example of the second embodiment. [Figure 17] 13 is an example of a display screen including a preview image and a setting field that are displayed in a preview image obtaining step in a modified example of the second embodiment. [Figure 18] 13 is an example of a display screen including an L histogram displayed in a Lab histogram display step in a modified example of the second embodiment. [Figure 19] 1 is a graph showing a scatter diagram in which reference data and measured data are plotted, and a regression line obtained by linearly approximating the plot marks. [Figure 20] Graph HS is the reference data, graph HM is the measured data, and graph HD is the difference obtained by subtracting graph HM from graph HS. [Figure 21] 1 is a conceptual diagram showing the distance between a range A occupied by a plurality of pass data, a range B occupied by a plurality of fail data, and measurement data M. FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a spectroscopic measurement device, a spectroscopic measurement result display method, and a spectroscopic measurement result display program according to the present invention will be described in detail with reference to the embodiments shown in the accompanying drawings.

[0012] 1. First embodiment First, the first embodiment will be described.

[0013] 1.1.Spectrometer Fig. 1 is a schematic diagram showing a spectroscopic measurement device 1 according to a first embodiment. Fig. 2 is a functional block diagram of the spectroscopic measurement device 1 shown in Fig. 1.

[0014] 1.1.1. Equipment Overview 1 includes a control unit 2, a spectroscopic measurement unit 3, an input unit 52, a display unit 54, a storage unit 56, a stage 61, and a light source 62. The spectroscopic measurement device 1 performs spectroscopic measurement of an object W to obtain a spectroscopic image. The spectroscopic measurement refers to obtaining a spectrum (spectroscopic data) by dispersing light reflected by the object W for each pixel. The spectroscopic image refers to cube data that compiles images for each spectroscopic wavelength.

[0015] The control unit 2 controls the operation of the spectroscopic measurement unit 3. The control unit 2 also has a function of receiving input from an input unit 52, a function of displaying information on a display unit 54, a function of writing and reading information to and from a storage unit 56, and the like.

[0016] The spectroscopic measurement unit 3 has a spectroscopic unit and an image sensor, not shown. Light irradiated from the light source 62 is reflected by the object W and enters the spectroscopic measurement unit 3 as reflected light. The spectroscopic unit is an optical element having a function of selecting light in a specific wavelength region from the reflected light. The selected light enters the image sensor. The image sensor is an image sensor having a function of detecting a two-dimensional distribution of the intensity of the incident light. By switching the specific wavelength selected by the spectroscopic unit, the image sensor can capture two-dimensional images at various wavelengths. This allows a spectroscopic image to be obtained. The spectroscopic measurement unit 3 may have a function of acquiring, for example, a monochrome image, an RGB image, etc. These images can be acquired in a shorter time than spectroscopic images, and therefore can be used as preview images.

[0017] The input unit 52 accepts an input operation by a user of the spectroscopic measurement device 1. The input information accepted by the input unit 52 is transmitted to the control unit 2.

[0018] The display unit 54 displays the display information output from the control unit 2. This allows the user of the spectroscopic measurement device 1 to visually recognize the display information.

[0019] The storage unit 56 stores programs, data, setting values, etc., necessary for the operation of the control unit 2. The storage unit 56 corresponds to reading of programs, etc. from the control unit 2 and writing of data, etc.

[0020] The stage 61 is a platform on which the object W is placed. The light source 62 irradiates light onto the object W. The light source 62 may be configured to appropriately use different irradiation methods depending on the type of the object W, etc.

[0021] 1.1.2.Control Unit The control unit 2 shown in FIG. 2 has, as functional units, a measurement control unit 204, an environmental setting value receiving unit 206, a Lab information calculation unit 208, a normalization processing unit 210, a display control unit 212, an image processing unit 216, and a pass / fail determination unit 218.

[0022] The measurement control unit 204 controls the operation of the spectroscopic measurement unit 3 and causes the spectroscopic measurement unit 3 to acquire a spectroscopic image and a preview image. The measurement control unit 204 stores the acquired spectroscopic image and preview image in the storage unit 56. The acquisition of the spectroscopic image and the preview image is executed by, for example, an input operation via the input unit 52.

[0023] The environment setting value receiving unit 206 receives the environment setting values ​​used when generating the L image, a image, or b image from the spectral image. The L image is an image obtained by converting the L value to luminance for each pixel. The a image and the b image are images obtained by converting the a value and the b value to luminance for each pixel. In this specification, the "L value" refers to the L* value that represents the lightness in the L*a*b* color space standardized by the International Commission on Illumination (CIE) in 1976. In addition, in this specification, the "a value" refers to the a* value that represents the chromaticity in the L*a*b* color space. Furthermore, in this specification, the "b value" refers to the b* value that represents the chromaticity in the L*a*b* color space. Examples of the environment setting values ​​include color matching functions and illumination light sources, and one or both of these are used. In the following description, at least one of the L value, a value, and b value is also referred to as the "Lab value". In addition, at least one of the L image, a image, and b image is also referred to as the "Lab image". In this specification, a "Lab image" is a type of Lab visualization information obtained by extracting and visualizing at least one of the L value, a value, and b value for each pixel.

[0024] Color matching functions are functions that represent the spectral sensitivity of the human eye. Examples of color matching functions include the CIE 1931 standard observer colorimetric function (2-degree field of view color matching function) and the CIE 1964 auxiliary standard observer colorimetric function (10-degree field of view color matching function).

[0025] The illumination light source is a standard light source defined to reproduce the illumination environment. Examples of illumination light sources include CIE Standard Illuminant D50, CIE Standard Illuminant D65, Incandescent A, Standard Illuminant C, Cool White Fluorescent CWF, and Fluorescent TL84.

[0026] The Lab information calculation unit 208 generates a Lab image based on the spectral image and the environmental setting value. Specifically, the L value, a value, and b value are extracted for each pixel from the spectral data for each pixel included in the spectral image based on the environmental setting value. Then, the L value is converted to luminance to generate the L image. For example, when the L image is a bitmap image with 256 gradations, the minimum value of the extracted L value may be made to correspond to luminance 0, and the maximum value of the L value may be made to correspond to luminance 255. In the same manner, the a value is converted to luminance to generate the a image, and the b value is converted to luminance to generate the b image. By generating the Lab image based on the environmental setting value, a Lab image in which color information of the object W is extracted with higher accuracy can be obtained. Note that the correspondence between the Lab value and the luminance is not limited to the above method.

[0027] The normalization processing unit 210 performs a process of normalizing the width of each luminance of the L image, the a image, and the b image. This normalization process is performed based on the ranges of the extracted L value, the a value, and the b value. Each range may be an arbitrarily specified range other than the range from the minimum value to the maximum value of the Lab value described above.

[0028] For example, the normalization processing unit 210 may perform a process of determining each of the above ranges based on each range of Lab values ​​in a two-dimensional region inputted by the input unit 52. The normalization processing unit 210 may also perform a process of determining each of the above ranges based on a designated value inputted by the input unit 52. In this specification, these two-dimensional regions and designated values ​​are also referred to as "normalization parameters."

[0029] The display control unit 212 has a function of displaying Lab images and the above-mentioned preview image on the display unit 54. The display control unit 212 may also have a function of displaying on the display unit 54, for example, a GUI (Graphical User Interface) screen that accepts input or selection of environmental setting values, a GUI screen that accepts input of normalization parameters, the results of image processing by the image processing unit 216, the results of pass / fail determination processing by the pass / fail determination unit 218, and the like.

[0030] FIG. 3 is a diagram showing an example of a hardware configuration for realizing the functions of each functional unit included in the spectroscopic measurement device 1 of FIG.

[0031] The functions of the functional units of the spectroscopic measurement device 1 are realized by hardware including, for example, a CPU 41, a memory 42, a hard disk 43, a mouse 44, a keyboard 45, a monitor 46, an external interface 47, and an external bus 48, as shown in Fig. 3. Of these, the CPU 41, the memory 42, the hard disk 43, the external interface 47, and the external bus 48 are, for example, a computer.

[0032] The CPU 41 is a central processing unit. Examples of the memory 42 include any non-volatile memory element (ROM), any volatile memory element (RAM), and a removable external memory element. Examples of the external interface 47 include a digital input / output port such as a Universal Serial Bus (USB), an Ethernet port, and a video output port. The hard disk 43 stores a program 432, data 434, and an OS 436. The program 432 includes a spectroscopic measurement result display program described later. The data 434 is, for example, a spectroscopic image, a Lab image, an environmental setting value, a normalization parameter, and the like. The OS 436 is an operating system. The hard disk 43 may be, for example, a storage medium such as a flash memory or a solid state drive (SSD). In addition, all or a part of the hardware may be composed of a field-programmable gate array (FPGA), an application specific integrated circuit (ASIC), or the like. In addition, instead of or in addition to at least one of the mouse 44 and the keyboard 45, for example, a touch panel, a touch pad, a microphone, and the like may be provided.

[0033] The program 432 is loaded into the memory 42 and executed by the CPU 41. When the CPU 41 executes the program 432, the functions of the above-mentioned functional units are realized.

[0034] The spectroscopic measurement result display program may be stored in a non-volatile storage medium (a computer-readable storage medium). The program 432 and the data 434 may be provided from an external source via a network.

[0035] 1.2. How to display spectroscopic measurement results Next, a spectroscopic measurement result display method according to the first embodiment will be described.

[0036] Fig. 4 is a flowchart showing the configuration of a spectroscopic measurement result display method according to the first embodiment. The spectroscopic measurement result display method shown in Fig. 4 is performed, for example, by the CPU 41 executing a spectroscopic measurement result display program and the OS 436 included in the program 432. Note that the method may be performed by the CPU 41 executing only the spectroscopic measurement result display program.

[0037] The spectroscopic measurement result display method shown in FIG. 4 includes a preview image acquisition step S102, an environment setting value reception step S104, a spectroscopic image acquisition step S106, a Lab image generation step S108, a Lab image display step S110, and a normalization processing step S112.

[0038] 1.2.1. Preview image acquisition step In the preview image acquisition step S102, the computer is caused to perform a preview image acquisition process and a preview image display process.

[0039] 5 is an example of a display screen 702 including a preview image 703 displayed in the preview image acquisition step S102 and a Lab image 704 displayed in the Lab image display step S110. In this embodiment, a tomato is illustrated as the object W.

[0040] The display screen 702 shown in FIG. 5 has a preview image 703, a Lab image 704, a comparison image 705, a preview image acquisition button 707, a spectral image acquisition button 708, a Lab switching button 709, a normalization process button 711, a normalization parameter button 712, and an environmental setting value button 713.

[0041] The preview image acquisition process is a process in which the measurement control unit 204 shown in FIG. 2 controls the operation of the spectroscopic measurement unit 3 to acquire a preview image 703 shown in FIG. 5. The preview image display process is a process in which the display control unit 212 shown in FIG. 2 displays the preview image 703 on the display unit 54. When the preview image acquisition button 707 shown in FIG. 5 is pressed, the preview image acquisition process and the preview image display process are executed. The preview image 703 is acquired in a shorter time than a spectroscopic image, and therefore represents the appearance of the object W in almost real time. Therefore, the user of the spectroscopic measurement device 1 can efficiently perform the arrangement of the object W, the distance between the object W and the spectroscopic measurement unit 3, focus adjustment, lens replacement, adjustment of the light source 62, and the like while viewing the preview image 703.

[0042] 1.2.2. Environment setting value acceptance step In the environment setting value receiving step S104, the computer performs an environment setting value receiving process.

[0043] The environment setting value receiving process is a process in which the environment setting value receiving unit 206 shown in Fig. 2 receives an environment setting value. The environment setting value may be stored in advance in the storage unit 56, or may be input via the input unit 52.

[0044] FIG. 6 shows an example of an input screen 715 that supports input of the environmental setting values ​​in the environmental setting value receiving step S104.

[0045] When the environmental setting value button 713 shown in Fig. 5 is pressed, an input screen 715 shown in Fig. 6 is displayed on the display unit 54. The input screen 715 has a selection field 716 for selecting the type of color matching function and a selection field 717 for selecting the type of illumination light source. The selection fields 716 and 717 are pull-down menus, and the desired type can be selected from preset options.

[0046] 1.2.3.Spectral image acquisition step In the spectroscopic image acquisition step S106, the computer is caused to perform a spectroscopic image acquisition process.

[0047] The spectroscopic image acquisition process is a process in which the measurement control unit 204 shown in Fig. 2 controls the operation of the spectroscopic measurement unit 3 to acquire a spectroscopic image (not shown). When the spectroscopic image acquisition button 708 shown in Fig. 5 is pressed, the spectroscopic image acquisition process is executed. The acquired spectroscopic image is stored in the storage unit 56.

[0048] 1.2.4.Lab Image Generation Steps In the Lab image generating step S108, the computer is caused to perform a Lab image generating process (Lab information generating process).

[0049] When the spectral image acquisition button 708 shown in FIG. 5 is pressed, the Lab image generation process is executed following the spectral image acquisition process, and the Lab image 704 is generated. The Lab image generation process is a process in which the Lab information calculation unit 208 shown in FIG. 2 generates the Lab image 704. Specifically, at least one of the L value, the a value, and the b value is extracted for each pixel from the spectral image acquired in the spectral image acquisition process, and visualized. The visualization refers to a process of, for example, imaging, graphing, patterning, etc., on the Lab value. In this embodiment, the Lab value is visualized to generate the Lab image 704 (Lab visualization information). The Lab image 704 is an L image obtained by converting the L value to luminance for each pixel. Note that, instead of the L image, an a image obtained by converting the a value to luminance for each pixel, or a b image obtained by converting the b value to luminance for each pixel may be used. Note that, in the Lab image generation process, the environment setting value stored in the storage unit 56 is used.

[0050] In addition, the Lab image 704 is configured to display one of the L image, the a image, and the b image. Furthermore, two or more images may be displayed simultaneously. The displayed image can be switched using the Lab switching button 709 shown in FIG.

[0051] The L value represents lightness in the L*a*b* color space, and the a and b values ​​represent chromaticity. The a value represents chromaticity between red and green, and the b value represents chromaticity between yellow and blue. Therefore, by appropriately selecting either the L image, the a image, or the b image, it is possible to generate a Lab image 704 in which even subtle color unevenness is sufficiently emphasized.

[0052] In the above-mentioned preview image acquisition process, when the preview image acquisition button 707 shown in FIG. 5 is pressed, a search window SW shown in FIG. 5 may be displayed together with the preview image 703. By specifying a two-dimensional area in the preview image 703 using the search window SW, the range of each luminance of the Lab image 704 can be set in generating the Lab image 704. Each minimum value and each maximum value of the Lab values ​​in this two-dimensional area can be assigned to each minimum value and each maximum value of the luminance of the Lab image 704. The position, size, and shape of the search window SW can be specified by the input unit 52. This allows the Lab image 704 to be generated within a desired range of luminance.

[0053] Instead of using the search window SW, each range of Lab values ​​may be obtained from the entire preview image 703.

[0054] 1.2.5.Lab image display steps In the Lab image display step S110, the computer is caused to perform Lab image display processing (Lab information display processing).

[0055] The Lab image display process is a process in which the display control unit 212 shown in FIG. 2 displays a Lab image 704 on the display unit 54. The preview image 703 shows an object image IW. The Lab image 704 shows an object image LW. The object image LW shows color unevenness ST that is not recognized in the object image IW. By displaying the Lab image 704 in this way, it becomes possible to detect color unevenness (color information possessed by the object W) that cannot be captured in a normal monochrome image or RGB image. By displaying such a Lab image 704, the color information possessed by the object W can be displayed in a manner that allows for more intuitive understanding.

[0056] 5, a comparison image 705 is displayed alongside the Lab image 704. The comparison image 705 is an image that is stored in advance in the storage unit 56 or an image that is input at any timing, and is an image that is used for comparison with the Lab image 704. By displaying the comparison image 705 alongside the Lab image 704, the user of the spectroscopic measurement device 1 can easily compare the two images. As a result, the comparison image 705 can be used as a color sample, and therefore, when the user is judging whether or not the color information of the color unevenness ST is to be rejected, for example, this can assist in accurate judgment.

[0057] 1.2.6. Normalization Step In normalization step S112, a computer performs normalization processing. This step can be performed as necessary when the Lab image 704 generated by the Lab image generation process is not appropriate.

[0058] The normalization process in this step is a process in which the normalization processing unit 210 shown in Fig. 2 normalizes each luminance range of the Lab image based on the normalization parameter. As a result, a desired value is set for each range of the Lab value.

[0059] FIG. 7 shows an example of an input screen 720 that supports input of normalization parameters in the normalization processing step S112.

[0060] When the normalization parameter button 712 shown in Fig. 5 is pressed, an input screen 720 shown in Fig. 7 is displayed on the display unit 54. The input screen 720 has, as an example, sliders 722 and 723 that receive designated values ​​of normalization parameters for the a image. By sliding the slider 722 via the input unit 52, the maximum value of the a value can be specified, and by sliding the slider 723, the minimum value of the a value can be specified.

[0061] After the normalization parameters are specified, pressing a normalization process button 711 shown in Fig. 5 executes the normalization process. This updates the luminance ranges of the Lab image based on the normalization parameters. The updated Lab image 704 is then displayed in Fig. 5. By updating the Lab image 704, the luminance resolution can be further improved, and for example, the color unevenness ST shown in Fig. 5 can be displayed more clearly.

[0062] The method of inputting the normalization parameters is not limited to the above. For example, the search window SW may be changed to re-specify the two-dimensional region, or a specified value may be input in text. In the former case, normalization processing is performed based on each range of Lab values ​​in the two-dimensional region. In the latter case, normalization processing is performed based on a specified value input in text. This makes it possible to perform normalization processing as intended, and a Lab image 704 with sufficiently improved luminance resolution can be obtained.

[0063] Although the spectroscopic measurement result display method according to the first embodiment has been described above, some of the above steps may be omitted, or may be replaced with steps having equivalent configurations. Also, the order of the steps may be changed.

[0064] 2. Modification of the First Embodiment Next, a modification of the first embodiment will be described.

[0065] FIG. 8 is a flowchart showing the configuration of a spectroscopic measurement result display method according to a modified example of the first embodiment.

[0066] Modifications of the first embodiment will be described below, but in the following description, differences from the first embodiment will be mainly described, and descriptions of similar matters will be omitted. In each drawing, the same reference numerals are used for the same configurations as in Figs. 1 to 7.

[0067] The modified example of the first embodiment is similar to the first embodiment, except that a pass / fail determination of the color information of the object W is performed based on the generated Lab image.

[0068] The spectroscopic measurement result display method shown in FIG. 8 includes a preview image acquisition step S102, an environment setting value reception step S104, a spectroscopic image acquisition step S106, a Lab image generation step S108, a Lab image display step S110, a normalization processing step S112, an image processing step S114, a pass / fail determination step S116, and a determination result display step S118.

[0069] 2.1. Preview image acquisition step In the preview image acquisition step S102, the computer is caused to perform a preview image acquisition process and a preview image display process.

[0070] FIG. 9 shows an example of a display screen 702 including a preview image 703 and a setting field 730 displayed in the preview image acquisition step S102 in the modified example of the first embodiment.

[0071] A display screen 702 shown in FIG. 9 has a preview image 703 , a preview image acquisition button 707 , a spectral image acquisition button 708 , a normalization processing button 711 , a setting field 730 , a pass / fail determination result 731 , an image processing button 732 , and a pass / fail determination button 733 .

[0072] 2.2. Environment setting value reception step In the environment setting value receiving step S104, the computer performs an environment setting value receiving process.

[0073] 9 accepts input of setting values ​​for each setting item. Examples of setting items include environmental setting values ​​such as color matching functions and illumination light sources, normalization parameters such as the minimum L value, the maximum L value, the minimum a value, the maximum a value, the minimum b value, and the maximum b value, various threshold values, etc. These environmental setting values ​​and normalization parameters are stored in the storage unit 56.

[0074] 2.3.Spectral image acquisition step In the spectroscopic image acquisition step S106, the computer is caused to perform a spectroscopic image acquisition process.

[0075] 2.4.Lab image generation step In the Lab image generating step S108, the computer is caused to perform a Lab image generating process (Lab information generating process).

[0076] The Lab image generation process generates a Lab image (Lab visualization information) based on the environment setting values ​​and normalization parameters stored in the storage unit 56. Note that, for the normalization parameters, each range of Lab values ​​in a two-dimensional region specified in the search window SW shown in Fig. 9 may be used, or a designated value of the Lab value input in the setting field 730 shown in Fig. 9 may be used.

[0077] 2.5.Lab image display steps In the Lab image display step S110, the computer is caused to perform Lab image display processing (Lab information display processing).

[0078] FIG. 10 is an example of a display screen 702 including an L image 735 displayed in the Lab image display step S110 in the modified example of the first embodiment.

[0079] An L image 735 shown in Fig. 10 is an example of a Lab image. When a spectral image acquisition button 708 shown in Fig. 9 is pressed, a spectral image acquisition process and a Lab image generation process are executed, and the preview image 703 transitions to an L image 735. Note that Fig. 10 is provided with a switching button (not shown) that allows one or more of the L image, a image, and b image to be selected and displayed.

[0080] 2.6. Normalization Step In normalization step S112, a computer performs normalization processing. This step can be performed as necessary when the Lab image 704 generated by the Lab image generation process is not appropriate.

[0081] 10, an L image 735 and a setting field 730 (input receiving screen) for receiving input of normalization parameters are arranged side by side. This allows more appropriate normalization parameters to be input while observing changes in the L image 735.

[0082] 2.7. Image Processing Steps In image processing step S114, image processing is performed by a computer. Note that image processing step S114 may be performed as necessary and may be omitted.

[0083] 11 and 12 are each an example of a display screen 702 including an L image 735 after image processing in image processing step S114.

[0084] 10 is pressed, image processing is executed on the L image 735. The image processing is not particularly limited, but examples thereof include binarization processing, block detection processing, and the like.

[0085] The binarization process binarizes the luminance of each pixel of the L image 735 based on a preset threshold value. The binarization process emphasizes the color unevenness ST contained in the L image 735. Note that instead of the binarization process, any process that enhances the contrast between the color unevenness ST and other areas may be used.

[0086] The lump detection process detects lump in the L image 735 or the L image 735 that has been subjected to high contrast processing such as binarization processing, based on a preset threshold value. The lump detection makes it possible to identify the area occupied by the color unevenness ST. This makes it possible to quantitatively evaluate the size of the color unevenness ST. FIG. 11 includes an indicator Ind that shows the range detected as a lump by the lump detection process.

[0087] 2.8. Pass / Fail Judgment Step In pass / fail determination step S116, the computer performs pass / fail determination.

[0088] When the pass / fail judgment button 733 shown in FIG. 11 is pressed, a pass / fail judgment is made on the L image 735 that has been subjected to image processing. The pass / fail judgment is made, for example, based on the size and number of indicators Ind shown in FIG. 11. If the size and number of indicators Ind meet a threshold, it is judged as pass. For example, no indicators Ind are displayed in FIG. 12. Therefore, the L image 735 shown in FIG. 12 can be judged as pass. On the other hand, if the size and number of indicators Ind do not meet the threshold, it is judged as fail.

[0089] 2.9. Displaying the Judgment Result In the determination result display step S118, the computer is caused to perform a determination result display process.

[0090] When the pass / fail determination is made in pass / fail determination step S116, characters or the like indicating the determination result are displayed in pass / fail determination result 731 shown in Fig. 11 and Fig. 12. For example, "fail" is displayed in Fig. 11, and "pass" is displayed in Fig. 12. By making the pass / fail determination based on L image 735 in this way, the color information of object W can be inspected more accurately. In the above modified example as well, the same effects as in the first embodiment can be obtained.

[0091] 3. Second embodiment Next, a second embodiment will be described.

[0092] FIG. 13 is a flowchart showing the configuration of a spectroscopic measurement result display method according to the second embodiment.

[0093] The second embodiment will be described below, focusing on the differences from the first embodiment and omitting the description of the similarities. In each drawing, the same reference numerals are used for the same configurations as those in Figs. 1 to 7.

[0094] The second embodiment is similar to the first embodiment, except that a Lab histogram is generated and displayed as the Lab visualization information.

[0095] 3.1. Preview image acquisition step In the preview image acquisition step S102, the computer is caused to perform a preview image acquisition process and a preview image display process.

[0096] 14 is an example of a display screen 752 including a preview image 703 displayed in preview image acquisition step S102 and a Lab histogram 754 displayed in Lab histogram display step S210 in the second embodiment. In this embodiment, two landscape photographs (color photographs) with slightly different colors are shown as objects W.

[0097] The display screen 752 shown in FIG. 14 has a preview image 703, a Lab histogram 754, a preview image acquisition button 707, a spectral image acquisition button 708, a first region normalization processing button 711a, a second region normalization processing button 711b, a normalization parameter button 712, and an environmental setting value button 713.

[0098] 3.2. Environment setting value reception step In the environment setting value receiving step S104, the computer performs an environment setting value receiving process.

[0099] 3.3.Spectral image acquisition step In the spectroscopic image acquisition step S106, the computer is caused to perform a spectroscopic image acquisition process.

[0100] 3.4.Lab histogram generation steps In the Lab histogram generating step S208, the computer is caused to perform a Lab histogram generating process (Lab information generating process).

[0101] When the spectroscopic image acquisition button 708 shown in FIG. 14 is pressed, a spectroscopic image acquisition process and a Lab histogram generation process are executed, and a Lab histogram 754 is generated. The Lab histogram generation process is a process in which the Lab information calculation unit 208 shown in FIG. 2 generates the Lab histogram 754. In this embodiment, the Lab values ​​are graphed to generate the Lab histogram 754 (Lab visualization information). The Lab histogram 754 is an L histogram obtained by graphing the frequency of the L value for each class. Note that, instead of the L histogram, an a histogram obtained by graphing the frequency of the a value for each class, or a b histogram obtained by graphing the frequency of the b value for each class may be used. Note that, in the following description, at least one of the L histogram, a histogram, and b histogram is also referred to as a "Lab histogram". By generating such a Lab histogram 754 and displaying it in a Lab histogram display step S210 described later, it is possible to display the color information of the object W in a manner that allows a more intuitive understanding. Note that the Lab histogram generation process uses the environmental setting values ​​stored in the storage unit 56.

[0102] In addition, the Lab histogram 754 displays one of the L histogram, a histogram, and b histogram. Two or more may be displayed at the same time. The histogram to be displayed can be switched using the Lab switching button 709 shown in FIG.

[0103] In addition, in the above-mentioned preview image acquisition process, when the preview image acquisition button 707 shown in FIG. 14 is pressed, two search windows SW1 and SW2 shown in FIG. 14 may be displayed together with the preview image 703. By specifying a two-dimensional area in the preview image 703 using the search windows SW1 and SW2, the range of each class of the Lab histogram 754 can be set in generating the Lab histogram 754. Specifically, each minimum value and each maximum value of the Lab values ​​in this two-dimensional area can be assigned to each minimum value and each maximum value of the classes of the Lab histogram 754. The positions, sizes, and shapes of the search windows SW1 and SW2 can be specified by the input unit 52. This allows the Lab histogram 754 to be generated within a desired class range. Instead of the search windows SW1 and SW2, each range of Lab values ​​may be acquired from the entire preview image 703.

[0104] 3.5.Lab histogram display steps In the Lab histogram display step S210, the computer is caused to perform Lab histogram display processing (Lab information display processing).

[0105] The Lab histogram display process is a process in which the display control unit 212 shown in FIG. 2 displays the Lab histogram 754 on the display unit 54. The preview image 703 shows the object images IW1 and IW2. The Lab histogram 754 also includes the graph data D1 and D2 corresponding to the object images IW1 and IW2. By displaying such a Lab histogram 754, the difference in color information of the object W can be detected more accurately, and the difference in the detected color information can be displayed so as to be more intuitively understood. In addition, by simultaneously displaying the graph data D1 and D2 in this way, for example, the graph data D1 serving as a color sample and the graph data D2 serving as a measurement target can be compared. This enables accurate color inspection of the object image IW2.

[0106] 3.6. Normalization Step In normalization step S112, a computer performs normalization processing. This step can be performed as necessary when the Lab histogram 754 generated by the Lab histogram generation process is not appropriate.

[0107] 14 is pressed, the normalization parameters can be specified in the same manner as in the first embodiment, for example. Note that the normalization parameters can be set individually for the search windows SW1 and SW2.

[0108] Next, either the first area normalization process button 711a or the second area normalization process button 711b shown in FIG. 14 is pressed. When the first area normalization process button 711a is pressed, a normalization process is performed to normalize the range of each class of the Lab histogram 754 based on the normalization parameters set for the search window SW1. When the second area normalization process button 711b is pressed, a normalization process is performed to normalize the range of each class of the Lab histogram 754 based on the normalization parameters set for the search window SW2. This causes the range of each class of the Lab histogram 754 to be updated based on the normalization parameters. Then, the updated Lab histogram 754 is displayed in FIG. 14. By updating the Lab histogram 754, the frequency resolution can be further improved, and the graph data D1 and D2 can be compared with each other with higher accuracy.

[0109] The method of inputting the normalization parameters is not limited to the above. For example, the two-dimensional region may be respecified by changing the search windows SW1 and SW2, or a specified value may be input by text. This enables the normalization process to be performed as intended, and a Lab histogram 754 with sufficiently improved frequency resolution can be obtained.

[0110] FIG. 15 is a conceptual diagram showing an example of the differences between the L histogram HL, the a histogram Ha, and the b histogram Hb.

[0111] The object images IW1 and IW2 shown in Fig. 15 are substantially the same photograph, except for slight differences in color. These spectroscopic images are acquired, and Lab values ​​are extracted to generate an L histogram HL, an a histogram Ha, and a b histogram Hb. In each histogram, graph data D1 generated from the object image IW1 and graph data D2 generated from the object image IW2 are displayed superimposed on each other.

[0112] When comparing the three histograms, the difference between the graph data D1 and D2 is relatively small in the L histogram HL and the a histogram Ha. In contrast, the difference between the graph data D1 and D2 is large in the b histogram Hb. In this way, by displaying two or more histograms and comparing the graph data, the color information of the object images IW1 and IW2 can be compared more accurately. In particular, the a and b values ​​that represent chromaticity can have both negative and positive values. For this reason, even if the average values ​​of the a and b values ​​are calculated and used for comparison, the negative and positive values ​​may cancel each other out, resulting in an inappropriate comparison. In contrast, by comparing using histograms, the above-mentioned cancellation does not occur, and an appropriate comparison can be made.

[0113] Although the spectroscopic measurement result display method according to the second embodiment has been described above, some of the above steps may be omitted, or may be replaced with steps having equivalent configurations. Also, the order of the steps may be changed.

[0114] 4. Modification of the Second Embodiment Next, a modification of the second embodiment will be described.

[0115] FIG. 16 is a flowchart showing the configuration of a spectroscopic measurement result display method according to a modified example of the second embodiment.

[0116] A modified example of the second embodiment will be described below, but in the following description, the differences from the first and second embodiments will be mainly described, and a description of similar matters will be omitted. In each drawing, the same reference numerals are used for the same configurations as in Figs. 1 to 15.

[0117] The modified example of the second embodiment is similar to the second embodiment except that a pass / fail determination of the color information of the object W is performed based on the generated Lab histogram.

[0118] The spectroscopic measurement result display method shown in FIG. 16 includes a preview image acquisition step S102, an environment setting value reception step S104, a spectroscopic image acquisition step S106, a Lab histogram generation step S208, a Lab histogram display step S210, a normalization processing step S112, a quantitative evaluation step S214, a pass / fail determination step S116, and a determination result display step S118.

[0119] 4.1. Preview image acquisition step In the preview image acquisition step S102, the computer is caused to perform a preview image acquisition process and a preview image display process.

[0120] FIG. 17 shows an example of a display screen 752 including a preview image 703 and a setting field 730 displayed in the preview image acquisition step S102 in the modified example of the second embodiment.

[0121] A display screen 752 shown in FIG. 17 has a preview image 703 , a preview image acquisition button 707 , a spectral image acquisition button 708 , a normalization process button 711 , a setting field 730 , a pass / fail determination result 731 , a teach button 734 , and a pass / fail determination button 733 .

[0122] 4.2. Environment setting value reception step In the environment setting value receiving step S104, the computer performs an environment setting value receiving process.

[0123] 17 accepts input of setting values ​​for each setting item. Examples of setting items include environmental setting values ​​such as color matching functions and illumination light sources, and normalization parameters such as the minimum L value, the maximum L value, the minimum a value, the maximum a value, the minimum b value, and the maximum b value. These environmental setting values ​​and normalization parameters are stored in the storage unit 56.

[0124] 4.3.Spectral image acquisition step In the spectroscopic image acquisition step S106, the computer is caused to perform a spectroscopic image acquisition process.

[0125] 4.4.Lab histogram generation steps In the Lab histogram generating step S208, the computer is caused to perform a Lab histogram generating process (Lab information generating process).

[0126] The generation process of the Lab histogram 754 generates a Lab histogram (Lab visualization information) based on the environment setting values ​​and normalization parameters stored in the storage unit 56. Note that, for the normalization parameters, each range of Lab values ​​in a two-dimensional region specified in the search window SW shown in FIG. 17 may be used, or a designated value of the Lab value input in the setting field 730 shown in FIG. 17 may be used. Note that, when the Lab histogram 754 has a distribution close to a normal distribution, a value equivalent to ±3σ of the normal distribution may be adopted as the designated value of the Lab value. σ is the standard deviation of the normal distribution.

[0127] 4.5.Lab histogram display steps In the Lab histogram display step S210, the computer is caused to perform Lab histogram display processing (Lab information display processing).

[0128] FIG. 18 is an example of a display screen 762 including an L histogram 765 displayed in the Lab histogram display step S210 in the modified example of the second embodiment.

[0129] The L histogram 765 shown in FIG. 18 is an example of a Lab histogram. When the spectral image acquisition button 708 shown in FIG. 17 is pressed, a spectral image acquisition process and a Lab histogram generation process are executed. After that, when a histogram display button (not shown) is pressed, a display screen 762 shown in FIG. 18 is displayed. The display screen 762 shown in FIG. 18 has a Lab switching field 766, a reference data selection field 768, and an update button 769. The Lab switching field 766 is a pull-down menu, and any one of an L histogram, an a histogram, or a b histogram can be selected. The reference data selection field 768 allows the type of reference data to be selected. After the type of histogram and the type of reference data are selected, the update button 769 is pressed, and the graph data D1 and D2 displayed in the L histogram 765 are updated and displayed. This allows, for example, the graph data D1 based on the reference data and the graph data D2 based on the measurement data for the object W to be compared by overlapping them. As a result, accurate color inspection of the object image IW becomes possible.

[0130] 4.6. Normalization Step In normalization step S112, a computer performs normalization processing. This step can be performed as necessary when the Lab histogram 754 generated by the Lab histogram generation process is not appropriate.

[0131] 4.7. Quantitative evaluation step In the quantitative evaluation step S214, the computer performs the quantitative evaluation.

[0132] When the teach button 734 shown in FIG. 17 is pressed, a teaching screen (not shown) is displayed. On the teaching screen, reference data to be used for quantitative evaluation can be registered. The reference data is data that is the basis for pass / fail judgment, and is used to quantitatively evaluate the relationship between the measurement data for the object W and the reference data. On the teaching screen, a list of reference data may be displayed and selected. In this case, the list may display the pseudocolor of each data, a thumbnail image, an average Lab value, a threshold value for pass / fail judgment, etc. On the teaching screen, the reference data to be used for quantitative evaluation of the measurement data is selected.

[0133] Quantitative evaluations include, for example, an evaluation based on the correlation coefficient between reference data and measurement data (first evaluation), an evaluation based on the error rate between reference data and measurement data (second evaluation), and an evaluation based on a comparison of the Mahalanobis distance from multiple pieces of pass data to the measurement data and the Mahalanobis distance from multiple pieces of fail data to the measurement data (third evaluation).

[0134] In the first evaluation, the frequency of each class obtained from the spectral image is used as the measurement data, and the standard frequency set for each class is used as the reference data. Next, the ratio of the measurement data to the reference data is calculated for each class. Then, the correlation coefficient of the distribution of the obtained ratios is calculated, and a quantitative evaluation is performed based on the calculated correlation coefficient. This quantitative evaluation allows for accurate color inspection, which will be described later.

[0135] 19 is a graph showing a scatter diagram in which the reference data and the measured data are plotted, and a regression line obtained by linearly approximating the plot marks. By obtaining the regression line of the plot marks as shown in FIG. 19, the coefficient of determination R 2The coefficient of determination is the square of the correlation coefficient, and the closer it is to 1, the closer the measurement data is to the reference data. Note that while FIG. 19 shows a graph for the L value, graphs for the a value and the b value may also be created. In this case, the maximum, minimum and average values ​​of the correlation coefficient may be calculated from two or more graphs, and a quantitative evaluation may be performed based on the calculation results.

[0136] In the second evaluation, the frequency of each class obtained from the spectral image is used as the measurement data, and the standard frequency set for each class is used as the reference data. Next, the error rate between the reference data and the measurement data is calculated. Then, a quantitative evaluation is performed based on the calculated error rate. This quantitative evaluation allows for accurate color inspection, which will be described later.

[0137] FIG. 20 shows a graph HS of reference data, a graph HM of measured data, and a graph HD of the difference obtained by subtracting graph HM from graph HS. First, the difference values ​​for each L value class in graph HD are squared, the sum is taken, and then the square root is taken. The calculation result is then used as the error rate. The smaller the error rate value, the closer the measured data is to the reference data. Note that while FIG. 20 shows a graph for L values, graphs for a and b values ​​may also be created. In this case, the maximum, minimum, and average error rates may be calculated from two or more graphs, and a quantitative evaluation may be performed based on the calculation results.

[0138] In the third evaluation, the frequency of each class obtained from the spectral image is used as the measurement data, the pass frequency set for each class is used as the pass data, and the fail frequency set for each class is used as the fail data. Therefore, for example, the pass data is used as the measurement data acquired from an object W judged to pass by another method, and for example, the fail data is used as the measurement data acquired from an object W judged to fail by another method. Next, a quantitative evaluation is performed based on a comparison between the Mahalanobis distance from the multiple pass data to the measurement data and the Mahalanobis distance from the multiple fail data to the measurement data. Such a quantitative evaluation allows for accurate color inspection, which will be described later.

[0139] FIG. 21 is a conceptual diagram showing the distance between range A occupied by a plurality of pass data, range B occupied by a plurality of fail data, and measurement data M. In FIG. 21, the average value μ A , standard deviation σ A , and the Mahalanobis distance D between the measurement data and the accepted data A The Mahalanobis distance D A For example, the measurement data M and the average value μ A The difference between these is the standard deviation σ A In addition, in FIG. 21, the average value μ B , standard deviation σ B , and the Mahalanobis distance D between the measurement data and the rejection data B The Mahalanobis distance D B For example, the measurement data M and the average value μ B The difference between these is the standard deviation σ B The Mahalanobis distance D A and the Mahalanobis distance D B D A <D B When the above condition is satisfied, the measurement data M can be considered to be close to the acceptable data range A, and D B <D A When the above condition is satisfied, the measurement data M can be considered to be close to the range B of unacceptable data.

[0140] 4.8. Pass / Fail Judgment Step In pass / fail determination step S116, the computer performs pass / fail determination.

[0141] When the pass / fail judgment button 733 shown in Fig. 17 is pressed, a pass / fail judgment is performed based on the relationship between the quantitative evaluation result and the threshold value. If the quantitative evaluation result meets the threshold value, it is judged as pass. If the quantitative evaluation result does not meet the threshold value, it is judged as fail. In this way, color inspection based on the threshold value can be performed.

[0142] 4.9. Displaying the Judgment Result In the determination result display step S118, the computer is caused to perform a determination result display process.

[0143] When the pass / fail judgment is made in pass / fail judgment step S116, characters or the like indicating the judgment result are displayed in pass / fail judgment result 731 shown in Fig. 17. By making the pass / fail judgment based on the Lab histogram in this way, the color information of the object W can be inspected more accurately. In the above modified example as well, the same effects as those of the second embodiment can be obtained.

[0144] 5. Advantages of the above embodiment As described above, the spectroscopic measurement device 1 according to the embodiment includes the spectroscopic measurement unit 3, the display unit 54, and the control unit 2. The spectroscopic measurement unit 3 performs spectroscopic measurement of the object W and acquires a spectroscopic image. The control unit 2 generates Lab visualization information (Lab image 704 or Lab histogram 754) from the spectroscopic image, and causes the display unit 54 to display the Lab visualization information.

[0145] According to such a configuration, a spectroscopic measurement device 1 can be obtained that detects color information of the object W more accurately and displays the detected color information in an intuitive manner.

[0146] In addition, in the spectroscopic measurement device 1 according to the embodiment, the Lab visualization information is an L image obtained by converting the L value to luminance for each pixel, an a image obtained by converting the a value to luminance for each pixel, or a b image obtained by converting the b value to luminance for each pixel. According to such a configuration, a spectroscopic measurement device 1 can be obtained that can generate and display Lab images in which even subtle color unevenness is sufficiently emphasized.

[0147] Furthermore, in the spectroscopic measurement device 1 according to the embodiment, the control unit 2 sets the luminance range of each of the L image, the a image, or the b image based on the range of each of the extracted L value, a value, or b value.

[0148] According to such a configuration, a spectroscopic measurement device 1 capable of generating a Lab image 704 within a desired luminance range is obtained.

[0149] Moreover, in the spectroscopic measurement device 1 according to the embodiment, the control unit 2 has an image processing unit 216. The image processing unit 216 performs binarization processing on the L image, the a image, or the b image, and then performs mass detection processing on the binarized L image, the a image, or the b image.

[0150] According to such a configuration, for example, the area occupied by the color unevenness ST can be specified, thereby obtaining a spectroscopic measurement device 1 capable of quantitatively evaluating the size of the color unevenness ST.

[0151] In addition, in the spectroscopic measurement device 1 according to the embodiment, the Lab visualization information is an L histogram obtained by graphing the frequency of L values ​​for each class, an a histogram obtained by graphing the frequency of a values ​​for each class, or a b histogram obtained by graphing the frequency of b values ​​for each class.

[0152] According to such a configuration, a spectroscopic measurement device 1 can be obtained that can detect differences in color information possessed by the object W more accurately and display the detected differences in color information in a manner that allows for a more intuitive understanding.

[0153] Furthermore, in the spectroscopic measurement device 1 according to the embodiment, the control unit 2 sets the range of each class of the L histogram, the a histogram, or the b histogram based on the range of the extracted L value, a value, or b value.

[0154] With this configuration, a spectroscopic measurement device 1 capable of generating a Lab histogram 754 within a desired class range can be obtained.

[0155] In addition, in the spectroscopic measurement device 1 according to the embodiment, when the frequency for each class obtained from the spectroscopic image is used as the measurement data and the standard frequency set for each class is used as the reference data, the control unit 2 may have an acceptance / rejection judgment unit 218 that calculates the ratio of the measurement data to the reference data for each class and judges the acceptance / rejection of the measurement data based on the correlation coefficient of the distribution of the obtained ratios. With this configuration, the color of the object W can be inspected with high accuracy.

[0156] In addition, in the spectroscopic measurement device 1 according to the embodiment, when the frequency for each class obtained from the spectroscopic image is used as the measurement data and the standard frequency set for each class is used as the reference data, the control unit 2 may have a pass / fail judgment unit 218 that calculates an error rate between the reference data and the measurement data and judges whether the measurement data is pass / fail based on the error rate. With this configuration, the color of the object W can be inspected with high accuracy.

[0157] Furthermore, in the spectroscopic measurement device 1 according to the embodiment, when the frequency for each class obtained from the spectroscopic image is used as the measurement data, the pass frequency set for each class is used as the pass data, and the fail frequency set for each class is used as the fail data, the control unit 2 may have a pass / fail judgment unit 218 that makes a pass / fail judgment on the measurement data based on the Mahalanobis distance from the multiple pass data to the measurement data, and the Mahalanobis distance from the multiple fail data to the measurement data. With this configuration, the color of the object W can be inspected with high accuracy.

[0158] Moreover, the spectroscopic measurement device 1 according to the embodiment includes an input unit 52. The control unit 2 may include a normalization processing unit 210 that acquires the ranges of the L value, the a value, or the b value in the two-dimensional region input by the input unit 52 as the above-mentioned ranges.

[0159] According to this configuration, normalization processing can be performed as desired based on each range of Lab values ​​in a two-dimensional area.

[0160] Moreover, the spectroscopic measurement device 1 according to the embodiment includes an input unit 52. The control unit 2 may include a normalization processing unit 210 that acquires the designated values ​​inputted by the input unit 52 as the above-mentioned respective ranges. According to this configuration, normalization processing can be performed as desired based on the designated value.

[0161] Moreover, in the spectroscopic measurement device 1 according to the embodiment, the control unit 2 has a display control unit 212. The display control unit 212 causes the display unit 54 to display an L image 735 (Lab visualization information) and a setting field 730 (input receiving screen) for receiving input of a designated value side by side.

[0162] With this configuration, it is possible to input a more appropriate designated value (normalization parameter) while observing the change in the L image 735.

[0163] In the spectroscopic measurement device 1 according to the embodiment, the control unit 2 includes an environment setting value receiving unit 206 and a Lab information calculation unit 208. The environment setting value receiving unit 206 receives environment setting values ​​including at least one of a color matching function and an illumination light source. The Lab information calculation unit 208 generates Lab visualization information (Lab image 704 or Lab histogram 754) based on the spectral image and the environment setting values.

[0164] According to this configuration, Lab visualization information that extracts color information of the object W with higher accuracy can be obtained.

[0165] The spectroscopic measurement result display method according to the embodiment is a method for displaying the spectroscopic measurement result of the object W on the display unit 54, and includes a spectroscopic image acquisition step S106, a Lab image generation step S108 or a Lab histogram generation step S208, and a Lab image display step S110 or a Lab histogram display step S210. The spectroscopic image acquisition step S106 acquires a spectroscopic image of the object W. The Lab image generation step S108 and the Lab histogram generation step S208 generate Lab visualization information (Lab image 704 or Lab histogram 754) from the spectroscopic image. The Lab image display step S110 and the Lab histogram display step S210 display the Lab visualization information on the display unit 54.

[0166] According to such a configuration, color information of the object W can be detected more accurately, and the detected color information can be displayed so as to be intuitively understandable.

[0167] Moreover, the spectroscopic measurement result display program according to the embodiment is a program that causes a computer to perform a process of displaying the spectroscopic measurement result of the object W on the display unit 54. This spectroscopic measurement result display program causes the computer to perform a spectroscopic image acquisition process, a Lab information generation process, and a Lab information display process. The spectroscopic image acquisition process acquires a spectroscopic image of the object W. The Lab information generation process generates Lab visualization information (Lab image 704 or Lab histogram 754) from the spectroscopic image. The Lab information display process displays the Lab visualization information on the display unit 54.

[0168] According to such a configuration, a program can be obtained that can detect color information of the object W more accurately and display the detected color information in a manner that allows intuitive understanding.

[0169] Although the spectroscopic measurement device, the spectroscopic measurement result display method, and the spectroscopic measurement result display program according to the present invention have been described based on the illustrated embodiments, the present invention is not limited to this.

[0170] For example, the spectroscopic measurement device according to the present invention may be one in which each part of the above-described embodiment is replaced with any component having a similar function, or any component may be added to the above-described embodiment. Also, the spectroscopic measurement result display method according to the present invention may be one in which any purposed process is added to the above-described embodiment. Furthermore, the spectroscopic measurement result display program according to the present invention may be compressed or encrypted. [Explanation of symbols]

[0171] 1...spectroscopic measurement device, 2...control unit, 3...spectroscopic measurement unit, 41...CPU, 42...memory, 43...hard disk, 44...mouse, 45...keyboard, 46...monitor, 47...external interface, 48...external bus, 52...input unit, 54...display unit, 56...storage unit, 61...stage, 62...light source, 204...measurement control unit, 206...environment setting value reception unit, 208...Lab information calculation unit, 210...normalization processing unit, 212...display control unit, 216...image processing unit, 218...pass / fail judgment unit, 432...program, 434...data, 436...OS, 702...display screen, 703...preview image, 704...Lab image, 705...comparison target image, 707...preview image acquisition button, 708...spectroscopic image acquisition button, 709...La b switching button, 711...normalization processing button, 711a...first region normalization processing button, 711b...second region normalization processing button, 712...normalization parameter button, 713...environment setting value button, 715...input screen, 716...selection field, 717...selection field, 720...input screen, 722...slider, 723...slider, 730...setting field, 731...pass / fail judgment result, 732...image processing button, 733...pass / fail judgment button, 734...teach button, 735...L image, 752...display screen, 754...Lab histogram, 762...display screen, 765...L histogram, 766...Lab switching field, 768...reference data selection field, 769...update button, A...range, B...range, D1...graph data, D2...graph data, D A …Mahalanobis distance, D B...Mahalanobis distance, HD...graph, HL...L histogram, HM...graph, HS...graph, Ha...a histogram, Hb...b histogram, IW...object image, IW1...object image, IW2...object image, Ind...indicator, LW...object image, M...measurement data, R 2 ...coefficient of determination, S102...preview image acquisition step, S104...environment setting value reception step, S106...spectral image acquisition step, S108...Lab image generation step, S110...Lab image display step, S112...normalization processing step, S114...image processing step, S116...pass / fail judgment step, S118...judgment result display step, S208...Lab histogram generation step, S210...Lab histogram display step, S214...quantitative evaluation step, ST...color unevenness, SW...search window, SW1...search window, SW2...search window, W...object, μ A ...average value, μ B …mean value, σ A …Standard deviation, σ B …Standard deviation

Claims

1. a spectroscopic measurement unit that performs spectroscopic measurement of an object and acquires a spectroscopic image; A display unit; a control unit that generates Lab visualization information from the spectroscopic image and displays the Lab visualization information on the display unit; A spectroscopic measurement device comprising:

2. 2. The spectroscopic measurement device according to claim 1, wherein the Lab visualization information is an L image obtained by converting an L value to luminance for each pixel, an a image obtained by converting an a value to luminance for each pixel, or a b image obtained by converting a value to luminance for each pixel.

3. The spectroscopic measurement device according to claim 2 , wherein the control unit sets a luminance range for each of the L image, the a image, and the b image based on the extracted range of the L value, the a value, or the b value.

4. The spectroscopic measurement device according to claim 2 or 3, wherein the control unit has an image processing unit that performs a binarization process on the L image, the a image, or the b image, and then performs a mass detection process on the L image, the a image, or the b image that has been subjected to the binarization process.

5. 2. The spectroscopic measurement device according to claim 1, wherein the Lab visualization information is an L histogram obtained by graphing the frequency of L values ​​for each class, an a histogram obtained by graphing the frequency of a values ​​for each class, or a b histogram obtained by graphing the frequency of b values ​​for each class.

6. The spectroscopic measurement device according to claim 5 , wherein the control unit sets a range of each class of the L histogram, the a histogram, or the b histogram based on the range of each of the extracted L values, a values, or b values.

7. The frequency for each class obtained from the spectroscopic image is defined as measurement data, and a reference frequency set for each class is defined as reference data, 7. The spectroscopic measurement device according to claim 5, wherein the control unit includes a pass / fail determination unit that calculates a ratio of the measurement data to the reference data for each class and determines pass / fail of the measurement data based on a correlation coefficient of a distribution of the obtained ratios.

8. The frequency for each class obtained from the spectroscopic image is defined as measurement data, and a reference frequency set for each class is defined as reference data, 7. The spectroscopic measurement device according to claim 5, wherein the control unit includes a pass / fail determination unit that calculates an error rate between the reference data and the measurement data, and determines pass / fail of the measurement data based on the error rate.

9. The frequency for each of the classes obtained from the spectroscopic image is defined as measurement data, the pass frequency set for each of the classes is defined as pass data, and the fail frequency set for each of the classes is defined as fail data, The spectroscopic measurement device according to claim 5 or 6, wherein the control unit has a pass / fail judgment unit that judges whether the measurement data passes or fails based on the Mahalanobis distance from the plurality of pass data to the measurement data, and the Mahalanobis distance from the plurality of fail data to the measurement data.

10. An input unit is provided, The spectroscopic measurement device according to claim 3 , wherein the control unit has a normalization processing unit that acquires, as the ranges, ranges of the L value, the a value, or the b value in the two-dimensional region inputted by the input unit.

11. An input unit is provided, The spectrometer according to claim 3 , wherein the control unit includes a normalization processing unit that acquires designated values ​​inputted through the input unit as the ranges.

12. The spectroscopic measurement device according to claim 11 , wherein the control unit includes a display control unit that causes the display unit to display the Lab visualization information and an input acceptance screen that accepts input of the designated value side by side.

13. The control unit is an environmental setting value receiving unit that receives environmental setting values ​​including at least one of a color matching function and an illumination light source; a Lab information calculation unit that generates the Lab visualization information based on the spectral image and the environmental setting value; The spectroscopic measurement device according to claim 1 ,

14. A method for displaying a spectroscopic measurement result of an object on a display unit, comprising: acquiring a spectral image of the object; generating Lab visualization information from the spectroscopic image; displaying the Lab visualization information on the display unit; A method for displaying a result of spectroscopic measurement, comprising:

15. A spectroscopic measurement result display program that causes a computer to perform a process of displaying a spectroscopic measurement result of an object on a display unit, On the computer, A spectroscopic image acquisition process for acquiring a spectroscopic image of the object; A Lab information generation process for generating Lab visualized information from the spectroscopic image; a Lab information display process for displaying the Lab visualization information on the display unit; A spectroscopic measurement result display program for causing a computer to execute the above steps.

Images