Spectroscopic instruments and computer programs

Abstract

To provide a spectroscopic measurement unit and a computer program.SOLUTION: A spectroscopic camera 100 has a spectroscopic element 60 and a light receiver 70. The method for correcting the spectroscopic camera 100 includes: causing a first-wavelength-number light 31 to enter a spectroscopic element 60 from a spectroscopic light source 30; receiving a second-wavelength-number light 32 emitted from the spectroscopic element 60, by a light receiver 70; generating a matrix that represents spectroscopic characteristics on the basis of the output from the light receiver 70; and generating a correction matrix corrected on the basis of an inverse matrix of the matrix and storing the correction matrix into a storage unit 24.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to a spectroscopic measuring instrument and a computer program. [Background technology]

[0002] For example, Patent Document 1 discloses a method in which a color (color chart) printed on a medium is measured using a reference spectrophotometer and a spectrophotometer, a standard correction value (estimated matrix) is calculated in advance, and the correction value is applied to the spectrophotometer to obtain a reflectance spectrum close to that of the reference spectrophotometer.

[0003] Furthermore, for example, Patent Document 2 discloses a method of obtaining a reflection spectrum by adding a coefficient to a transmission profile. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2014-38081 [Patent Document 2] US10605660 publication Summary of the Invention [Problem to be solved by the invention]

[0005] However, the method described in Patent Document 1 has the problem that accurate correction cannot be performed if the media used to calculate the correction value is different from the media used for measurement. In addition, there is also the problem that different correction values ​​must be calculated if the elements constituting the spectrophotometer, such as the illumination light source and the spectroscopic element, are different. Furthermore, there is also the problem that an accurate reflectance spectrum cannot be obtained if the illumination light source used cannot be specified, as in the case of a spectroscopic camera. Furthermore, the method described in Patent Document 2 does not include any description of the sensitivity spectrum of the light receiver and the illumination spectrum, and there is a problem in that it is unclear what characteristics are included in the transmission profile. In other words, there is a need for a versatile correction method that does not require preparation of correction values ​​in advance and that can accurately measure optical spectra without requiring any configuration other than the spectrometer. [Means for solving the problem]

[0006] The spectrophotometer includes a variable wavelength spectral filter and an optical sensor, and a correction method for the spectrophotometer includes: causing light of a first wavelength number from a spectral light source to enter the variable wavelength spectral filter; receiving light of a second wavelength number that has exited the variable wavelength spectral filter with the optical sensor; generating a matrix representing spectral characteristics based on an output from the optical sensor; generating a correction matrix based on an inverse matrix of the matrix; and storing the correction matrix in a storage device.

[0007] The computer program is a computer program for correcting a spectroscopic measuring instrument having a variable wavelength spectral filter and an optical sensor, and includes causing light of a first wavelength number from a spectral light source to be incident on the variable wavelength spectral filter, receiving light of a second wavelength number that has exited the variable wavelength spectral filter with the optical sensor, generating a matrix representing spectral characteristics based on an output from the optical sensor, generating a corrected correction matrix based on an inverse matrix of the matrix, and storing the correction matrix in a storage device. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 10 is a diagram showing an equation for calculating a correction value. [Figure 2] 4 is a graph showing the spectral characteristics of a spectroscopic element. [Figure 3] 10 is a graph showing the difference between the measurement values ​​of a spectroscopic camera and the true spectral characteristics. [Figure 4] FIG. 1 is a schematic diagram showing the configuration of a spectroscopic camera according to a first embodiment. [Figure 5] FIG. 10 is a diagram showing an equation for obtaining a true output in which the characteristics of the spectroscopic element are corrected. [Figure 6] 10 is a graph showing the spectral characteristics of a spectroscopic camera. [Figure 7]10 is a graph showing the spectral characteristics of a bandpass filter. [Figure 8] 10 is a graph showing the sensitivity characteristics of a photoreceiver. [Figure 9] 10 is a graph showing the inverse matrix of the spectral characteristic M. [Figure 10] 10 is a graph showing a corrected reflectance spectrum. [Figure 11] 5A and 5B are diagrams for explaining correction within a measurement area of ​​a spectroscopic camera. [Figure 12] 10 is a diagram showing an equation for adding a parameter to a correction value. [Figure 13] Graph showing the reflectance spectrum before adding parameters. [Figure 14] Graph showing the reflectance spectrum after adding parameters. [Figure 15] FIG. 2 is a diagram showing the basic form of a spectral characteristic M. [Figure 16] FIG. 10 is a diagram for explaining the contents of the spectral characteristic M. [Figure 17] FIG. 10 is a diagram showing the formula for calculating the correction value M†. [Figure 18] FIG. 10 is a diagram showing the formula for calculating the correction value M†. [Figure 19] FIG. 10 is a diagram for explaining how to obtain a parameter β. [Figure 20] FIG. 10 is a diagram for explaining the contents of a correction formula. [Figure 21] FIG. 10 is a cross-sectional view showing the configuration of a spectroscopic camera according to a modified example. [Figure 22] FIG. 10 is a diagram showing an equation for calculating a photoreceiver output whose spectral characteristics have been corrected. DETAILED DESCRIPTION OF THE INVENTION

[0009] First, with reference to FIG. 1, a method for determining the correction value of a spectrometer will be described.

[0010] As shown in Figure 1, the spectral output of a spectrometer is the product of the true spectral characteristics of the object being measured and the characteristics of the spectroscopic element acting as a variable wavelength spectral filter. Specifically, if the spectral output of the spectrometer (matrix: (m × 1)) is P, the characteristics of the spectroscopic element are M, and the true spectral characteristics of the object being measured (matrix: (m × 1)) are R, then the spectral output P can be calculated using the following formula (1) (see Figure 1). In other words, the spectral output P can be obtained by generating a matrix (m × m) that represents the characteristic M of the spectroscopic element.

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[0012] Therefore, by multiplying the spectral output P of the spectrometer by a correction matrix generated by inverse matrix using the characteristics of the spectroscopic element, the true spectral characteristics R of the object can be obtained. The inverse matrix of the characteristics of this spectroscopic element becomes the correction value.

[0013] Specifically, the inverse matrix of the characteristics of the spectroscopic element is M -1 Then, the true spectral characteristic R of the object can be calculated by the following equation (2) (see Figure 1).

[0014]

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[0015] The equations (1) and (2) can be calculated using the following equations (3) to (6) (see FIG. 1). -1 is the correction value.

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[0020] M in equation (3) is a square matrix, i.e., the rows and columns are the same. M is also regular, i.e., an inverse matrix exists. E in equation (5) is a unit matrix, i.e., "1".

[0021] Next, the spectral characteristics of the spectroscopic element and the difference between the true spectral characteristics and the measured values ​​of a spectroscopic measuring instrument equipped with the spectroscopic element will be described with reference to FIGS.

[0022] The object to be measured is a BCRA12 color tile used as a standard for colorimetry.The spectroscopic element is a wavelength-tunable Fabry-Perot etalon with a half-width (resolution) of up to 45 nm.

[0023] The graph shown in FIG. 2 shows an example of the spectral characteristics of a spectral element, with the horizontal axis representing wavelength (nm) and the vertical axis representing transmittance.

[0024] The graph shown in Figure 3 compares the reflectance spectrum of a reference spectrometer, shown by the solid line, with the reflectance spectrum measured using a spectroscopic element, shown by the dashed line. The reference reflectance spectrum was measured using a commercially available high-precision spectrophotometer (Shimadzu UV-3150), and is considered to be the true reflectance spectrum. The graph shown in Figure 3 represents wavelength (nm) on the horizontal axis and reflectance on the vertical axis. Note that the reflectance spectrum measured using the spectroscopic element, shown by the dashed line, uses an LED light source.

[0025] As shown in FIG. 3, it can be seen that there is a large discrepancy between the reflection spectrum measured using the spectroscopic element shown by the dashed line and the true reflection spectrum shown by the solid line.

[0026] Next, the configuration of a spectroscopic camera 100 as a spectroscopic measuring instrument of this embodiment will be described with reference to FIG.

[0027] As shown in FIG. 4, the spectroscopic camera 100 includes a measurement unit 10 and a control unit 20.

[0028] The measurement unit 10 includes an incident optical system 40 into which light from the spectroscopic light source 30 is incident, a bandpass filter (BPF) 50, a spectroscopic element 60 that disperses the incident light, and a photodetector 70 as an optical sensor that captures the light dispersed by the spectroscopic element 60.

[0029] The incident optical system 40 includes, for example, an autofocus mechanism. The incident optical system 40 is also configured, for example, by a telecentric optical system, and guides the light 31 of the first wavelength number to the spectroscopic element 60 so that the optical axis and the chief ray are parallel or approximately parallel to each other.

[0030] The spectroscopic element 60 is, for example, a wavelength-selective filter, and a Fabry-Perot filter capable of changing the transmission wavelength band is used. The spectroscopic element 60 is a wavelength-tunable interference filter including a pair of substrates 61, 62, a pair of reflective films 63, 64 facing each other, and a gap changer 65 capable of changing the gap dimension between these reflective films 63, 64. The gap changer 65 is, for example, configured by an electrostatic actuator. The wavelength-tunable interference filter is also called an etalon. The spectroscopic element 60 is disposed on the optical path of light incident on the photodetector 70.

[0031] The spectroscopic element 60 changes the gap dimension of the reflective films 63 and 64 by changing the voltage applied to the gap change unit 65 under the control of the control unit 20, and changes the output wavelength λi (i=1, 2,..., N), which is the wavelength of the light that passes through the reflective films 63 and 64.

[0032] The light receiver 70 is, for example, a CCD (Charge Coupled Device), and is an imaging device that photoelectrically converts the light 32 of the second wavelength number that has passed through the spectroscopic element 60 to obtain an electrical signal that represents the object to be measured.

[0033] The spectroscopic camera 100 sequentially receives instructions for a plurality of measurement bands (multi-bands) from the control unit 20 at the spectroscopic element 60, thereby sequentially changing the transmission wavelength range of the spectroscopic element 60. In this way, the spectroscopic camera 100 captures an image of the measurement object with sensitivity in a plurality of wavelength bands.

[0034] The control unit 20 includes a processing unit 21 that generates a matrix representing the spectral characteristics based on the output from the photoreceiver 70 and generates a correction matrix by inverting the matrix, and a storage unit 24 that serves as a storage device for storing the correction matrix. Specifically, the processing unit 21 includes a matrix generation unit 22 that generates the matrix and a correction matrix generation unit 23 that generates the correction matrix. The control unit 20 is configured with one or more processors and, for example, operates in accordance with a control program stored in the storage unit 24 to perform overall control of the operation of the spectroscopic camera 100.

[0035] Furthermore, the processing unit 21 performs various processes by executing a control program as a computer program. The storage unit 24 is configured with memories such as RAM (Random Access Memory) and ROM (Read Only Memory). The RAM is used for temporary storage of various data, and the ROM stores control programs and control data for controlling the operation of the spectroscopic camera 100. The processing unit 21 performs each process using the data and parameters stored in the corresponding storage unit 24.

[0036] Next, a method for determining the spectral characteristics of the spectroscopic camera 100 of this embodiment will be described with reference to FIGS.

[0037] The spectral characteristics of the spectroscopic element 60 are measured by introducing light from a spectroscopic light source 30 (Asahi Spectroscopy Corporation's constant energy spectroscopic light source PVL-3310) into the spectroscopic camera 100 and using a photoreceiver 70 such as an area sensor. That is, the spectral characteristics are measured in the form of the spectroscopic camera 100. As described above, the spectroscopic camera 100 measures the spectral characteristics of the bandpass filter 50 and the photoreceiver 70. Specifically, this can be calculated using the following equation (7) (see FIG. 5).

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[0039] By using equation (7), the spectral characteristic M measured by the spectroscopic camera 100 can be obtained. M is the product of each characteristic (m × m matrix). ET is the spectral characteristic of the spectroscopic element 60. B is the spectral characteristic of the bandpass filter 50. PD is the sensitivity of the photodetector 70. eλ as the second wavelength number is the driving wavelength (measurement pitch) of the spectroscopic element 60. λ is the data wavelength (data pitch) of each characteristic. That is, there are two methods for generating the spectral characteristic: a direct measurement method as described above, and a calculation method by multiplying the data of each characteristic by .

[0040] Fig. 6 is a graph showing the spectral characteristic M obtained by actual measurement using the spectroscopic camera 100. Specifically, the spectral characteristic M shown in Fig. 6 is a graph obtained by multiplying the spectral characteristic of the spectroscopic element 60 shown in Fig. 2, the spectral characteristic of the bandpass filter 50 shown in Fig. 7, and the sensitivity characteristic of the photodetector 70 shown in Fig. 8.

[0041] 6 to 8, the control wavelengths range from 400 nm to 700 nm in 20 nm increments, and for example, a control wavelength of 400 nm has spectral characteristics of 400 nm to 700 nm. These are called data wavelengths. In terms of a matrix, the rows are the data wavelengths and the columns are the control wavelengths of the light separating element 60.

[0042] The spectroscopic camera 100 of this embodiment calculates the inverse matrix M of the matrix representing the actually measured spectral characteristics shown in FIG. 6 as shown in the following equation (8). -1 The correction matrix generated by the above equation is multiplied by the output P of the spectroscopic camera 100. This makes it possible to obtain the original true intensity spectrum Rt.

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[0044] Specifically, Rt in equation (8) is the true output after correcting the characteristics of the spectroscopic element 60, that is, the intensity spectrum. In other words, it is the spectrum of the light that actually enters the spectroscopic camera 100. M -1 is the inverse matrix of the characteristics measured by the light receiver 70 obtained by equation (7). P is the output of the spectroscopic camera 100 including the light source characteristics and the like.

[0045] Figure 9 shows the inverse matrix M -1 Specifically, the inverse matrix M when the measurement pitch is 20 nm (m=16) is -1 , that is, the correction value in this spectroscopic camera 100. By making such correction, it is possible to cancel the characteristics of the spectroscopic element.

[0046] The following equation (9) is used to calculate the reflectance spectrum (see Figure 5). This is an intensity spectrum, so for example, white is measured before red is measured. In this case, correction is performed in the same way as above.

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[0048] For example, to calculate reflectance, the correct red reflectance spectrum is calculated by dividing the corrected red intensity spectrum by the reference white intensity spectrum and multiplying it by the existing reference white calibration data. This allows for an accurate spectrum to be obtained. Furthermore, by multiplying it by a luminance calibration coefficient, the light source spectrum can also be measured accurately.

[0049] FIG. 10 shows the output P of the photodetector 70 when the 12 colors of the BCRA tiles are measured by the spectroscopic camera 100, with the correction value M -1 10 is a graph showing the results of calculating the reflectance R by multiplying by . That is, it shows the reflectance spectrum after correction.

[0050] Specifically, similar to Fig. 3, this graph compares the true reflectance spectrum of a reference spectrometer, shown by the solid line, with the reflectance spectrum measured using spectroscopic camera 100, shown by the dashed line. Note that the graph shown in Fig. 10 represents wavelength (nm) on the horizontal axis and reflectance on the vertical axis. Note that the reflectance spectrum measured using spectroscopic element 60, shown by the dashed line, uses an LED light source, similar to Fig. 3.

[0051] As shown in FIG. 10, by using the correction method of the spectroscopic camera 100 of this embodiment, the true reference reflectance spectrum (solid line) and the corrected reflectance spectrum (dashed line) can be made to be approximately the same reflectance spectrum.

[0052] The above correction method has been shown to enable nearly accurate measurement of the reflectance spectrum, but it can also enable nearly accurate measurement of the spectrum of light sources such as LEDs. When measuring a light source, the true output Rt obtained by correcting the spectral characteristics in Figure 5 is the true output, and with calibration, an accurate luminance spectrum can be obtained.

[0053] 11, in a spectroscopic camera 100 that uses an etalon as the spectroscopic element 60, the spectroscopic characteristics vary depending on the angle of the light rays 33 and 34 incident on the spectroscopic element 60, the in-plane gap unevenness of the spectroscopic element 60 itself, and the location of the photoreceiver 70. Therefore, if the spectroscopic characteristics are measured for each pixel using a photoreceiver 70 such as an area sensor, a correction value is created for each pixel, and correction is performed for each pixel, accurate measurements can be made for all pixels in the photoreceiver 70. Furthermore, measurement differences within an area can be reduced.

[0054] Next, a correction method for suppressing overfitting by adding a parameter (regularization) to the correction value will be described with reference to FIGS.

[0055] In the spectroscopic camera 100, when the measurement pitch becomes small, overfitting (for example, an inability to perform a correct evaluation due to an increase in noise) may occur. In this case, accurate spectral characteristics can be obtained by adding a parameter (regularization) to the correction value, as shown in Figures 12 to 14.

[0056] The following equations (10) to (13) show a correction method that adds a parameter to suppress overfitting of the spectroscopic camera 100 (see FIG. 12). Figures 13 and 14 are graphs showing the reflectance spectra before and after adding the parameter β to the correction value. The measurement pitch is 5 nm.

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[0061] Equation (11) is an equation obtained by adding a parameter β to the product M of each characteristic. Note that I is a unit matrix (E). Equation (12) is an equation obtained by correcting the characteristic of the light separating element 60 to obtain the true output Rt.

[0062] In this way, the correction value M' ―1 By including the parameter β in the above equation, the overfitting portion F shown in Fig. 13 is suppressed, and a more accurate reflectance spectrum can be obtained over the entire measurement wavelength range, as shown in Fig. 14. Fig. 13 is a graph showing the reflectance spectrum when the parameter β is 0. Fig. 14 is a graph showing the reflectance spectrum when the parameter β is 1.

[0063] Next, the basic form of correction will be described with reference to FIGS.

[0064] As shown in Fig. 15, M is the spectral characteristic obtained by measurement using a spectroscopic camera 100 in the form of a camera equipped with an etalon, i.e., a spectroscopic element 60. The corrected photodetector output Rt can be calculated using equation (14) (see Fig. 15). M † is M -1 is a correction value different from P. P is the receiver output.

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[0066] The corrected reflectance R can be calculated using equation (15) (see FIG. 15). White-data is the reference reflectance calibration value.

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[0068] FIG. 16 shows the content of the spectral characteristic M. In the following equation (16), M is the spectral characteristic of the spectroscopic camera 100 in the form of a camera (see FIG. 16). ET is the spectral characteristic of the etalon, i.e., the spectroscopic element 60. B is the spectral characteristic of the bandpass filter (BPF) 50. PD is the sensitivity of the photodetector 70. eλ is the drive wavelength (measurement pitch). λ is the data wavelength (data pitch). n is the number of data points in eλ and λ.

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[0070] The spectral characteristic M is basically a square matrix with the same number of rows and columns, i.e., the number of data points for eλ and λ is the same.

[0071] Next, with reference to FIGS. 17 to 20, the correction value M when the spectral characteristic M is a square matrix and when it is not a square matrix will be calculated. † The formula for calculating this will be explained below.

[0072] When the spectral characteristic M is a square matrix, the correction value M is expressed as shown in the following equations (17) to (19). † = Inverse matrix M of M -1 If the spectral characteristic M is not a square matrix, the correction value M can be calculated as a pseudo-inverse matrix as shown in equation (20). † can be obtained.

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[0077] Specifically, as shown in the following equations (21) to (23), three correction values ​​M † There are three ways to calculate the correction value M † is a part that includes the regularization parameter β and the unit matrix I, which is different from the above equations (19) and (20).

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[0081] Equation (21) is the correction value M when the spectral characteristic M is a square matrix. † Specifically, when the parameter β is large, the correction value M † approaches the unit matrix I=1 and is the same as the case without correction. On the other hand, when the parameter β is 0, the correction value M † is the simple inverse matrix M of the spectral characteristic M -1 In other words, the parameter β is a parameter that limits the amount of correction. In a broad sense, it can be said to be a regularization parameter. Since overfitting is a phenomenon caused by overcorrection, overfitting can be suppressed by adjusting the parameter β.

[0082] Equation (22) is the correction value M when the spectral characteristic M is not a square matrix. † Specifically, it is a commonly known pseudo-inverse matrix with a regularization term βI. Even if the spectral characteristic M is not a square matrix, the inverse matrix M of M †For example, if the measurement pitch is 20 nm, the number of data points for eλ is n=16, the data pitch is 5 nm, and the number of data points for λ is m=61, then the inverse matrix M can be calculated, and the correction value M † However, even if the measurement pitch is 20 nm (n=16), the output pitch after correction will be 5 nm (m=61).

[0083] Equation (23) is a simplification of equation (22) when the spectral characteristic M is a square matrix in the pseudo-inverse matrix with a regularization term of equation (22). Specifically, β(M T ) -1 The term is the regularization term. The correction value M for the parameter β † The behavior of is different from that of equation (21). When the parameter β is 0, the correction value M † is the simple inverse matrix M of M -1 This becomes:

[0084] FIG. 19 is a diagram illustrating how to determine the parameter β. First, a sample is measured and corrected using the spectroscopic camera 100. Next, the value of the parameter β is changed to check the error between the sample and the reference value. Specifically, as shown in the graph in FIG. 19, the parameter β that minimizes the error is selected. An example of a sample is 12 colors of BCRA tiles. Calibration data for the BCRA tiles and measurement data from a high-precision spectrometer are used as the reference value. Equation (24) is an example of an equation for calculating the error in the reflectance spectrum (see FIG. 19).

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[0086] The following equation (25) shows the content of the correction equation (see Figure 20). For example, if the photodetector output in 20 nm increments from 400 nm to 700 nm is multiplied by the matrix, the matrix from 400 nm to 700 nm can be obtained. This becomes the spectrum. Furthermore, the light source spectrum S can be measured using equation (26). k is the luminance calibration coefficient.

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[0089] As described above, the spectroscopic camera 100 of this embodiment includes a spectroscopic element 60 and a photoreceiver 70, and the correction method of the spectroscopic camera 100 includes making light 31 of a first wavelength number from a spectroscopic light source 30 incident on the spectroscopic element 60, receiving light 32 of a second wavelength number emitted from the spectroscopic element 60 with the photoreceiver 70, generating a matrix representing the spectroscopic characteristics based on the output from the photoreceiver 70, and storing the correction matrix generated by the inverse matrix of the matrix in the memory unit 24.

[0090] According to this method, the actual spectral characteristics obtained by receiving light by the optical receiver 70 are corrected. Therefore, compared to conventional methods that measure a spectral spectrum based on a correction value created in advance, it is possible to cancel out the characteristics of, for example, the medium or light source, and to measure an accurate spectral spectrum that is not affected by characteristic dependency. In addition, there is no need to have data for correction in advance, and correction values ​​can be created using only the components of the spectral camera 100, so a highly versatile spectral camera 100 can be provided. Furthermore, an accurate spectral spectrum can be measured regardless of the object being measured.

[0091] In the spectroscopic camera 100, the inverse matrix is ​​the correction value M † It is preferable that the following formula is satisfied when the spectral characteristics are M, the regularization parameter is β, and the unit matrix is ​​I: M † =(M+β·I) -1 Using this formula, when the regularization parameter β is large, the correction value M † The unit matrix I approaches 1 and becomes the same as without correction. When the regularization parameter β is 0, the correction value M †is the simple inverse matrix M of the spectral characteristic M -1 That is, the regularization parameter β is a parameter that limits the amount of correction. Therefore, by adjusting the regularization parameter β, overfitting can be suppressed.

[0092] In the spectroscopic camera 100, the inverse matrix is ​​the correction value M † It is preferable that the following formula is satisfied when the spectral characteristics are M, the regularization parameter is β, and the unit matrix is ​​I: M † =M T (M.M. T +β·I) -1 According to this method, the regularization term β·I is added to the commonly known pseudo-inverse matrix, and even if the spectral characteristic M is not a square matrix, the correction value M † can be obtained.

[0093] In the spectroscopic camera 100, the inverse matrix is ​​the correction value M † It is preferable that the following formula is satisfied when the spectral characteristic is M and the regularization parameter is β: M † =(M+β(M T ) -1 ) -1 According to this method, when the spectral characteristic M is a square matrix, the pseudo-inverse matrix with a regularization term according to claim 3 can be obtained in a simplified manner. β(M T ) -1 is the regularization term. The correction value M for the regularization parameter β † The behavior of is different from that of claim 2. When the regularization parameter β is 0, the correction value M † is the simple inverse matrix M of the spectral characteristic M -1 becomes.

[0094] Furthermore, in the spectroscopic camera 100, the spectroscopic element 60 preferably has a pair of reflective films 63, 64 and a gap changer 65 that can change the gap dimension between the pair of reflective films 63, 64, and is disposed on the optical path of light incident on the photoreceiver 70. According to this method, since the spectroscopic element 60 having the above configuration is disposed on the optical path, it is possible to measure an accurate optical spectrum regardless of the object to be measured, as compared to, for example, a wavelength dispersive type.

[0095] Furthermore, it is preferable that the light receiver 70 is an optical sensor array in the spectroscopic camera 100. According to this method, since an optical sensor array is used, it is possible to measure the object to be measured over a wide range with high accuracy.

[0096] The computer program is a computer program for correcting a spectroscopic camera 100 having a spectroscopic element 60 and a light receiver 70, and includes causing light 31 of a first wavelength number from a spectroscopic light source 30 to enter the spectroscopic element 60, receiving light 32 of a second wavelength number emitted from the spectroscopic element 60 with the light receiver 70, generating a matrix representing the spectroscopic characteristics based on the output from the light receiver 70, and storing the correction matrix generated by the inverse matrix of the matrix in the memory unit 24.

[0097] This computer program corrects the actual spectral characteristics obtained by receiving light with the optical receiver 70. This makes it possible to cancel out the characteristics of, for example, the medium or light source, compared to a method of measuring a spectral spectrum based on a pre-created correction value, thereby enabling accurate spectral measurements that are not affected by characteristic dependencies. In addition, since there is no need to have data for correction in advance and correction values ​​can be created using only the components of the spectral camera 100, a highly versatile spectral camera 100 can be provided. Furthermore, accurate spectral measurements can be made regardless of the object being measured.

[0098] A modification of the above embodiment will now be described.

[0099] The spectroscopic measuring instrument is not limited to the spectroscopic camera 100 described above, and for example, a spectroscopic camera 200 shown in FIG. 21 may be used.

[0100] The spectroscopic camera 200 of the modified example differs from the above embodiment in that a general-purpose spectrophotometer 270 (MCPD, Otsuka Electronics Co., Ltd.) is installed instead of the photoreceiver 70 to measure the spectroscopic characteristics of the spectroscopic element 60.

[0101] The modified spectroscopic camera 200 includes an illumination light source (LED) 130, a band-pass filter 50, a spectroscopic element 60, and a general-purpose spectrophotometer 270. A white tile is used as the reference measurement object 210. In this measurement, the spectral characteristics of the spectroscopic element 60 also include the spectral characteristics of the illumination light source 130, the reference measurement object 210, and the band-pass filter 50.

[0102] Correction value M -1 When calculating reflectance R, the measured spectral characteristics are further multiplied by the spectral characteristics of the spectrophotometer 270 (photoreceiver). The spectral characteristics of the spectrophotometer 270 may use manufacturer data, or data measured by a separate dedicated measuring device. The method for calculating reflectance R is the same as in the above embodiment.

[0103] Correction value M by inverse matrix -1 In the above, the original spectral characteristic data needs to be a square matrix (m × m) with the same number of rows and columns, but by using a pseudo-inverse matrix as shown in the following equations (27) to (29), correction values ​​can be created even for matrices with different numbers of rows and columns (see FIG. 22). In other words, correction values ​​can be created even if the measurement pitch eλ of the spectral characteristics and the data pitch λ are different.

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[0107] This spectroscopic camera 200 has a built-in illumination light source 130, so it can measure the reflectance spectrum of a white tile. When the spectroscopic camera 200 is equipped with the illumination light source 130, the accuracy of correction is improved by measuring the illumination light source 130 as well. Furthermore, by measuring with a highly accurate spectrophotometer 270, an accurate reflectance spectrum can be measured.

[0108] Furthermore, the above-mentioned light receiver 70 may be a single light sensor, or may be a light sensor array, an area sensor, an image sensor, a camera, or the like.

[0109] Furthermore, in the above embodiment, the light receiver 70 of the spectrometer includes an array in which a plurality of light sensors are arranged two-dimensionally, but it may also be composed of a single light receiving sensor. [Explanation of symbols]

[0110] 10...measurement unit, 20...control unit, 21...processing unit, 22...matrix generation unit, 23...correction matrix generation unit, 24...memory unit as memory device, 30...spectrographic light source, 31, 32...light, 33, 34...light ray, 40...incident optical system, 50...bandpass filter, 60...spectrographic element as variable wavelength spectral filter, 61, 62...pair of substrates, 63, 64...pair of reflective films, 65...gap changing unit, 70...photoreceiver as optical sensor, 100...spectrographic camera as spectroscopic measuring instrument, 130...illumination light source, 200...spectrographic camera, 210...reference measurement object, 270...spectrophotometer.

Claims

1. A spectroscopic measuring instrument comprising a variable wavelength spectral filter and an optical sensor, The method for correcting the spectrometer comprises: causing light of a first wavelength number from a spectral light source to be incident on the variable wavelength spectral filter; The light of the second wavelength number emitted from the variable wavelength spectral filter is received by the optical sensor. And, generating a matrix representing a spectral characteristic based on an output from the optical sensor; A correction matrix is ​​generated based on the inverse matrix of the matrix, and the correction matrix is ​​stored in a storage device. To pay, and Multiplying the spectral output of the spectrometer obtained by measuring the object by the correction matrix. By this, the spectral characteristics of the variable wavelength spectral filter are cancelled, and the spectral characteristics of the object to be measured are corrected. Get sexuality, the inverse matrix includes a correction value M † , When the spectral characteristics are M, the regularization parameter is β, and the unit matrix is ​​I, the following Spectroscopic instruments that satisfy the formula. M † =M T (M・M T +β・I) -1

2. A spectroscopic measuring instrument comprising a variable wavelength spectral filter and an optical sensor, The method for correcting the spectrometer comprises: causing light of a first wavelength number from a spectral light source to be incident on the variable wavelength spectral filter; The light of the second wavelength number emitted from the variable wavelength spectral filter is received by the optical sensor. And, generating a matrix representing a spectral characteristic based on an output from the optical sensor; A correction matrix is ​​generated based on the inverse matrix of the matrix, and the correction matrix is ​​stored in a storage device. To pay, and Multiplying the spectral output of the spectrometer obtained by measuring the object by the correction matrix. By this, the spectral characteristics of the variable wavelength spectral filter are cancelled, and the spectral characteristics of the object to be measured are corrected. Get sexuality, the inverse matrix includes a correction value M † , A spectrometer that satisfies the following formula when the spectral characteristic is M and the regularization parameter is β: Measuring instrument. M † = (M + β (M T ) -1 ) -1

3. 3. The spectrometer according to claim 1, The variable wavelength spectral filter has a pair of reflective films and a gap dimension between the pair of reflective films. A variable gap changer is provided, and the variable gap changer is disposed on the optical path of light incident on the optical sensor. Spectroscopic measuring instruments.

4. The spectroscopic measuring instrument according to any one of claims 1 to 3, The spectroscopic instrument, wherein the optical sensor is an optical sensor array.

5. A computer that corrects a spectroscopic measuring instrument having a variable wavelength spectral filter and an optical sensor. A computer program, The computer program comprises: causing light of a first wavelength number from a spectral light source to be incident on the variable wavelength spectral filter; The light of the second wavelength number emitted from the variable wavelength spectral filter is received by the optical sensor. And, generating a matrix representing a spectral characteristic based on an output from the optical sensor; A correction matrix is ​​generated based on the inverse matrix of the matrix, and the correction matrix is ​​stored in a storage device. To pay, multiplying the spectral output of the spectrometer obtained by measuring the object to be measured by the correction matrix; By combining the variable wavelength spectral filter, the spectral characteristics of the variable wavelength spectral filter are cancelled, and the object to be measured is It is possible to obtain the spectral characteristics of the inverse matrix includes a correction value M † , When the spectral characteristics are M, the regularization parameter is β, and the unit matrix is ​​I, the following A computer program that satisfies the equation. M † =M T (M・M T +β・I) -1

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