Color measurement method based on hyperspectral imaging

Abstract

The invention relates to the technical field of color measurement, in particular to a color measurement method based on hyperspectral imaging, which comprises the following steps: judging whether the chromatic aberration of a to-be-measured sample needs to be calculated or not, and if the chromatic aberration of the to-be-measured sample needs to be calculated, presetting a standard color value, and acquiring dark background hyperspectral data of the to-be-measured sample based on a hyperspectral imaging device, otherwise, directly acquiring the dark background hyperspectral data of the to-be-measured sample based on the hyperspectral imaging device. According to the method, the dark background hyperspectral data, the reflectivity calibration plate data and the real-time hyperspectral data of the sample are collected and corrected, so that the color measurement precision can be remarkably improved, the interference of an ambient light source and equipment noise is eliminated, the finally obtained standard real-time hyperspectral data is ensured to reflect the real spectral characteristics of the sample to be measured, and the accuracy of color measurement is improved. And the corrected standard real-time hyperspectral data can more accurately reflect the reflectivity spectrum of the sample to be detected, so that the calculation of the color value is more accurate.

Description

Technical Field

[0001] The invention relates to the technical field of color measurement, and in particular to a color measurement method based on hyperspectral imaging. Background Art

[0002] Hyperspectral imaging is a technology for obtaining spectral information of the surface of an object. It combines imaging technology and spectral analysis and can obtain image data in multiple continuous spectral bands. Unlike traditional RGB imaging, hyperspectral imaging not only captures visible light information, but also covers other bands such as infrared and ultraviolet, thereby obtaining richer spectral features.

[0003] Traditional methods usually rely on relatively simple equipment (such as colorimeter or photometer) for measurement, which is easily affected by changes in illumination, background interference and the noise of the equipment itself. These factors may cause unstable measurement results and make it difficult to reflect the true spectral characteristics of the sample. Traditional methods usually do not have the background correction function of hyperspectral imaging systems and cannot effectively eliminate the interference of background light sources, changes in environmental conditions and equipment noise, which makes the measurement results likely to be affected by environmental fluctuations, resulting in large differences in measurement results at different times and under different conditions. Traditional methods usually use simple color difference calculation formulas and may only measure based on a few color channels (such as RGB or XYZ models). These methods often lack sufficient color information and are difficult to fully and accurately reflect the color characteristics of the sample. Moreover, traditional methods often rely on manual setting of standard colors and judgment of color differences, which are subjective and prone to errors, especially in batch control and large-scale testing. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the disadvantages of the above-mentioned prior art and provide a color measurement method based on hyperspectral imaging.

[0005] The technical solution adopted to solve the above technical problems is: a color measurement method based on hyperspectral imaging, including:

[0006] Determine whether it is necessary to calculate the color difference of the sample to be measured. If it is necessary to calculate the color difference of the sample to be measured, pre-set the standard color value, and collect the dark background hyperspectral data of the sample to be measured based on the hyperspectral imaging device; otherwise, directly collect the dark background hyperspectral data of the sample to be measured based on the hyperspectral imaging device;

[0007] Based on a preset target light source irradiating a preset reflectance calibration plate, the hyperspectral data of the reflectance calibration plate of the sample to be measured in the reflectance calibration plate is collected based on the hyperspectral imaging device;

[0008] Based on the hyperspectral imaging device, real-time hyperspectral data of the sample to be measured is collected, and based on the dark background hyperspectral data of the sample to be measured and the hyperspectral data of the reflectance calibration plate, the real-time hyperspectral data of the sample to be measured is corrected to obtain standard real-time hyperspectral data of the sample to be measured;

[0009] Calculate the reflectance spectrum of the standard real-time hyperspectral data of the sample to be measured;

[0010] The color value of the sample to be measured is calculated based on the reflectance spectrum of the standard real-time hyperspectral data of the sample to be measured, and the color difference value of the sample to be measured is calculated based on the preset standard color value and the color value of the sample to be measured.

[0011] Preferably, the expression of the dark background hyperspectral data of the sample to be measured is as follows:

[0012] DC_BK(x1, y1, b1);

[0013] Among them, DC_BK(x1, y1, b1) represents the dark background hyperspectral data, x1 represents the number of sampling points in the spatial dimension of the dark background hyperspectral data in the FOV direction, y1 represents the number of sampling frames in the time dimension of the dark background hyperspectral data, and b1 represents the number of sampling points in the wavelength dimension of the dark background hyperspectral data.

[0014] Preferably, the expression of the hyperspectral data of the reflectivity calibration plate of the sample to be measured is as follows:

[0015] DC_WB(x2,y2,b2);

[0016] Among them, DC_WB(x2, y2, b2) represents the dark background hyperspectral data, x2 represents the number of spatial dimension sampling points in the FOV direction of the reflectance calibration plate hyperspectral data, y2 represents the number of spatial dimension sampling points in the push-scan direction of the reflectance calibration plate hyperspectral data, and b2 represents the number of sampling points in the wavelength dimension of the reflectance calibration plate hyperspectral data.

[0017] Preferably, the expression of the real-time hyperspectral data of the sample to be measured is as follows:

[0018] DC_Bbj(x3_t, y3_t, b3_t);

[0019] Among them, DC_Bbj(x3_t, y3_t, b3_t) represents the real-time hyperspectral data at time t, x3_t represents the number of spatial dimension sampling points in the FOV direction of the real-time hyperspectral data at time t, y3_t represents the number of spatial dimension sampling points in the push-scan direction of the real-time hyperspectral data at time t, and b3_t represents the number of sampling points in the wavelength dimension of the real-time hyperspectral data at time t.

[0020] Preferably, the real-time hyperspectral data of the sample to be measured is corrected based on the dark background hyperspectral data of the sample to be measured and the hyperspectral data of the reflectance calibration plate to obtain the standard real-time hyperspectral data of the sample to be measured, including:

[0021] Calculate average frame dark background hyperspectral data of the dark background hyperspectral data;

[0022] Calculate the first average frame reflectance calibration plate hyperspectral data of the reflectance calibration plate hyperspectral data;

[0023] Calculate the second average frame reflectance calibration plate hyperspectral data of the reflectance calibration plate hyperspectral data;

[0024] The real-time hyperspectral data of the sample to be measured is corrected based on the average frame dark background hyperspectral data, the first average frame reflectivity calibration plate hyperspectral data and the second average frame reflectivity calibration plate hyperspectral data to obtain standard real-time hyperspectral data of the sample to be measured.

[0025] Preferably, the calculation formula of the average frame dark background hyperspectral data is as follows:

[0026]

[0027] Among them, DC _ BK_Frame(xm, 1, bn) represents the average frame dark background hyperspectral data;

[0028] The calculation formula of the first average frame reflectance calibration plate hyperspectral data is as follows:

[0029]

[0030] Among them, DC _ Light(xm, 1, 1) represents the first average frame reflectance calibration plate hyperspectral data;

[0031] The calculation formula of the second average frame reflectance calibration plate hyperspectral data is as follows:

[0032]

[0033] Wherein, DC_Ref(1, 1, bn) represents the hyperspectral data of the second average frame reflectivity calibration plate.

[0034] Preferably, the correction formula of the real-time hyperspectral data of the sample to be measured is as follows:

[0035]

[0036] Wherein, DC_Ref(1, 1, bn) represents the hyperspectral data of the second average frame reflectivity calibration plate.

[0037] Preferably, the calculation formula of the reflectance spectrum of the standard real-time hyperspectral data of the sample to be measured is as follows:

[0038]

[0039] Among them, DC_Obj_ref xi，yj，bk represents the reflectance spectrum of the standard real-time hyperspectral data of the sample to be measured, and Ref_ref(1, 1, bk) represents the real reflectance of the reflectance calibration plate.

[0040] Preferably, the calculation formula of the color value of the sample to be measured is as follows:

[0041]

[0042] Wherein, X, Y and Z represent three components of the color value of the sample to be measured, K represents the magnification correction coefficient, and XC, YC and ZC represent the response coefficients of the three components of the color value of the sample to be measured respectively.

[0043] The beneficial effects of the present invention are as follows: (1) The present invention can significantly improve the accuracy of color measurement by collecting dark background hyperspectral data, reflectance calibration plate data and real-time hyperspectral data of the sample and performing corrections. By eliminating the interference of ambient light sources and equipment noise, it is ensured that the final obtained standard real-time hyperspectral data reflects the true spectral characteristics of the sample to be measured, and the corrected standard real-time hyperspectral data can more accurately reflect the reflectance spectrum of the sample to be measured, thereby making the calculation of the color value more accurate; (2) The present invention can effectively reduce the interference caused by background light sources, environmental conditions or equipment noise by collecting and using dark background hyperspectral data. This background correction method makes the color measurement result more stable and reliable, and is suitable for measurement needs in different environments. The standard color value is set and compared with the color value of the sample to be tested, and the color difference is calculated. By comparing the standard color value, the difference between the sample to be tested and the standard color can be quantified, thereby providing an objective and quantitative basis for color control and ensuring the color consistency and comparability of different batches and different scenes; (3) The present invention can collect the hyperspectral data of the sample in real time, so the method is suitable for occasions requiring real-time monitoring and dynamic control. By timely correcting and calculating the reflectance spectrum of the sample, the standard color value of the sample can be obtained in a short time, and the accurate color difference can be calculated, providing support for applications such as online quality inspection and production line color control. Moreover, due to the high degree of automation of the hyperspectral imaging system, after combining the correction process, the method can complete the color measurement task without a lot of manual intervention, which reduces human errors and subjective judgments, improves measurement efficiency and accuracy, and is particularly suitable for large-scale production inspection or batch quality control. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A schematic flow chart of the steps of an overall method in an embodiment of the present invention;

[0045] Figure 2 A schematic diagram of dark background hyperspectral data in an embodiment of the present invention;

[0046] Figure 3 A schematic diagram of a light intensity distribution curve of a reflectivity calibration plate in an embodiment of the present invention;

[0047] Figure 4 A schematic diagram of a hyperspectral data curve of a second average frame reflectivity calibration plate in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] Embodiment 1, as Figure 1 As shown, the present invention proposes a color measurement method based on hyperspectral imaging, comprising:

[0049] S1. Determine whether it is necessary to calculate the color difference of the sample to be measured. If it is necessary to calculate the color difference of the sample to be measured, pre-set the standard color value, and collect the dark background hyperspectral data of the sample to be measured based on the hyperspectral imaging device. Otherwise, directly collect the dark background hyperspectral data of the sample to be measured based on the hyperspectral imaging device.

[0050] It should be noted that if Figure 2 Shown are dark background hyperspectral data;

[0051] S2, irradiating a preset reflectance calibration plate with a preset target light source, and collecting reflectance calibration plate hyperspectral data of the sample to be measured in the reflectance calibration plate using a hyperspectral imaging device;

[0052] S3, collecting real-time hyperspectral data of the sample to be measured based on the hyperspectral imaging device, and correcting the real-time hyperspectral data of the sample to be measured based on the dark background hyperspectral data of the sample to be measured and the hyperspectral data of the reflectivity calibration plate to obtain standard real-time hyperspectral data of the sample to be measured;

[0053] S4, calculating the reflectance spectrum of the standard real-time hyperspectral data of the sample to be measured;

[0054] S5. Calculate the color value of the sample to be measured based on the reflectance spectrum of the standard real-time hyperspectral data of the sample to be measured, and calculate the color difference value of the sample to be measured based on the preset standard color value and the color value of the sample to be measured.

[0055] In the present invention, the sample to be measured refers to an object or surface that needs to be measured and color analyzed, for example, it can be food, plants, clothing, paint or any other items that need to be evaluated by color; the hyperspectral imaging device is a device used to obtain the reflectance data of an object at multiple wavelengths (usually hundreds to thousands of continuous bands). Unlike traditional RGB images, hyperspectral imaging not only captures images in the visible light range, but also includes data of infrared, ultraviolet and other wavelengths, thereby providing more detailed spectral information for applications such as material identification and quality analysis; the dark background refers to the background signal captured by the hyperspectral device when the sample is not irradiated. The dark background data is used in the subsequent correction process to remove the influence of environmental noise, instrument noise, etc., to ensure that the collected data reflects only the true signal of the target sample; the reflectance calibration plate is a standard plate with a known reflectance, which is usually used to calibrate hyperspectral imaging equipment. The reflectance of the calibration plate is measured at each wavelength. The following are known, which can help the device perform spectral calibration when collecting data to ensure the accuracy of the measurement results; the hyperspectral data obtained from the reflectance calibration plate, since the reflectance of the calibration plate is known, by comparing these data with the actual data collected by the device, the device can be calibrated to convert the measured data into a standard reflectance value; real-time hyperspectral data This refers to the hyperspectral data of the sample to be tested obtained by the device during the real-time acquisition process, that is, the reflectance information at each wavelength captured by the device under the irradiation of the light source. These data contain the reflection characteristics of the sample to be tested at different wavelengths for subsequent analysis; the reflectance spectrum refers to the reflectance value of the sample to be tested at different wavelengths. The reflectance is the proportion of the incident light reflected by the surface of an object, usually a value between 0 and 1. By measuring the reflectance of the sample at multiple wavelengths, its complete spectral curve can be obtained; the color value refers to the numerical representation of the sample in a specific color space.

[0056] Embodiment 2, as Figure 3-Figure 4 As shown, the color measurement method based on hyperspectral imaging proposed by the present invention, compared with the first embodiment, this embodiment also includes: the expression of the dark background hyperspectral data of the sample to be measured is as follows:

[0057] DC_BK(x1, y1, b1);

[0058] Among them, DC_BK(x1, y1, b1) represents the dark background hyperspectral data, x1 represents the number of sampling points in the spatial dimension of the dark background hyperspectral data in the FOV direction, y1 represents the number of sampling frames in the time dimension of the dark background hyperspectral data, and b1 represents the number of sampling points in the wavelength dimension of the dark background hyperspectral data.

[0059] In this embodiment, FOV (Field of View) refers to the spatial range that the hyperspectral imaging system can capture. In hyperspectral imaging, the FOV direction usually refers to the direction in which the imaging device collects samples in space. For example, FOV can be the horizontal or vertical field of view of the device, which affects the spatial resolution of the data; the number of sampling points in the spatial dimension of the FOV direction refers to the number of data points collected when the samples are sampled in the spatial dimension in the FOV direction, which represents the resolution obtained by the imaging device in space. The more sampling points, the higher the spatial resolution; the number of sampling frames in the time dimension represents the number of hyperspectral data frames collected by the system from different time points within a period of time. Each frame of data corresponds to the data at a time point, which is very important for dynamic monitoring or studying the time change process; the number of sampling points in the wavelength dimension represents the number of data points collected in the wavelength dimension. Usually, the hyperspectral imaging device will sample at multiple wavelengths, which can range from ultraviolet to visible light, and then to near infrared or mid-infrared range. The more sampling points in the wavelength dimension, the more refined the data, and can provide more information.

[0060] In an optional embodiment, the expression of the hyperspectral data of the reflectivity calibration plate of the sample to be measured is as follows:

[0061] DC_WB(x2,y2,b2);

[0062] Among them, DC_WB(x2, y2, b2) represents the dark background hyperspectral data, x2 represents the number of spatial dimension sampling points in the FOV direction of the reflectance calibration plate hyperspectral data, y2 represents the number of spatial dimension sampling points in the push-scan direction of the reflectance calibration plate hyperspectral data, and b2 represents the number of sampling points in the wavelength dimension of the reflectance calibration plate hyperspectral data.

[0063] In an optional embodiment, the expression of the real-time hyperspectral data of the sample to be measured is as follows:

[0064] DC_Bbj(x3_t, y3_t, b3, b);

[0065] Among them, DC_Bbj(x3_t, y3_t, b3_t) represents the real-time hyperspectral data at time t, x3_t represents the number of spatial dimension sampling points in the FOV direction of the real-time hyperspectral data at time t, y3_t represents the number of spatial dimension sampling points in the push-scan direction of the real-time hyperspectral data at time t, and b3_t represents the number of sampling points in the wavelength dimension of the real-time hyperspectral data at time t.

[0066] In an optional embodiment, the real-time hyperspectral data of the sample to be measured is corrected based on the dark background hyperspectral data of the sample to be measured and the hyperspectral data of the reflectance calibration plate to obtain standard real-time hyperspectral data of the sample to be measured, including:

[0067] Calculate the average frame dark background hyperspectral data of the dark background hyperspectral data;

[0068] Calculate the first average frame of the reflectivity calibration plate hyperspectral data;

[0069] Calculate the second average frame reflectance calibration plate hyperspectral data of the reflectance calibration plate hyperspectral data;

[0070] The real-time hyperspectral data of the sample to be measured is corrected based on the average frame dark background hyperspectral data, the first average frame reflectivity calibration plate hyperspectral data and the second average frame reflectivity calibration plate hyperspectral data to obtain standard real-time hyperspectral data of the sample to be measured.

[0071] In an optional embodiment, the calculation formula of the average frame dark background hyperspectral data is as follows:

[0072]

[0073] Among them, DC _ BK_Frame(xm, 1, bn) represents the average frame dark background hyperspectral data;

[0074] The calculation formula of the first average frame reflectance calibration plate hyperspectral data is as follows:

[0075]

[0076] Among them, DC_Light(xm, 1, 1) represents the hyperspectral data of the first average frame reflectivity calibration plate:

[0077] The calculation formula of the second average frame reflectance calibration plate hyperspectral data is as follows:

[0078]

[0079] Wherein, DC_Ref(1, 1, bn) represents the hyperspectral data of the second average frame reflectivity calibration plate.

[0080] In an optional embodiment, the correction formula of the real-time hyperspectral data of the sample to be measured is as follows:

[0081]

[0082] Wherein, DC_Ref(1, 1, bn) represents the hyperspectral data of the second average frame reflectivity calibration plate.

[0083] In an optional embodiment, the calculation formula of the reflectance spectrum of the standard real-time hyperspectral data of the sample to be measured is as follows:

[0084]

[0085] Among them, DC_Obj_ref xi，yj，bk represents the reflectance spectrum of the standard real-time hyperspectral data of the sample to be measured, and Ref_ref(1, 1, bk) represents the real reflectance of the reflectance calibration plate.

[0086] In an optional embodiment, the calculation formula of the color value of the sample to be measured is as follows:

[0087]

[0088] Wherein, X, Y and Z represent three components of the color value of the sample to be measured, K represents the magnification correction coefficient, and XC, YC and ZC represent the response coefficients of the three components of the color value of the sample to be measured respectively.

[0089] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited thereto, and various changes can be made within the knowledge scope of technicians in the relevant technical field without departing from the purpose of the present invention.

Claims

1. A color measurement method based on hyperspectral imaging, characterized in that: include: Determine whether it is necessary to calculate the color difference of the sample to be measured. If it is necessary to calculate the color difference of the sample to be measured, pre-set the standard color value, and collect the dark background hyperspectral data of the sample to be measured based on the hyperspectral imaging device; otherwise, directly collect the dark background hyperspectral data of the sample to be measured based on the hyperspectral imaging device; Based on a preset target light source irradiating a preset reflectance calibration plate, the hyperspectral data of the reflectance calibration plate of the sample to be measured in the reflectance calibration plate is collected based on the hyperspectral imaging device; Based on the hyperspectral imaging device, real-time hyperspectral data of the sample to be measured is collected, and based on the dark background hyperspectral data of the sample to be measured and the hyperspectral data of the reflectance calibration plate, the real-time hyperspectral data of the sample to be measured is corrected to obtain standard real-time hyperspectral data of the sample to be measured; Calculate the reflectance spectrum of the standard real-time hyperspectral data of the sample to be measured; The color value of the sample to be measured is calculated based on the reflectance spectrum of the standard real-time hyperspectral data of the sample to be measured, and the color difference value of the sample to be measured is calculated based on the preset standard color value and the color value of the sample to be measured.

2. The color measurement method based on hyperspectral imaging according to claim 1, characterized in that: The expression of the dark background hyperspectral data of the sample to be measured is as follows: DC_BK(x1,y1,b1); Among them, DC_BK(x1,y1,b1) represents the dark background hyperspectral data, x1 represents the number of sampling points in the spatial dimension of the dark background hyperspectral data in the FOV direction, y1 represents the number of sampling frames in the time dimension of the dark background hyperspectral data, and b1 represents the number of sampling points in the wavelength dimension of the dark background hyperspectral data.

3. The color measurement method based on hyperspectral imaging according to claim 2, characterized in that: The expression of the hyperspectral data of the reflectivity calibration plate of the sample to be measured is as follows: DC_WB(x2,y2,b2); Among them, DC_WB(x2,y2,b2) represents the dark background hyperspectral data, x2 represents the number of spatial dimension sampling points in the FOV direction of the reflectance calibration plate hyperspectral data, y2 represents the number of spatial dimension sampling points in the push-scan direction of the reflectance calibration plate hyperspectral data, and b2 represents the number of sampling points in the wavelength dimension of the reflectance calibration plate hyperspectral data.

4. The color measurement method based on hyperspectral imaging according to claim 3 is characterized in that: The expression of the real-time hyperspectral data of the sample to be measured is as follows: DC_Bbj(x3_t,y3_t,b3_t); Among them, DC_Bbj(x3_t,y3_t,b3_t) represents the real-time hyperspectral data at time t, x3_t represents the number of spatial dimension sampling points in the FOV direction of the real-time hyperspectral data at time t, y3_t represents the number of spatial dimension sampling points in the push-scan direction of the real-time hyperspectral data at time t, and b3_t represents the number of sampling points in the wavelength dimension of the real-time hyperspectral data at time t.

5. The color measurement method based on hyperspectral imaging according to claim 4, characterized in that: Correcting the real-time hyperspectral data of the sample to be measured based on the dark background hyperspectral data of the sample to be measured and the hyperspectral data of the reflectance calibration plate to obtain standard real-time hyperspectral data of the sample to be measured, including: Calculate average frame dark background hyperspectral data of the dark background hyperspectral data; Calculate the first average frame reflectance calibration plate hyperspectral data of the reflectance calibration plate hyperspectral data; Calculate the second average frame reflectance calibration plate hyperspectral data of the reflectance calibration plate hyperspectral data; The real-time hyperspectral data of the sample to be measured is corrected based on the average frame dark background hyperspectral data, the first average frame reflectivity calibration plate hyperspectral data and the second average frame reflectivity calibration plate hyperspectral data to obtain standard real-time hyperspectral data of the sample to be measured.

6. The color measurement method based on hyperspectral imaging according to claim 5, characterized in that: The calculation formula of the average frame dark background hyperspectral data is as follows: Among them, DC_BK_Frame(xm,1,bn) represents the average frame dark background hyperspectral data; The calculation formula of the first average frame reflectance calibration plate hyperspectral data is as follows: Wherein, DC_Light(xm,1,1) represents the hyperspectral data of the first average frame reflectance calibration plate; The calculation formula of the second average frame reflectance calibration plate hyperspectral data is as follows: Wherein, DC_Ref(1,1,bn) represents the hyperspectral data of the second average frame reflectivity calibration plate.

7. The color measurement method based on hyperspectral imaging according to claim 6, characterized in that: The correction formula for the real-time hyperspectral data of the sample to be measured is as follows: Wherein, DC_Ref(1,1,bn) represents the hyperspectral data of the second average frame reflectivity calibration plate.

8. The color measurement method based on hyperspectral imaging according to claim 7, characterized in that: The calculation formula of the reflectance spectrum of the standard real-time hyperspectral data of the sample to be measured is as follows: Among them, DC_Obj_ref xi,yj,bk Ref_ref(1,1,bk) represents the reflectance spectrum of the standard real-time hyperspectral data of the sample to be measured, and Ref_ref(1,1,bk) represents the actual reflectance of the reflectance calibration plate.

9. The color measurement method based on hyperspectral imaging according to claim 8, characterized in that: The calculation formula of the color value of the sample to be measured is as follows: Wherein, X, Y and Z represent three components of the color value of the sample to be measured, K represents the magnification correction coefficient, and XC, YC and ZC represent the response coefficients of the three components of the color value of the sample to be measured respectively.

Images