Infrared temperature measurement method, device, equipment and product without baffle

Abstract

The present application discloses a baffle-free infrared temperature measurement method, device, equipment and product, and relates to the field of infrared image processing technology. The method includes: performing non-uniform correction on infrared images, and the non-uniform correction is used to improve the pixel error generated by infrared imaging equipment during the imaging process. After the non-uniform correction is completed, the temperature of the high and low temperature box is controlled to rise, and the background of black bodies of different temperatures is collected at different movement temperatures to obtain a corresponding relationship data set of the movement temperature, the black body temperature and the black body pixel. Based on the corresponding relationship data set, the relationship between the black body pixels of q black bodies of different temperatures and the current movement temperature is fitted to obtain the fitted pixel values ​​of the q black bodies of different temperatures. The black body temperature and the fitted pixel value are fitted according to the Lagrange interpolation method to obtain the target function relationship, and the pixel value of the target to be measured is input into the target function relationship to obtain the target temperature. The above method can not only improve the dynamic range of temperature measurement, but also improve the measurement accuracy.

Description

Technical Field

[0001] The present application relates to the field of infrared image processing technology, and in particular to a baffle-free infrared temperature measurement method, device, equipment and product. Background Art

[0002] As an important means of non-contact temperature measurement, infrared radiation measurement technology has been widely used in various industrial fields and scientific research scenarios. In traditional infrared temperature measurement technology, devices with baffles are often used to filter or calibrate stray light during the measurement process to improve the accuracy and stability of temperature measurement. However, the existence of baffles also brings a series of problems, such as increasing the complexity and cost of the equipment, limiting the flexibility and response speed of temperature measurement, and the temperature measurement results may also be affected by damage or contamination of the baffles.

[0003] However, the infrared thermometer without a barrier has a higher sensitivity to infrared radiation, but it may also receive more background noise and irrelevant information, thus affecting the accuracy of temperature measurement.

[0004] Therefore, how to improve the temperature measurement accuracy in the process of infrared temperature measurement without a baffle is a problem that needs to be solved urgently. Summary of the invention

[0005] The main purpose of the present application is to provide a baffle-free infrared temperature measurement method, device, equipment and product, aiming to solve the technical problem of how to improve the temperature measurement accuracy in the process of baffle-free infrared temperature measurement.

[0006] To achieve the above object, the present application proposes a baffle-free infrared temperature measurement method, the method comprising:

[0007] Performing non-uniform correction on the infrared image, wherein the non-uniform correction is used to improve the pixel error generated by the infrared imaging device during the imaging process;

[0008] After the non-uniform correction is completed, the high and low temperature boxes are controlled to heat up, and the background of black bodies at different temperatures are collected at different core temperatures to obtain a corresponding relationship data set of the core temperature, the black body temperature, and the black body pixels;

[0009] Based on the corresponding relationship data set, fitting the relationship between the black body pixels of q black bodies with different temperatures and the current movement temperature to obtain the fitting pixel values ​​of the q black bodies with different temperatures;

[0010] Fitting the black body temperature and the fitting pixel value according to the Lagrange interpolation method to obtain an objective function relationship;

[0011] The pixel value of the target to be measured is input into the target function relationship to obtain the target temperature.

[0012] In one embodiment, the step of performing non-uniform correction on the infrared image includes:

[0013] Collect the background data of the infrared movement by controlling the temperature and time conditions, and save the corresponding movement temperature data;

[0014] The collected background data is averaged, and the background pixel value minus the average is subtracted to obtain the background offset;

[0015] Analyzing the core temperature data and the background bias according to the least square method to obtain a first functional relationship, wherein the first functional relationship is used to calculate the fitting bias of each point in the infrared image;

[0016] The original image pixel value and the fitting bias are subtracted to complete the non-uniform correction of the infrared image.

[0017] In one embodiment, the collected background data is averaged, and the background pixel value is subtracted from the average value to obtain the background offset, and the average value is expressed as:

[0018]

[0019] Among them, MEAN(f) represents the mean value of the fth background collected, B (i,j) (f) represents the pixel value of the f-th background (i, j) collected, m represents the length of the image, and n represents the width of the image;

[0020] OFFSET (i,j) (f) = B (i,j) (f)-MEAN(f)

[0021] Among them, OFFSET (i,j) (f) represents the background offset.

[0022] In one embodiment, the step of analyzing the core temperature data and the background bias according to the least square method to obtain a first functional relationship, wherein the first functional relationship is used to calculate the fitting bias of each point in the infrared image, includes:

[0023] Analyzing the movement temperature data and the background bias according to the least square method to obtain a first functional relationship;

[0024] Input the current movement temperature into the first functional relationship to obtain a fitting bias of the first point in the infrared image;

[0025] The fitting offset of each point in the infrared image is calculated according to the fitting offset of the first point.

[0026] In one embodiment, the step of fitting the relationship between the black body pixels of q black bodies with different temperatures and the current movement temperature based on the corresponding relationship data set to obtain the fitting pixel values ​​of the q black bodies with different temperatures includes:

[0027] Analyze the corresponding relationship data set according to the least square method to obtain a second functional relationship;

[0028] Input the current movement temperature into the second functional relationship to obtain a fitting pixel of the first point in the infrared image;

[0029] The fitting pixels of each point in the infrared image are calculated according to the fitting pixels of the first point.

[0030] In one embodiment, the step of fitting the blackbody temperature and the fitting pixel value according to the Lagrange interpolation method to obtain the objective function relationship includes:

[0031] Fitting the blackbody temperature and the fitted pixel value according to the Lagrange interpolation method to obtain the weight proportions corresponding to different temperatures;

[0032] The objective function relationship is determined according to the weight ratio.

[0033] In addition, to achieve the above-mentioned purpose, the present application also proposes an infrared temperature measuring device without a baffle, and the infrared temperature measuring device without a baffle comprises:

[0034] An infrared correction module, used to perform non-uniform correction on the infrared image, wherein the non-uniform correction is used to improve the pixel error generated by the infrared imaging device during the imaging process;

[0035] A data acquisition module, used to control the temperature rise of the high and low temperature boxes after the non-uniform correction is completed, collect the background of black bodies at different temperatures at different core temperatures, and obtain a corresponding relationship data set of core temperature, black body temperature and black body pixels;

[0036] A pixel fitting module, used for fitting the relationship between the black body pixels of q black bodies with different temperatures and the current movement temperature based on the corresponding relationship data set, to obtain the fitting pixel values ​​of the q black bodies with different temperatures;

[0037] A function determination module, used for fitting the black body temperature and the fitting pixel value according to the Lagrange interpolation method to obtain a target function relationship;

[0038] The target temperature measurement module is used to input the pixel value of the target to be measured into the target function relationship to obtain the target temperature.

[0039] In addition, to achieve the above-mentioned purpose, the present application also proposes a baffle-free infrared temperature measurement device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the baffle-free infrared temperature measurement method as described above.

[0040] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the infrared temperature measurement method without a baffle as described above are implemented.

[0041] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of the infrared temperature measurement method without a baffle as described above are implemented.

[0042] One or more technical solutions proposed in this application have at least the following technical effects:

[0043] The infrared image is subjected to non-uniform correction. Through non-uniform correction, the pixel error generated by the infrared imaging device during the imaging process can be improved, so that the temperature information in the image is more accurate and consistent. After the non-uniform correction is completed, the high and low temperature boxes are controlled to heat up, and the background of black bodies of different temperatures are collected at different movement temperatures to obtain the corresponding relationship data set of the movement temperature, black body temperature and black body pixels, so that the system can still maintain high measurement accuracy and stability under different working conditions. Based on the corresponding relationship data set, the relationship between the black body pixels of q black bodies of different temperatures and the current movement temperature is fitted to obtain the fitted pixel values ​​of q black bodies of different temperatures. According to the Lagrange interpolation method, the black body temperature and the fitted pixel value are fitted to obtain the objective function relationship, and finally the pixel value of the target to be measured is input into the objective function relationship to obtain the target temperature. Through the above-mentioned infrared temperature measurement method without baffles, not only the dynamic range of temperature measurement can be improved, but also the measurement accuracy can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0045] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0046] Figure 1This is a flow chart of the first embodiment of the infrared temperature measurement method without a baffle in the present application;

[0047] Figure 2 This is a flow chart of a second embodiment of the infrared temperature measurement method without a baffle of the present application;

[0048] Figure 3 This is a flow chart of a third embodiment of the infrared temperature measurement method without a baffle of the present application;

[0049] Figure 4 This is a schematic diagram of the module structure of an infrared temperature measuring device without a baffle according to an embodiment of the present application;

[0050] Figure 5 Schematic diagram of the device structure of the hardware operating environment involved in the infrared temperature measurement method without a baffle in the embodiment of the present application.

[0051] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0052] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0053] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0054] In traditional infrared temperature measurement technology, devices with baffles are often used to filter or calibrate stray light during the measurement process to improve the accuracy and stability of temperature measurement. However, the existence of baffles also brings a series of problems, such as increasing the complexity and cost of the equipment, limiting the flexibility and response speed of temperature measurement, and the temperature measurement results may be affected by damage or contamination of the baffles. However, infrared thermometers without baffles are more sensitive to infrared radiation, but they may also receive more background noise and irrelevant information, thus affecting the accuracy of temperature measurement.

[0055] The present application provides a solution to perform non-uniform correction on infrared images. Through non-uniform correction, the pixel error generated by infrared imaging equipment during the imaging process can be improved, so that the temperature information in the image is more accurate and consistent. After the non-uniform correction is completed, the temperature rise of the high and low temperature boxes is controlled, and the background of black bodies at different temperatures is collected at different movement temperatures to obtain a corresponding relationship data set of the movement temperature, black body temperature and black body pixels, so that the system can still maintain high measurement accuracy and stability under different working conditions. Based on the corresponding relationship data set, the relationship between the black body pixels of q black bodies at different temperatures and the current movement temperature is fitted to obtain the fitted pixel values ​​of q black bodies at different temperatures. The black body temperature and the fitted pixel value are fitted according to the Lagrange interpolation method to obtain the objective function relationship, and finally the pixel value of the target to be measured is input into the objective function relationship to obtain the target temperature. Through the above-mentioned infrared temperature measurement method without baffles, not only the dynamic range of temperature measurement can be improved, but also the measurement accuracy can be improved.

[0056] Based on this, the embodiment of the present application provides an infrared temperature measurement method without a baffle. Figure 1 , Figure 1 This is a flow chart of the first embodiment of the infrared temperature measurement method without a baffle in the present application.

[0057] In this embodiment, the infrared temperature measurement method without a baffle includes steps S10 to S50:

[0058] Step S10, performing non-uniform correction on the infrared image, where the non-uniform correction is used to improve the pixel error generated by the infrared imaging device during the imaging process.

[0059] It should be noted that non-uniformity correction is an important technology in infrared image processing, which is used to eliminate or reduce the response differences between pixels in the infrared imaging process (such as infrared cameras). This difference may be caused by various factors such as the non-uniformity of the detector manufacturing process, the difference in materials between pixels, and changes in the working environment (such as temperature).

[0060] Step S20, after the non-uniformity correction is completed, the high and low temperature boxes are controlled to heat up, and the background of black bodies at different temperatures are collected at different core temperatures to obtain a corresponding relationship data set of the core temperature, the black body temperature and the black body pixels.

[0061] It should be noted that the high and low temperature chamber is a device that can simulate different temperature environments and is used to test the performance and reliability of products under extreme temperature conditions. The core temperature is the operating temperature of the detector in the infrared camera. A black body can be understood as an idealized object that absorbs all incident radiation without reflecting or transmitting any radiation. In the field of infrared temperature measurement, black bodies are often used as standard heat sources to calibrate infrared cameras. By measuring the radiation intensity of a black body at different temperatures, the temperature measurement accuracy of an infrared camera can be evaluated. The black body temperature is the effective temperature corresponding to the black body radiation. During the calibration process of an infrared camera, the black body is set at different temperature points in order to collect the corresponding radiation data. These temperature points are the black body temperature. The black body pixel is the pixel value corresponding to the black body area in the image when the infrared camera shoots the black body. The correspondence data set is a series of data points collected during the calibration process, which is used to establish the correspondence between the core temperature, black body temperature, and black body pixels.

[0062] Step S30, based on the corresponding relationship data set, fitting the relationship between the black body pixels of q black bodies with different temperatures and the current movement temperature, to obtain the fitting pixel values ​​of the q black bodies with different temperatures.

[0063] It should be noted that q represents the number of blackbodies at different temperatures. It can be understood that the number and temperature of the blackbody settings are determined according to the measurement requirements. For example, if the temperature measurement range is large, a larger number of blackbodies need to be set to improve the measurement accuracy; if the temperature measurement range is small, such as under extreme conditions (such as in a sub-zero temperature environment), a smaller number of blackbodies can be set to avoid wasting resources.

[0064] Step S40, fitting the black body temperature and the fitting pixel value according to the Lagrange interpolation method to obtain the objective function relationship.

[0065] It should be noted that the Lagrange interpolation method is a polynomial interpolation method, which can construct a polynomial function based on a set of known data points (such as blackbody temperature and corresponding fitting pixel values). The objective function relationship is obtained through mathematical methods such as the Lagrange interpolation method, which describes the functional relationship between the blackbody temperature and the fitting pixel value.

[0066] Step S50, inputting the pixel value of the target to be measured into the target function relationship to obtain the target temperature.

[0067] It should be noted that the target to be measured can be understood as an object or area whose temperature needs to be measured. The target temperature is the temperature value of the target to be measured calculated by the objective function relationship, which can be understood as the final result of the infrared temperature measurement process, reflecting the surface temperature of the target to be measured at the measurement time.

[0068] In this embodiment, the infrared image is subjected to non-uniform correction. Through the non-uniform correction, the pixel error generated by the infrared imaging device during the imaging process can be improved, so that the temperature information in the image is more accurate and consistent. After the non-uniform correction is completed, the high and low temperature boxes are controlled to heat up, and the background of black bodies at different temperatures are collected at different movement temperatures to obtain a corresponding relationship data set of the movement temperature, the black body temperature and the black body pixel, so that the system can still maintain high measurement accuracy and stability under different working conditions. Based on the corresponding relationship data set, the relationship between the black body pixels of q black bodies at different temperatures and the current movement temperature is fitted to obtain the fitted pixel values ​​of q black bodies at different temperatures. According to the Lagrange interpolation method, the black body temperature and the fitted pixel value are fitted to obtain the objective function relationship, and finally the pixel value of the target to be measured is input into the objective function relationship to obtain the target temperature. Through the above-mentioned infrared temperature measurement method without baffles, not only the dynamic range of temperature measurement can be improved, but also the resolution of measurement can be improved.

[0069] Reference Figure 2 , Figure 2 This is a flow chart of the second embodiment of the infrared temperature measurement method without a baffle in the present application. Figure 1 The first embodiment shown provides a second embodiment of the infrared temperature measurement method without a baffle of the present application.

[0070] In the second embodiment, the step S10 includes:

[0071] Step S101, collecting background data of the infrared movement by controlling temperature and time conditions, and saving corresponding movement temperature data.

[0072] For example, the infrared movement and the black body are placed in a high and low temperature box, and the temperature is increased by the equation. The specific process can be: after the high and low temperature box is kept at 0 degrees for 1 hour, the infrared movement is powered on and works for 30 minutes, and then the temperature starts to rise, the background is collected, the pixel value of the background is saved, and the temperature of the movement is saved at the same time. The black body is not powered on during the whole process.

[0073] Step S102, calculating the mean of the collected background data, and subtracting the mean from the background pixel value to obtain the background offset.

[0074] It should be noted that the mean is expressed as:

[0075]

[0076] Among them, MEAN(f) represents the mean value of the fth background collected, B (i,j) (f) represents the pixel value of the f-th background (i, j) collected, m represents the length of the image, and n represents the width of the image.

[0077] OFFSET (i,j)(f) = B (i,j) (f)-MEAN(f)

[0078] Among them, OFFSET (i,j) (f) represents the background offset.

[0079] Step S103, analyzing the core temperature data and the background bias according to the least square method to obtain a first functional relationship, and the first functional relationship is used to calculate the fitting bias of each point in the infrared image.

[0080] It should be noted that step S103 includes: analyzing the movement temperature data and the background bias according to the least squares method to obtain a first functional relationship; inputting the current movement temperature into the first functional relationship to obtain a fitting bias of the first point in the infrared image; and calculating the fitting bias of each point in the infrared image according to the fitting bias of the first point.

[0081] For example, according to the core temperature fpa, the offset of each point is fitted by the least square method, and the first point OFFSET of the offset of the previously saved core temperature fpa(f) and the calculated background is read. (1,1) (f) The quadratic equation is used for fitting, that is, y = a*x 2 +b*x+c. Further, the bias sample of the first fitting point can be expressed as:

[0082] BD (1,1) (1) = a*fpa(1) 2 +b*fpa(1)+c

[0083] BD (1,1) (2) = a*fpa(2) 2 +b*fpa(2)+c

[0084] BD (1,1) (3) = a*fpa(3) 2 +b*fpa(3)+c

[0085] Therefore, the bias of the first point of the fit can be expressed as:

[0086] BD (1,1) (f) = a*fpa(f) 2 +b*fpa(f)+c

[0087] Where, f represents the number of samples collected, fpa(f) represents the movement temperature, BD (1,1) (f) represents the bias of the first point of the fit. The sample formula for calculating the square of the difference between the actual bias and the fitted bias is expressed as:

[0088] x(1)=(OFFSET (1,1)(1)-BD (1,1) (1)) 2

[0089] x(2)=(OFFSET (1,1) (2)-BD (1,1) (2) 2

[0090] x(3)=(OFFSET (1,1) (3)-BD (1,1) (3)) 2

[0091] Therefore, the square of the difference between the actual deviation and the fitted deviation can be expressed as:

[0092] x(f)=(OFFSET (1,1) (f)-BD (1,1) (f)) 2

[0093] Furthermore, the minimum value of the sum of the squares of the differences between the actual deviation and the fitted deviation is calculated, and the calculation formula is expressed as:

[0094] S(a,b,c)=min(x(1)+x(2)+x(3)+...+x(f))

[0095] By taking partial derivatives to obtain the corresponding coefficients a, b, and c, we can get the functional relationship between the bias of the first point and the FPA value, and then calculate the fitting bias of the first point according to the FPA value, and then calculate the fitting bias of each point in turn.

[0096] Step S104, subtracting the original image pixel value from the fitting bias to complete the non-uniform correction of the infrared image.

[0097] Exemplarily, the formula for non-uniformity correction can be expressed as:

[0098] nuc(i,j)=src(i,j)-nihe_offset (i,j)

[0099] Among them, nuc(i,j) represents the image after non-uniform correction, src(i,j) represents the original input image without processing, nihe_offset (i,j) Represents the fitting bias, and (i, j) represents the coordinate point of the image.

[0100] In this embodiment, by collecting the background data of the infrared movement and performing mean calculation and offset processing, the fixed pattern noise in the image can be effectively reduced. The relationship between the movement temperature and the background offset is analyzed by the least squares method to obtain the first functional relationship. Through the first functional relationship, the fitting offset of each pixel point can be calculated for the current movement temperature, so as to perform accurate correction. The quality of the infrared image after non-uniform correction is significantly improved, which is not only clearer and more accurate, but also easier to analyze and interpret.

[0101] In one embodiment, based on the above-mentioned second embodiment, step S30 includes analyzing the corresponding relationship data set according to the least squares method to obtain a second functional relationship; inputting the current movement temperature into the second functional relationship to obtain the fitting pixels of the first point in the infrared image; and calculating the fitting pixels of each point in the infrared image based on the fitting pixels of the first point.

[0102] Exemplarily, according to the temperature of the movement, the pixel value of the black body is fitted by the least squares method, and the two satisfy a cubic equation. The sum of the squares of the differences between the actual pixel values ​​collected and the fitted pixels is minimized. The corresponding coefficients are obtained by taking partial derivatives, and thus the fitting function is obtained. The fitted pixels can be obtained by substituting the movement temperature, and the fitted pixels of other black bodies are calculated in turn, and are marked as: ff(t1), ff(t2), ff(t3), ff(t4), ff(t5), and ff(t6).

[0103] In this embodiment, the corresponding relationship data set between the movement temperature and the pixel value of the black body (or other standard object with known temperature) is analyzed by the least square method to obtain the second functional relationship, and a cubic equation (or other high-order polynomial) is used for fitting to capture the complex nonlinear relationship between the movement temperature and the pixel value. The best fitting coefficient is obtained by minimizing the sum of squares of the difference between the actual pixel value and the fitted pixel value and solving the partial derivative to ensure that the fitting function can best describe the data relationship.

[0104] In one embodiment, based on the above embodiment, before the step of fitting the relationship between the black body pixels of q black bodies with different temperatures and the current movement temperature based on the corresponding relationship data set to obtain the fitted pixel values ​​of the q black bodies with different temperatures, the infrared movement can be placed in a high and low temperature box, and six black bodies with different temperatures are placed outside the high and low temperature box. The black body temperatures are set from low to high as: t1, t2, t3, t4, t5, t6. After the black bodies are working stably, their errors are measured and corrected. After the infrared movement is stable in the low temperature environment of the high and low temperature box, the high and low temperature box is heated up, and the pixel values ​​of the six black bodies are collected and saved at the same time, and the temperature of the movement is saved. When saving the black body pixel values, the six black bodies must be included in the image of the infrared movement, and the six black bodies are selected in turn. The pixels in each box are sorted, and the average of the first ten largest pixels is calculated, which is the pixel value of the black body.

[0105] It should be noted that the correction of blackbody temperature usually requires the use of high-precision equipment and instruments to ensure the accuracy and reliability of the measurement results. For example, a high-precision blackbody radiation source is used as a standard source. The blackbody can stably emit radiation energy at a specific temperature. Prepare an infrared thermal imager or other radiation thermometer as a measuring device to ensure that the equipment itself has high precision and stability. Aim the infrared thermal imager at the blackbody radiation source to ensure that the measuring distance and angle meet the equipment requirements. Start the measuring equipment, record the radiation energy of the blackbody radiation source at different temperatures, and compare it with the actual temperature of the blackbody. According to the measurement results, adjust the calibration parameters of the infrared thermal imager to eliminate the measurement error.

[0106] In this embodiment, by placing the infrared movement in a high and low temperature box to simulate the working conditions in different temperature environments, and simultaneously measuring the radiation energy of six external black bodies of different temperatures, the performance of the infrared movement at different temperatures can be accurately reflected. At the same time, a high-precision black body radiation source and an infrared thermal imager are used for calibration to ensure the reliability of the measurement results. By selecting and sorting the top ten largest pixels to calculate the average, random errors and noise interference are reduced. By setting six black bodies of different temperatures to cover a wider temperature range, it is possible to analyze the performance of the infrared movement at different temperatures. This multi-temperature point analysis method helps to have a more comprehensive understanding of the working characteristics and limitations of the infrared movement, and provides a basis for subsequent optimization and improvement.

[0107] Reference Figure 3 , Figure 3 This is a flow chart of the third embodiment of the infrared temperature measurement method without a baffle in the present application. Figure 2 The second embodiment shown provides a third embodiment of the infrared temperature measurement method without a baffle in the present application.

[0108] In the third embodiment, the step S40 includes:

[0109] Step S401, fitting the blackbody temperature and the pixel value according to the Lagrange interpolation method to obtain the weight proportions corresponding to different temperatures.

[0110] It should be noted that the weight ratio indicates the influence of different blackbody temperatures on the difference results.

[0111] Step S402, determining the objective function relationship according to the weight ratio.

[0112] It should be noted that the objective function relationship is determined according to the weight ratio obtained in step S401 (the relationship between the black body temperature and the fitted pixel value obtained according to the Lagrange interpolation method).

[0113] For example, the weights corresponding to different temperatures are w1, w2, w3, w4, w5, and w6, which are specifically expressed as follows:

[0114]

[0115] temp=w1*t1+w2*t2+w3*t3+w4*t4+w5*t5+w6*t6

[0116] Among them, ff(t) represents the pixel value of the object to be tested, ff(t1), ff(t2), ff(t3), ff(t4), ff(t5), and ff(t6) represent the pixel values ​​of the tested black body, t1, t2, t3, t4, t5, and t6 represent the temperatures of the six set black bodies, w1, w2, w3, w4, w5, and w6 represent the weights of the calculated temperatures, which are t1, t2, t3, t4, t5, and t6 respectively, and temp represents the actual measured temperature of the black body.

[0117] In this embodiment, in the Lagrangian interpolation process, each data point (i.e., the pixel value corresponding to each blackbody temperature) contributes to the final interpolation result through its corresponding Lagrangian basis polynomial. The values ​​of these basis polynomials can be regarded as the "weight proportion" of different blackbody temperatures to the difference results, which intuitively reflects the importance of each data point in the fitting process. The determination of the objective function relationship makes it possible to conveniently predict or calculate the corresponding pixel value based on the blackbody temperature in practical applications without having to perform complex interpolation calculations again.

[0118] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the infrared temperature measurement method without a baffle in the present application. More simple transformations based on this technical concept are all within the protection scope of the present application.

[0119] This application also provides an infrared temperature measuring device without a baffle, please refer to Figure 4 , the infrared temperature measuring device without baffle comprises:

[0120] The infrared correction module 10 is used to perform non-uniform correction on the infrared image, wherein the non-uniform correction is used to improve the pixel error generated by the infrared imaging device during the imaging process;

[0121] The data acquisition module 20 is used to control the temperature of the high and low temperature boxes to rise after the non-uniform correction is completed, collect the background of black bodies at different temperatures at different core temperatures, and obtain a corresponding relationship data set of the core temperature, the black body temperature and the black body pixels;

[0122] A pixel fitting module 30 is used to fit the relationship between the black body pixels of q black bodies with different temperatures and the current movement temperature based on the corresponding relationship data set to obtain the fitting pixel values ​​of the q black bodies with different temperatures;

[0123] A function determination module 40 is used to fit the black body temperature and the fitting pixel value according to the Lagrange interpolation method to obtain a target function relationship;

[0124] The target temperature measurement module 50 is used to input the pixel value of the target to be measured into the target function relationship to obtain the target temperature.

[0125] The baffle-free infrared temperature measurement device provided by the present application adopts the baffle-free infrared temperature measurement method in the above-mentioned embodiment, which can solve the technical problem of how to improve the temperature measurement accuracy in the process of baffle-free infrared temperature measurement. Compared with the prior art, the beneficial effects of the baffle-free infrared temperature measurement device provided by the present application are the same as the beneficial effects of the baffle-free infrared temperature measurement method provided by the above-mentioned embodiment, and the other technical features of the baffle-free infrared temperature measurement device are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0126] The present application provides an infrared temperature measurement device without a baffle, and the infrared temperature measurement device without a baffle includes: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the infrared temperature measurement method without a baffle in the above-mentioned embodiment 1.

[0127] Reference below Figure 5 , which shows a schematic diagram of the structure of a non-shielded infrared temperature measuring device suitable for implementing the embodiment of the present application. The non-shielded infrared temperature measuring device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The infrared temperature measuring device without a baffle shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0128] like Figure 5As shown, the infrared temperature measuring device without a baffle may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the infrared temperature measuring device without a baffle are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the infrared temperature measurement device without a baffle to communicate with other devices wirelessly or by wire to exchange data. Although Figure 5 The infrared temperature measurement device without a baffle having various systems is shown, but it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0129] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0130] The infrared temperature measurement device without baffles provided by the present application adopts the infrared temperature measurement method without baffles in the above-mentioned embodiment, which can solve the technical problem of how to improve the temperature measurement accuracy in the process of infrared temperature measurement without baffles. Compared with the prior art, the beneficial effects of the infrared temperature measurement device without baffles provided by the present application are the same as the beneficial effects of the infrared temperature measurement method without baffles provided by the above-mentioned embodiment, and the other technical features of the infrared temperature measurement device without baffles are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0131] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0132] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0133] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the infrared temperature measurement method without a baffle in the above-mentioned embodiment.

[0134] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0135] The computer-readable storage medium may be included in the infrared temperature measuring device without a baffle, or may exist independently without being assembled into the infrared temperature measuring device without a baffle.

[0136] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the infrared temperature measuring device without a baffle, the infrared temperature measuring device without a baffle: performs non-uniform correction on the infrared image, and the non-uniform correction is used to improve the pixel error generated by the infrared imaging device during the imaging process; after the non-uniform correction is completed, the high and low temperature boxes are controlled to heat up, and the background of black bodies at different temperatures are collected at different movement temperatures to obtain a corresponding relationship data set of the movement temperature, the black body temperature and the black body pixels; based on the corresponding relationship data set, the relationship between the black body pixels of q black bodies at different temperatures and the current movement temperature is fitted to obtain the fitted pixel values ​​of the q black bodies at different temperatures; the black body temperature and the fitted pixel value are fitted according to the Lagrange interpolation method to obtain the target function relationship; the pixel value of the target to be measured is input into the target function relationship to obtain the target temperature.

[0137] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0138] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0139] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0140] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned infrared temperature measurement method without a baffle, and can solve the technical problem of how to improve the temperature measurement accuracy in the process of infrared temperature measurement without a baffle. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the infrared temperature measurement method without a baffle provided in the above-mentioned embodiment, and will not be repeated here.

[0141] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned infrared temperature measurement method without a baffle when executed by a processor.

[0142] The computer program product provided by the present application can solve the technical problem of how to improve the temperature measurement accuracy in the process of infrared temperature measurement without a baffle. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the infrared temperature measurement method without a baffle provided by the above embodiment, and will not be repeated here.

[0143] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A baffle-free infrared temperature measurement method, characterized in that: The method includes: Performing non-uniform correction on the infrared image, wherein the non-uniform correction is used to improve the pixel error generated by the infrared imaging device during the imaging process; After the non-uniform correction is completed, the high and low temperature boxes are controlled to heat up, and the background of black bodies at different temperatures are collected at different core temperatures to obtain a corresponding relationship data set of the core temperature, the black body temperature, and the black body pixels; Based on the corresponding relationship data set, fitting the relationship between the black body pixels of q black bodies with different temperatures and the current movement temperature to obtain the fitting pixel values ​​of the q black bodies with different temperatures; Fitting the black body temperature and the fitting pixel value according to the Lagrange interpolation method to obtain an objective function relationship; Inputting the pixel value of the target to be measured into the target function relationship to obtain the target temperature; The step of performing non-uniform correction on the infrared image includes: Collect the background data of the infrared movement by controlling the temperature and time conditions, and save the corresponding movement temperature data; The collected background data is averaged, and the background pixel value minus the average is subtracted to obtain the background offset; Analyzing the core temperature data and the background bias according to the least square method to obtain a first functional relationship, wherein the first functional relationship is used to calculate the fitting bias of each point in the infrared image; The original image pixel value and the fitting bias are subtracted to complete the non-uniform correction of the infrared image.

2. The method according to claim 1, characterized in that The background data collected is averaged, and the background pixel value is subtracted from the average to obtain the background offset. The average is expressed as: Among them, MEAN(f) represents the mean value of the fth background collected, B (i,j) (f) represents the pixel value of the f-th background (i, j) collected, m represents the length of the image, and n represents the width of the image; OFFSET (i,j) (f)=B (i,j) (f)-MEAN(f) Among them, OFFSET (i,j) (f) represents the background offset.

3. The method according to claim 2, characterized in that The step of analyzing the core temperature data and the background bias according to the least square method to obtain a first functional relationship, wherein the first functional relationship is used to calculate the fitting bias of each point in the infrared image, comprises: Analyzing the movement temperature data and the background bias according to the least square method to obtain a first functional relationship; Input the current movement temperature into the first functional relationship to obtain a fitting bias of the first point in the infrared image; The fitting offset of each point in the infrared image is calculated according to the fitting offset of the first point.

4. The method according to claim 1, characterized in that The step of fitting the relationship between the black body pixels of q black bodies with different temperatures and the current movement temperature based on the corresponding relationship data set to obtain the fitting pixel values ​​of the q black bodies with different temperatures comprises: Analyze the corresponding relationship data set according to the least square method to obtain a second functional relationship; Input the current movement temperature into the second functional relationship to obtain a fitting pixel of the first point in the infrared image; The fitting pixels of each point in the infrared image are calculated according to the fitting pixels of the first point.

5. The method according to claim 1, characterized in that The step of fitting the blackbody temperature and the fitting pixel value according to the Lagrange interpolation method to obtain the objective function relationship includes: Fitting the blackbody temperature and the fitted pixel value according to the Lagrange interpolation method to obtain the weight proportions corresponding to different temperatures; The objective function relationship is determined according to the weight ratio.

6. An infrared temperature measuring device without a baffle, characterized in that: The device comprises: An infrared correction module, used to perform non-uniform correction on the infrared image, wherein the non-uniform correction is used to improve the pixel error generated by the infrared imaging device during the imaging process; A data acquisition module, used to control the temperature rise of the high and low temperature boxes after the non-uniform correction is completed, collect the background of black bodies at different temperatures at different core temperatures, and obtain a corresponding relationship data set of core temperature, black body temperature and black body pixels; A pixel fitting module, used for fitting the relationship between the black body pixels of q black bodies with different temperatures and the current movement temperature based on the corresponding relationship data set, to obtain the fitting pixel values ​​of the q black bodies with different temperatures; A function determination module, used for fitting the black body temperature and the fitting pixel value according to the Lagrange interpolation method to obtain a target function relationship; A target temperature measurement module is used to input the pixel value of the target to be measured into the target function relationship to obtain the target temperature; The infrared correction module is also used to collect background data of the infrared movement by controlling temperature and time conditions, and save corresponding movement temperature data; perform mean calculation on the collected background data, and subtract the mean from the background pixel value to obtain background bias; analyze the movement temperature data and the background bias according to the least squares method to obtain a first functional relationship, and the first functional relationship is used to calculate the fitting bias of each point in the infrared image; and perform a difference between the original image pixel value and the fitting bias to complete the non-uniform correction of the infrared image.

7. An infrared temperature measuring device without a baffle, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the infrared temperature measurement method without a baffle according to any one of claims 1 to 5.

8. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the infrared temperature measurement method without a baffle as described in any one of claims 1 to 5 are implemented.

9. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the infrared temperature measurement method without a baffle as claimed in any one of claims 1 to 5 are implemented.

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