Field-of-view testing method, apparatus and system based on infrared imaging system

Abstract

Disclosed in the present application are a field-of-view testing method, apparatus and system based on an infrared imaging system. The method comprises: acquiring an initial response signal when a diaphragm is not provided; providing a diaphragm and adjusting an aperture and a spacing value to obtain a plurality of groups of detection signals; if only a test result for one detection direction needs to be acquired, analyzing to obtain a spatial angle of each group of initial detection parameters; converting the detection signals into two-dimensional grayscale maps, and performing image processing to obtain image pixel parameters; and performing linear fitting on the spatial angles and the image pixel parameters of the plurality of groups of detection signals to obtain a test result of a field of view. The field-of-view test method converts detection signals into two-dimensional grayscale images and performs image processing, and performs linear fitting on spatial angles and image pixel parameters of a plurality of groups of detection signals, which effectively avoids the impact on a test result caused by the non-uniformity of infrared rays irradiated on the central region and the edge of the surface of a black body, thereby improving the reliability of field-of-view tests for infrared imaging systems.

Description

Method, apparatus and system for field-of-view testing based on infrared imaging system

[0001] Cross-reference of related applications

[0002] This application is based on and claims priority to Chinese Patent Application No. 202411903376.3, filed on December 23, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of intelligent testing technology, and in particular to a field-of-view testing method, apparatus and system based on an infrared imaging system. Background Technology

[0004] Existing infrared imaging systems can perform infrared imaging detection within a certain field of view. To ensure the reliability of the infrared imaging system, its field of view can be tested before use. Existing technologies typically involve changing the horizontal and vertical distances between the detector and the blackbody, and calculating the spatial angle of the field of view using formulas. However, existing imaging systems do not consider the non-uniformity of infrared radiation radiated from the central region and edges of the blackbody surface, resulting in poor reliability of the field of view test. Therefore, existing methods for testing the field of view of infrared imaging systems suffer from low reliability.

[0005] Application content

[0006] This application provides a field-of-view testing method, apparatus, and system based on an infrared imaging system, aiming to solve the problem of low testing reliability in existing methods for testing the field of view of infrared imaging systems.

[0007] In a first aspect, embodiments of this application provide a field-of-view testing method based on an infrared imaging system. This method is applied in a data processing terminal. The field-of-view testing system includes a blackbody, an aperture, a lens, and a detector arranged sequentially. The data processing terminal is communicatively connected to the detector. The method includes:

[0008] Acquire the initial response signal detected by the detector when no aperture is set;

[0009] The aperture and spacing of the aperture stop are adjusted according to the initial response signal, and multiple sets of detection signals detected by the detector are acquired simultaneously; the spacing value is the distance between the aperture stop and the detector.

[0010] Determine whether it is only necessary to obtain test results from one detection direction;

[0011] If so, then each set of detection signals and corresponding initial detection parameters are analyzed according to the preset spatial angle analysis rules to obtain the spatial angle corresponding to each set of initial detection parameters; the initial detection parameters include the aperture and spacing values ​​of the aperture.

[0012] Each group of detection signals is converted into a corresponding two-dimensional grayscale image and processed according to a preset image processing algorithm to obtain the image pixel parameters corresponding to each group of detection signals.

[0013] Linear fitting is performed on the spatial angle and image pixel parameters of multiple sets of detection signals to obtain the corresponding field of view test results.

[0014] Secondly, embodiments of this application also provide a field-of-view testing device based on an infrared imaging system. This device is configured in a data processing terminal. The field-of-view testing system includes a blackbody, an aperture, a lens, and a detector arranged sequentially. The data processing terminal is communicatively connected to the detector. The device is used to execute the field-of-view testing method based on an infrared imaging system as described in the first aspect above. The device includes:

[0015] An initial response signal acquisition unit is used to acquire the initial response signal detected by the detector when no aperture is set.

[0016] The detection signal acquisition unit is used to adjust the aperture and spacing value of the aperture according to the initial response signal, and simultaneously acquire multiple sets of detection signals detected by the detector; the spacing value is the distance between the aperture and the detector.

[0017] The judgment unit is used to determine whether it is only necessary to obtain the test result of one detection direction;

[0018] A spatial angle resolution unit is used to, if so, resolve each set of detection signals and corresponding initial detection parameters according to a preset spatial angle resolution rule to obtain the spatial angle corresponding to each set of initial detection parameters; the initial detection parameters include the aperture and spacing values ​​of the aperture.

[0019] The image pixel parameter acquisition unit is used to convert each group of detection signals into corresponding two-dimensional grayscale images and perform image processing according to a preset image processing algorithm to obtain the image pixel parameters corresponding to each group of detection signals.

[0020] The test result acquisition unit is used to perform linear fitting on the spatial angle and image pixel parameters of multiple sets of detection signals to obtain the corresponding field of view test results.

[0021] Thirdly, embodiments of this application also provide a field-of-view testing system based on an infrared imaging system, wherein the system includes a data processing terminal, a blackbody, an aperture, a lens, and a detector.

[0022] The blackbody, aperture, lens and detector are all arranged sequentially on the guide rail by mounting brackets, and the guide rail is equipped with a scale for measuring distance values;

[0023] The data processing terminal is communicatively connected to the detector. The data processing terminal includes a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other through the communication bus.

[0024] Memory, used to store computer programs;

[0025] When the processor executes the computer program stored in the memory, it implements the steps of the field-of-view testing method based on the infrared imaging system as described in the first aspect above.

[0026] Fourthly, embodiments of this application also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the field-of-view testing method based on an infrared imaging system as described in the first aspect above.

[0027] This application provides a field-of-view testing method, apparatus, and system based on an infrared imaging system. The method includes: acquiring the initial response signal without an aperture; setting the aperture and adjusting the aperture distance and spacing values ​​to obtain multiple sets of detection signals; if only the test result for one detection direction is needed, analyzing the spatial angles of each set of initial detection parameters; converting the detection signals into two-dimensional grayscale images and performing image processing to obtain image pixel parameters; and linearly fitting the spatial angles of the multiple sets of detection signals and the image pixel parameters to obtain the field-of-view test result. The above-described field-of-view testing method, by converting the detection signals into two-dimensional grayscale images and performing image processing, and by linearly fitting the spatial angles of the multiple sets of detection signals and the image pixel parameters, can effectively avoid the influence of the non-uniformity of infrared radiation radiated from the central region and edge of the blackbody surface on the test results, thus improving the reliability of field-of-view testing of the infrared imaging system. Attached Figure Description

[0028] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 is a flowchart of the field-of-view testing method based on an infrared imaging system provided in an embodiment of this application;

[0030] Figure 2 is a structural diagram of the field-of-view testing system based on an infrared imaging system provided in an embodiment of this application;

[0031] Figure 3 is an application effect diagram of the field-of-view testing method based on an infrared imaging system provided in the embodiments of this application;

[0032] Figure 4 shows another application effect of the field-of-view testing method based on an infrared imaging system provided in the embodiments of this application;

[0033] Figure 5 shows another application effect of the field-of-view testing method based on an infrared imaging system provided in the embodiments of this application;

[0034] Figure 6 is a schematic block diagram of a field-of-view testing device based on an infrared imaging system provided in an embodiment of this application;

[0035] Figure 7 is a schematic block diagram of a computer device provided in an embodiment of this application. Detailed Implementation

[0036] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0037] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0038] It should also be understood that the terminology used in this application specification is for the purpose of describing particular embodiments only and is not intended to limit the application. As used in this application specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0039] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0040] Please refer to Figure 1. As shown in the figure, an embodiment of this application provides a field-of-view testing method based on an infrared imaging system. This method is applied in a data processing terminal and is executed by an application installed in the data processing terminal. The data processing terminal can be a laptop, desktop computer, tablet computer, or mobile phone, etc. The data processing terminal can also be a control board that realizes data processing and command information transmission and reception, such as a PLC (Programmable Logic Controller) circuit board carrying an MCU chip. As shown in Figure 2, the field-of-view testing system also includes a blackbody 11, an aperture 12, a lens 13, and a detector 14 arranged in sequence. The data processing terminal 20 is communicatively connected to the detector 14. The lens 13 and the detector 14 are packaged into a detection module 10 for infrared radiation detection. The blackbody 11 serves as an infrared radiation source and adopts a blackbody with a planar structure of a certain size. The aperture 12 has a through hole, and the aperture diameter can be adjusted by rotating a knob or by sending an adjustment command from the data processing terminal 20 to an automated control device to adjust the aperture diameter. As shown in Figure 1, the method includes steps S110 to S160.

[0041] S110. Obtain the initial response signal detected by the detector when no aperture is set.

[0042] Without setting an aperture, adjust the distance between the detector and the blackbody so that the central region of the blackbody (approximately 75% of its diameter) fills the detector's field of view. The initial response signal is obtained by collecting the response data from the detector's sensing of infrared radiation. The initial response signal includes the response signal intensity at the horizontal edge and the response signal intensity at the vertical edge. If only the test results for one detection direction are needed, the response signal intensity at either the horizontal or vertical edge can be recorded as V0. If only the test results for two detection directions are needed simultaneously, the response signal intensity V at the horizontal edge can be recorded separately. h0 Response signal intensity V at the vertical edge v0 .

[0043] S120. Adjust the aperture and spacing value of the aperture according to the initial response signal, and simultaneously acquire multiple sets of detection signals detected by the detector; the spacing value is the distance between the aperture and the detector.

[0044] Furthermore, as shown in Figure 3, an aperture is added between the blackbody and the detector module. The aperture is moved horizontally, resulting in a distance L1 between the aperture and the detector in the detector module. The aperture is adjusted so that the image edge pixel response signal in the currently obtained detection signal is V0 / 2 (assuming only one detection direction test result is needed; if two detection directions test results are needed simultaneously, two tests must be performed separately and the result obtained must be V0 / 2). h0 / 2 and V v0 (The two sets of detection signals and two sets of initial detection parameters corresponding to / 2), the aperture of the measuring aperture is denoted as D1. Record the obtained detection signals and the corresponding set of initial detection parameters to complete one field of view detection.

[0045] Further movement ensures the distance between the aperture and the detector in the detection module is L2. Simultaneously, the aperture is adjusted so that the image edge pixel response signal in the currently obtained detection signal is V0 / 2. The aperture of the measured aperture is recorded as D2. The aperture is moved again and the aperture is adjusted, repeating the above steps to perform one field-of-view detection and recording the distance value L3 and the aperture D3; as shown in Figure 3. In other embodiments, more field-of-view detections can be performed, obtaining more than three sets of detection signals and initial detection parameters.

[0046] S130. Determine whether it is only necessary to obtain the test results for one detection direction.

[0047] Furthermore, it can be determined whether only the test results of one detection direction are needed; if so, the corresponding field test results can be obtained by directly taking the response signal intensity of the horizontal edge or the response signal intensity of the vertical edge in the above initial response signal (and detection signal) once.

[0048] In a more specific embodiment, after step S130, the following steps are further included: if not, the horizontal and vertical detection values ​​and corresponding initial detection parameters contained in each group of detection signals are analyzed according to a preset spatial angle analysis rule to obtain the horizontal and vertical spatial angles corresponding to each group of initial detection parameters; each group of detection signals is converted into a corresponding two-dimensional grayscale image and image processing is performed according to a preset image processing algorithm to obtain the image horizontal pixel parameters and image vertical pixel parameters corresponding to each group of detection signals; the horizontal spatial angles and image horizontal pixel parameters of multiple groups of detection signals are linearly fitted to obtain the corresponding horizontal field of view test results; the vertical spatial angles and image vertical pixel parameters of multiple groups of detection signals are linearly fitted to obtain the corresponding vertical field of view test results; the horizontal field of view test results and the vertical field of view test results are combined to form the corresponding field of view test results.

[0049] If test results from two detection directions are required, the response signal intensity at the horizontal edge and the response signal intensity at the vertical edge in the initial response signal (and detection signal) should be taken separately for field of view testing. The combined test results from the horizontal and vertical directions should be used as the final field of view test result.

[0050] The process of testing the response signal intensity at the horizontal edge and the response signal intensity at the vertical edge is the same as the process of testing one set of response signal intensities, except that the test values ​​are changed (V0 is replaced with V). h0 / 2 or V v0 / 2) Changes occur. The following explanation will elaborate on the process of testing the strength of a set of response signals.

[0051] S140. If so, then each group of detection signals and the corresponding initial detection parameters are analyzed according to the preset spatial angle analysis rules to obtain the spatial angle corresponding to each group of initial detection parameters; the initial detection parameters include the aperture and spacing values ​​of the aperture.

[0052] According to the pre-set spatial angle analysis rules, each set of detection signals and the initial detection parameters corresponding to each set of detection signals are analyzed separately. Since each set of detection signals corresponds to a set of initial detection parameters, the two sets of data can be analyzed together to obtain the spatial angles corresponding to each set of initial detection parameters. The number of spatial angles obtained is equal to the number of initial detection parameters.

[0053] In a more specific embodiment, step S140 specifically includes the following sub-steps: inputting the initial detection parameters of each group of detection signals into the analytical formula in the spatial angle analysis rule to obtain the spatial angle corresponding to each group of initial detection parameters.

[0054] Specifically, the initial detection parameters of each group of detection signals can be input into the analytical formula, which can be expressed by formula (1):

[0055] Where n is the number of initial detection parameter sets, i.e., n = 1, 2, 3...; θ n For the nth set of spatial angles obtained from analysis, D n Let L be the aperture in the nth set of initial detection parameters. n The spacing value is the initial detection parameter of the nth group.

[0056] S150. Convert each group of detection signals into a corresponding two-dimensional grayscale image and perform image processing according to a preset image processing algorithm to obtain the image pixel parameters corresponding to each group of detection signals.

[0057] Furthermore, each set of detection signals is converted into a corresponding two-dimensional grayscale image. The detection signal contains detection intensity values ​​corresponding to multiple pixels, and different detection intensity values ​​can be converted into different grayscale colors. The larger the detection intensity value, the darker the grayscale color; the smaller the detection intensity value, the lighter the grayscale color. The resulting two-dimensional grayscale image is shown in Figure 4. Based on the above detection signal acquisition process, the center of the obtained two-dimensional grayscale image is a circular high-temperature region, indicating that the blackbody radiates infrared light to the detector, while the apex of the image is a low-temperature region, indicating that the blackbody radiation is blocked by the aperture. The obtained two-dimensional grayscale image is processed according to a pre-set image processing algorithm to obtain the corresponding image pixel parameters. Thus, each set of detection signals can correspond to a set of image pixel parameters.

[0058] In a more specific embodiment, step S150 specifically includes the following sub-steps: calculating the gradient value of each pixel in the two-dimensional grayscale image and obtaining the maximum gradient value; filtering the pixels in the two-dimensional grayscale image according to the judgment ratio configured in the image processing algorithm and the maximum gradient value to obtain effective pixels; and solving the evaluation function in the image processing algorithm to obtain the center coordinates and radius of the circle corresponding to the gradient value of the effective pixels as the image pixel parameters.

[0059] Specifically, each pixel in a two-dimensional grayscale image corresponds to a coordinate value and a grayscale value. The gradient value of each pixel can be calculated as shown in formula (2):

[0060] Slope x Slope is the gradient component of a pixel with coordinates (x, y) in the horizontal direction. y Let be the gradient component of the pixel with coordinates (x, y) in the vertical direction. Based on the above calculation formula, the gradient value of each pixel can be obtained, and the maximum gradient value in each two-dimensional grayscale image can be obtained, which is Max(Grad). The image composed of the gradient values ​​of each pixel is shown in Figure 5 (where dark colors represent small gradients and light colors represent large gradients).

[0061] The pixels in the two-dimensional grayscale image are further filtered according to the judgment ratio configured in the image processing algorithm. Specifically, based on the judgment ratio T and the maximum gradient value of the two-dimensional grayscale image, the filtering threshold T×Max(Grad) can be calculated. It is then determined whether the gradient value of each pixel in the two-dimensional grayscale image is not less than the filtering threshold. If it is not less than the filtering threshold, the pixel is retained; if it is less than the filtering threshold, the pixel is removed. Finally, the retained pixels are obtained as valid pixels.

[0062] Furthermore, by solving the evaluation function in the image processing algorithm, the image pixel parameters corresponding to each two-dimensional grayscale image can be obtained. The evaluation function can be expressed by formula (3):

[0063] It can be proven that this evaluation function has a unique minimum value, where (x0, y0) is the center point of the circle in the two-dimensional grayscale image at the point of minimum value, and R is the pixel radius in pixels; (x i y i The coordinates of the i-th pixel among the effective pixels are given. Based on the evaluation function described above, the pixel radius R and center coordinates (x0, y0) of each two-dimensional grayscale image can be obtained sequentially as the corresponding image pixel parameters. Each set of detection signals can then be used to calculate a set of image pixel parameters, where the center coordinates (x0, y0) are the same across all sets, only the pixel radius R varies. For example, for the three sets of detection signals mentioned above, the radius R1 corresponding to L1 and D1 can be obtained; based on the same principle, the radius R2 corresponding to L2 and D2, and the radius R3 corresponding to L3 and D3 can be obtained.

[0064] S160. Perform linear fitting on the spatial angle and image pixel parameters of the multiple sets of detection signals to obtain the corresponding field of view test results.

[0065] There is a certain linear correlation between the spatial angle of different detection signals and the image pixel parameters. The spatial angle and image pixel parameters of multiple sets of detection signals can be linearly fitted to obtain the corresponding field of view test results.

[0066] In a more specific embodiment, step S160 specifically includes the following sub-steps: performing linear fitting on the spatial angle and the radius in the image pixel parameters to obtain the corresponding fitting parameters; generating a fitting function corresponding to the field of view angle and the number of array pixels based on the fitting parameters as the corresponding field of view test result.

[0067] Specifically, the radius and spatial angle in the image pixel parameters corresponding to the same set of detection signals can be linearly fitted. The specific fitting process can be represented by formula (4): θ nn =k×R nn +b (4);

[0068] Where, θ n R is the spatial angle corresponding to the nth group of detection signals. n Let be the radius in the image pixel parameters of the nth group of detection signals, and k and b be fitting parameters. The fitting parameters can be determined by fitting the radius and spatial angle of at least three groups of detection signals.

[0069] Obviously, when 2R equals the number of array pixels N, the field of view test conditions are met. Therefore, the corresponding fitting function can be generated as the field of view test result based on the fitting parameters. The obtained fitting function can be expressed by formula (5):

[0070] Where k and b are known values, N is the number of array pixels of the detector, and FOV is the field of view angle.

[0071] In the example above, the number of pixels in the horizontal and vertical directions of the detector is the same, so the test result in one direction can be used as the module's index. If the number of pixels in the horizontal and vertical directions is different, it is necessary to measure the horizontal field of view (HFOV) and the vertical field of view (VFOV) separately, and the measurement process is the same as described above. When performing R-θ linear fitting, the coefficients in the horizontal and vertical directions may differ, and the final result should use the number of pixels N in the horizontal direction. H and the number of pixels in the vertical direction N V Calculate them separately. Then, the horizontal test results corresponding to the horizontal field of view (HFOV) and the vertical test results corresponding to the vertical field of view (VFOV) can be obtained. By combining the horizontal and vertical test results, the corresponding field of view test results can be obtained. The specific field of view test results are shown in formula (6).

[0072] The field-of-view testing method based on an infrared imaging system disclosed in the above embodiments includes: acquiring the initial response signal without an aperture; setting an aperture and adjusting the aperture distance and spacing values ​​to obtain multiple sets of detection signals; if only the test result of one detection direction needs to be obtained, then analyzing the spatial angles of each set of initial detection parameters; converting the detection signals into two-dimensional grayscale images and performing image processing to obtain image pixel parameters; and performing linear fitting on the spatial angles and image pixel parameters of multiple sets of detection signals to obtain the field-of-view test result. This field-of-view testing method, by converting the detection signals into two-dimensional grayscale images and performing image processing, and by performing linear fitting on the spatial angles and image pixel parameters of multiple sets of detection signals, can effectively avoid the influence of the non-uniformity of infrared radiation radiated from the central region and edge of the blackbody surface on the test results, thus improving the reliability of field-of-view testing of the infrared imaging system.

[0073] This application also provides a field-of-view testing device based on an infrared imaging system. This device can be configured in a data processing terminal, which is communicatively connected to the detector. The field-of-view testing device is used to execute any of the aforementioned embodiments of the field-of-view testing method based on an infrared imaging system. Specifically, please refer to Figure 6, which is a schematic block diagram of the field-of-view testing device based on an infrared imaging system provided in this application embodiment.

[0074] As shown in Figure 6, the field-of-view testing device 100 based on the infrared imaging system includes an initial response signal acquisition unit 110, a detection signal acquisition unit 120, a judgment unit 130, a spatial angle resolution unit 140, an image pixel parameter acquisition unit 150, and a test result acquisition unit 160.

[0075] The initial response signal acquisition unit 110 is used to acquire the initial response signal detected by the detector when no aperture is set.

[0076] The detection signal acquisition unit 120 is used to adjust the aperture and spacing value of the aperture according to the initial response signal, and simultaneously acquire multiple sets of detection signals detected by the detector; the spacing value is the distance between the aperture and the detector.

[0077] The judgment unit 130 is used to determine whether it is only necessary to obtain the test result of one detection direction.

[0078] The spatial angle resolution unit 140 is used to, if so, resolve each set of detection signals and corresponding initial detection parameters according to the preset spatial angle resolution rules to obtain the spatial angle corresponding to each set of initial detection parameters; the initial detection parameters include the aperture and spacing values ​​of the aperture.

[0079] The image pixel parameter acquisition unit 150 is used to convert each group of detection signals into corresponding two-dimensional grayscale images and perform image processing according to a preset image processing algorithm to obtain the image pixel parameters corresponding to each group of detection signals.

[0080] The test result acquisition unit 160 is used to perform linear fitting on the spatial angle and image pixel parameters of multiple sets of detection signals to obtain the corresponding field of view test results.

[0081] The field-of-view testing device based on an infrared imaging system provided in this application uses the aforementioned field-of-view testing method based on an infrared imaging system. It acquires the initial response signal without an aperture stop, sets an aperture stop, and adjusts the aperture distance and spacing to obtain multiple sets of detection signals. If only the test result for one detection direction is needed, the spatial angles of each set of initial detection parameters are analyzed. The detection signals are converted into two-dimensional grayscale images and image processing is performed to obtain image pixel parameters. Linear fitting is then performed on the spatial angles of multiple sets of detection signals and the image pixel parameters to obtain the field-of-view test result. This field-of-view testing method, by converting the detection signals into two-dimensional grayscale images and performing image processing, and by linearly fitting the spatial angles of multiple sets of detection signals and the image pixel parameters, effectively avoids the influence of the non-uniformity of infrared radiation radiated from the central region and edges of the blackbody surface on the test results, thus improving the reliability of field-of-view testing of the infrared imaging system.

[0082] This application embodiment also provides a field-of-view testing system based on an infrared imaging system, as shown in Figures 2 and 3. The system includes a data processing terminal 20, a blackbody 11, an aperture 12, a lens 13, and a detector 14. The blackbody 11, aperture 12, lens 13, and detector 14 are all sequentially arranged on a guide rail 15 via mounting brackets. The guide rail 15 is equipped with a scale for measuring distance values. The data processing terminal 20 is communicatively connected to the detector 14. The lens 13 and the detector 14 are packaged into a detection module 10 for infrared radiation detection. More specifically, the detector 14 is an infrared thermopile detection array. The aperture 12 is rotatably connected to the end of a lead screw, and the rotation of the lead screw drives the aperture to translate along the guide rail.

[0083] Among them, the detector 14 can be set as a 32×32 infrared thermopile detection array, then the array pixels in the detector 14 are 32×32.

[0084] The field-of-view testing device based on the infrared imaging system described above can be implemented as a computer program, which can run on the computer device shown in Figure 7.

[0085] Please refer to Figure 7, which is a schematic block diagram of a computer device provided in an embodiment of this application. This computer device can be a data processing terminal used to perform a field-of-view testing method based on an infrared imaging system for field-of-view testing.

[0086] Referring to Figure 7, the computer device 500 includes a processor 502, a memory, and a communication interface 505 connected via a communication bus 501. The memory may include a storage medium 503 and internal memory 504.

[0087] The storage medium 503 may store an operating system 5031 and a computer program 5032. When the computer program 5032 is executed, it causes the processor 502 to execute a field-of-view testing method based on an infrared imaging system. The storage medium 503 may be a volatile storage medium or a non-volatile storage medium.

[0088] The processor 502 provides computing and control capabilities to support the operation of the entire computer device 500.

[0089] The internal memory 504 provides an environment for the operation of the computer program 5032 in the storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a field-of-view testing method based on an infrared imaging system.

[0090] The communication interface 505 is used for network communication, such as providing data information transmission. Those skilled in the art will understand that the structure shown in FIG7 is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 500 to which the present application is applied. A specific computer device 500 may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0091] The processor 502 is used to run the computer program 5032 stored in the memory to implement the corresponding functions in the above-mentioned field-of-view testing method based on the infrared imaging system.

[0092] Those skilled in the art will understand that the embodiments of the computer device shown in FIG7 do not constitute a limitation on the specific configuration of the computer device. In other embodiments, the computer device may include more or fewer components than shown, or combine certain components, or have different component arrangements. For example, in some embodiments, the computer device may include only a memory and a processor. In such embodiments, the structure and function of the memory and processor are consistent with those shown in FIG7, and will not be repeated here.

[0093] It should be understood that, in the embodiments of this application, the processor 502 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0094] In another embodiment of this application, a computer-readable storage medium is provided. This computer-readable storage medium may be volatile or non-volatile. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps included in the above-described field-of-view testing method based on an infrared imaging system.

[0095] Those skilled in the art will readily understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0096] In the several embodiments provided in this application, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Units with the same function may be grouped into one unit. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, or it may be an electrical, mechanical, or other form of connection.

[0097] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of this application, depending on actual needs.

[0098] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0099] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a computer-readable storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned computer-readable storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks.

[0100] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A field-of-view testing method based on an infrared imaging system, characterized in that, The method is applied in a data processing terminal. The field-of-view testing system includes a blackbody, an aperture, a lens, and a detector arranged sequentially. The data processing terminal is communicatively connected to the detector. The method includes: Acquire the initial response signal detected by the detector when no aperture is set; The aperture and spacing of the aperture stop are adjusted according to the initial response signal, and multiple sets of detection signals detected by the detector are acquired simultaneously; the spacing value is the distance between the aperture stop and the detector. Determine whether it is only necessary to obtain test results from one detection direction; If so, then each set of detection signals and corresponding initial detection parameters are analyzed according to the preset spatial angle analysis rules to obtain the spatial angle corresponding to each set of initial detection parameters; the initial detection parameters include the aperture and spacing values ​​of the aperture. Each group of detection signals is converted into a corresponding two-dimensional grayscale image and processed according to a preset image processing algorithm to obtain the image pixel parameters corresponding to each group of detection signals. Linear fitting is performed on the spatial angle and image pixel parameters of multiple sets of detection signals to obtain the corresponding field of view test results.

2. The field-of-view testing method based on an infrared imaging system according to claim 1, characterized in that, The step involves analyzing each set of detection signals and their corresponding initial detection parameters according to a preset spatial angle analysis rule to obtain the spatial angle corresponding to each set of initial detection parameters, including: The initial detection parameters of each group of detection signals are input into the analytical formula in the spatial angle analysis rule to obtain the spatial angle corresponding to each group of initial detection parameters.

3. The field-of-view testing method based on an infrared imaging system according to claim 1, characterized in that, The step of converting each group of detection signals into a corresponding two-dimensional grayscale image and performing image processing according to a preset image processing algorithm to obtain the image pixel parameters corresponding to each group of detection signals includes: Calculate the gradient value of each pixel in the two-dimensional grayscale image and obtain the maximum gradient value; The effective pixels are obtained by filtering the pixels in the two-dimensional grayscale image according to the judgment ratio configured in the image processing algorithm and the maximum gradient value. The center coordinates and radius of the circle corresponding to the gradient value of the effective pixel are obtained by solving the evaluation function in the image processing algorithm and used as the image pixel parameters.

4. The field-of-view testing method based on an infrared imaging system according to claim 1, characterized in that, The linear fitting of the spatial angle and image pixel parameters of multiple sets of detection signals to obtain the corresponding field-of-view test results includes: Linear fitting is performed on the spatial angle and the radius in the image pixel parameters to obtain the corresponding fitting parameters; Based on the fitting parameters, a fitting function corresponding to the field of view angle and the number of array pixels is generated as the corresponding field of view test result.

5. The field-of-view testing method based on an infrared imaging system according to any one of claims 1-4, characterized in that, After determining whether it is only necessary to obtain the test result of one detection direction, the process also includes: If not, then according to the preset spatial angle analysis rules, the horizontal and vertical detection values ​​and the corresponding initial detection parameters contained in each group of detection signals are analyzed to obtain the horizontal and vertical spatial angles corresponding to each group of initial detection parameters. Each group of detection signals is converted into a corresponding two-dimensional grayscale image and processed according to a preset image processing algorithm to obtain the horizontal and vertical pixel parameters of the image corresponding to each group of detection signals. Linear fitting is performed on the horizontal spatial angle and horizontal pixel parameters of the image of the multiple sets of detection signals to obtain the corresponding horizontal field of view test results. Linear fitting is performed on the vertical spatial angle and vertical pixel parameters of the image of multiple sets of detection signals to obtain the corresponding vertical field of view test results; The horizontal and vertical test results of the field of view are combined to form the corresponding field of view test result.

6. A field-of-view testing device based on an infrared imaging system, characterized in that, The device is configured in a data processing terminal. The field-of-view testing system includes a blackbody, an aperture, a lens, and a detector arranged sequentially. The data processing terminal is communicatively connected to the detector. The field-of-view testing device based on the infrared imaging system is used to execute the field-of-view testing method based on the infrared imaging system as described in any one of claims 1-5. The device includes: An initial response signal acquisition unit is used to acquire the initial response signal detected by the detector when no aperture is set. The detection signal acquisition unit is used to adjust the aperture and spacing value of the aperture according to the initial response signal, and simultaneously acquire multiple sets of detection signals detected by the detector; the spacing value is the distance between the aperture and the detector. The judgment unit is used to determine whether it is only necessary to obtain the test result of one detection direction; A spatial angle resolution unit is used to, if so, resolve each set of detection signals and corresponding initial detection parameters according to a preset spatial angle resolution rule to obtain the spatial angle corresponding to each set of initial detection parameters; the initial detection parameters include the aperture and spacing values ​​of the aperture. The image pixel parameter acquisition unit is used to convert each group of detection signals into corresponding two-dimensional grayscale images and perform image processing according to a preset image processing algorithm to obtain the image pixel parameters corresponding to each group of detection signals. The test result acquisition unit is used to perform linear fitting on the spatial angle and image pixel parameters of multiple sets of detection signals to obtain the corresponding field of view test results.

7. A field-of-view testing system based on an infrared imaging system, characterized in that, The system includes a data processing terminal, a blackbody, an aperture, a lens, and a detector. The blackbody, aperture, lens and detector are all arranged sequentially on the guide rail by mounting brackets, and the guide rail is equipped with a scale for measuring distance values; The data processing terminal is communicatively connected to the detector. The data processing terminal includes a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other through the communication bus. Memory, used to store computer programs; When the processor executes the computer program stored in the memory, it implements the steps of the field-of-view testing method based on an infrared imaging system as described in any one of claims 1 to 5.

8. The field-of-view testing system based on an infrared imaging system according to claim 7, characterized in that, The detector is an infrared thermopile detection array.

9. The field-of-view testing system based on an infrared imaging system according to claim 7 or 8, characterized in that, The aperture is rotatably connected to the end of the lead screw, and the lead screw rotates to drive the aperture to translate along the guide rail.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the field-of-view testing method based on an infrared imaging system as described in any one of claims 1-5.

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