Splash screen test method, device, computer equipment, storage medium and program product

Abstract

The application relates to a flash screen test method and device for an infrared detector, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring multiple frames of image data output by the infrared detector in a stable working state; calculating the frame mean value of each frame of image data to obtain a frame mean value sequence; performing linear fitting on the frame mean value sequence by using a least square method to obtain a fitting straight line; calculating the difference between the frame mean value of each frame and the corresponding point value on the fitting straight line to obtain a difference sequence; calculating the standard deviation of the difference sequence; and comparing the standard deviation with a preset judgment threshold to determine whether the infrared detector has a flash screen problem. The method can realize rapid, quantitative and automatic detection of the flash screen phenomenon of the infrared detector, and greatly improves the test efficiency, accuracy and result consistency.

Description

Technical Field

[0001] This invention relates to the field of infrared detector detection technology, and in particular to a flicker test method, apparatus, computer equipment, storage medium and program product. Background Technology

[0002] Infrared detectors are the core component of thermal imaging systems, and their imaging quality directly affects the clarity and stability of the final image. In practical applications, some infrared detectors exhibit screen flickering, where the brightness or grayscale values ​​of the output image flicker or jump non-uniformly and at high frequency. This flickering phenomenon severely interferes with the observer's visual experience and reduces the accuracy of target recognition and tracking.

[0003] Currently, the detection of flickering issues in infrared detectors largely relies on subjective human judgment. Testers observe the image sequence output by the infrared detector over a long period with the naked eye, judging from experience whether there is any unpleasant flickering. The results of this method heavily depend on the experience and subjective feelings of the testers, lack objective and unified quantitative standards, and different testers may have inconsistent judgments. Furthermore, it suffers from problems such as low efficiency and insufficient reliability. Summary of the Invention

[0004] Therefore, it is necessary to provide a flicker test method, device, computer equipment, readable storage medium, and computer program product that can achieve rapid, quantitative, and automated detection of flickering phenomena in infrared detectors, addressing the aforementioned technical problems.

[0005] Firstly, this application provides a method for screen flicker testing, including: Acquire multiple frames of image data output by the infrared detector under test under stable operating conditions; Calculate the frame mean of each frame of image data to obtain a sequence of frame mean values; The frame mean sequence is fitted with a straight line using the least squares method to obtain the fitted straight line. Calculate the difference between the frame mean of each frame and the corresponding point value on the fitted line to obtain the difference sequence, and calculate the standard deviation of the difference sequence; The flashing state of the infrared detector under test is determined based on the standard deviation and the preset judgment threshold.

[0006] Based on the above steps, by extracting the average value of image frames and separating low-frequency interferences such as device temperature drift through least squares fitting, the degree of screen flicker fluctuation is quantified by the standard deviation of the difference sequence, and automated judgment is completed by relying on the threshold. This eliminates subjective human judgment and effectively realizes the quantification and automation of screen flicker detection, thereby improving detection efficiency and accuracy.

[0007] In one embodiment, determining the flicker state of the infrared detector under test based on the standard deviation and a preset judgment threshold includes: If the standard deviation is greater than or equal to the preset judgment threshold, it is determined that the infrared detector under test has a screen flickering problem, and the screen flickering test fails. If the standard deviation is less than the preset judgment threshold, it is determined that the infrared detector under test does not have a screen flickering problem, and the screen flickering test is passed.

[0008] Based on the above steps, this embodiment sets clear binary judgment rules, which are simple and clear in logic, facilitate automated program execution, and ensure uniform testing standards for single-category products.

[0009] In one embodiment, determining the flicker state of the infrared detector under test based on the standard deviation and a preset judgment threshold includes: For the infrared detector under test according to the first standard, the flashing state of the infrared detector under test is determined according to the standard deviation and the first judgment threshold. For the infrared detector under test according to the second standard, the flashing state of the infrared detector under test is determined according to the standard deviation and the second determination threshold; wherein, the first standard is higher than the second standard, and the first determination threshold is lower than the second determination threshold.

[0010] Based on the above steps, this embodiment configures differentiated thresholds for products of different quality levels. Higher-level products use stricter thresholds, while general-purpose products use more lenient thresholds. The solution is more adaptable and can cover the quality inspection requirements of multiple types of infrared detectors.

[0011] In one embodiment, acquiring multi-frame image data output by the infrared detector in a stable operating state includes: When the infrared detector under test is in a constant temperature environment and aligned with a heating unit with a stable temperature, the infrared detector is activated. While the infrared detector under test maintains a stable output state, N frames of image data are continuously acquired through the infrared detector under test; where N is a positive integer greater than 1.

[0012] Based on the above steps, this embodiment uses a constant temperature environment and a stable heating unit to shield against external environmental interference, ensuring that the acquired image data only reflects the detector's own performance, thus guaranteeing the validity of the detection data and the accuracy of the detection results from the source.

[0013] In one embodiment, calculating the frame mean of each frame of image data to obtain a frame mean sequence includes: For the acquired image data from frame 1 to frame N, the arithmetic mean of the gray values ​​of all pixels in the image data is calculated frame by frame to obtain the frame mean value of the corresponding frame number. The frame mean sequence is obtained based on the order of the frame numbers and the average value of each frame.

[0014] Based on the above steps, this embodiment uses the arithmetic mean of the gray values ​​of all pixels to represent the overall brightness of a single frame image, avoiding the interference of local abnormal pixels on the detection results. At the same time, it constructs a sequence by sorting the frame numbers to ensure the integrity of the data time sequence.

[0015] In one embodiment, the step of using the least squares method to perform linear fitting on the frame mean sequence to obtain a fitted line includes: Using frame number as the independent variable With the frame mean sequence as the dependent variable The linear fitting line is obtained by fitting using the least squares method: in, The slope of the fitted line, This is the intercept of the fitted line.

[0016] Based on the above steps, this embodiment uses a linear model to fit the low-frequency change trend of the frame mean, accurately distinguishes between normal slow changes such as detector temperature drift and high-frequency fluctuations caused by screen flicker, effectively removes interference terms, and improves the accuracy of screen flicker feature extraction.

[0017] Secondly, this application also provides a screen flicker testing device, comprising: The acquisition module is used to acquire multiple frames of image data output by the infrared detector under test in a stable working state; The first calculation module is used to calculate the frame mean of each frame of image data to obtain a frame mean sequence. The fitting module is used to perform linear fitting on the frame mean sequence using the least squares method to obtain a fitted straight line. The second calculation module is used to calculate the difference between the frame mean of each frame and the corresponding point value on the fitted line, to obtain a difference sequence, and to calculate the standard deviation of the difference sequence. The determination module is used to determine the flashing state of the infrared detector under test based on the standard deviation and a preset judgment threshold.

[0018] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the screen flickering test method described in the first aspect.

[0019] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the screen flickering test method described in the first aspect.

[0020] Fifthly, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the screen flicker test method described in the first aspect.

[0021] In summary, this application proposes a method, apparatus, computer device, storage medium, and computer program product for testing the flickering phenomenon of infrared detectors. The method includes: acquiring multiple frames of image data output by the infrared detector under stable operating conditions; calculating the frame mean value of each frame of image data to obtain a frame mean value sequence; performing linear fitting on the frame mean value sequence using the least squares method to obtain a fitted line; calculating the difference between the frame mean value of each frame and the corresponding point value on the fitted line to obtain a difference value sequence; calculating the standard deviation of the difference value sequence; and comparing the standard deviation with a preset judgment threshold to determine whether the infrared detector has a flickering problem. This method enables rapid, quantitative, and automated detection of flickering phenomena in infrared detectors, significantly improving testing efficiency, accuracy, and result consistency. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating a screen flicker test method in one embodiment; Figure 2 This is a flowchart illustrating the flicker test method in another embodiment; Figure 3 This is a structural block diagram of a screen flicker test device in one embodiment; Figure 4 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0024] The flicker test method for infrared detectors provided in this application can be applied to scenarios such as infrared detector production testing, factory quality inspection, and performance screening. Through a communication connection between a computer device and the infrared detector, it enables automated acquisition, processing, and flicker determination of the output image data from the infrared detector. The computer device can be, but is not limited to, various industrial control computers, personal computers, laptops, embedded processors, etc., and the infrared detector can be any type of infrared imaging device, such as an uncooled infrared detector or a cooled infrared detector under test.

[0025] In one embodiment, such as Figure 1 As shown, a screen flickering test method is provided. Taking the application of this method to the aforementioned computer device as an example, the method includes the following steps: Step S101: Acquire multiple frames of image data output by the infrared detector under test in a stable working state.

[0026] In this embodiment, multiple frames of continuous image data output by the infrared detector under test are acquired when it is in a stable operating state. Acquiring data only after the detector has warmed up and the image output is stable effectively ensures data stability.

[0027] Step S102: Calculate the frame mean of each frame of image data to obtain a frame mean sequence.

[0028] In this embodiment, for each acquired image, the arithmetic mean of the grayscale values ​​of all pixels in the entire image is calculated. The frame mean values ​​of all frames are then arranged in the order of acquisition to form a frame mean value sequence. This frame mean value sequence can intuitively reflect the overall brightness change trend of the image over time.

[0029] For example, for the first to Nth frames of infrared images, the arithmetic mean of the gray values ​​of all pixels in the image is calculated frame by frame to obtain the frame mean M1, M2, ..., MN of the corresponding frames. These frame mean values ​​are arranged in the order of the frame number to form a frame mean sequence.

[0030] Based on the above steps, the arithmetic mean of all pixels is used to convert the two-dimensional infrared image data of a single frame into one-dimensional frame mean data, which greatly simplifies the subsequent data processing. At the same time, it can completely characterize the overall brightness level of a single frame infrared image, avoid the interference of factors such as local pixel anomalies and bad pixels on the overall screen flicker judgment result, and ensure the accuracy of feature extraction.

[0031] Step S103: Use the least squares method to fit a straight line to the frame mean sequence to obtain the fitted straight line.

[0032] In this embodiment, a linear fit is performed on the frame mean sequence to obtain a fitted straight line. This fitted straight line is used to characterize the low-frequency, slow brightness change trend caused by device temperature drift and slight aging in the flicker-free state of the detector.

[0033] For example, using frame numbers 1 to N as independent variables. The frame mean sequence M1 to MN is used as the dependent variable. By using the least squares method for linear fitting, the functional expression of the fitted line is obtained. ,in, The slope of the fitted line, The intercept of the fitted line is given. This fitted line characterizes the stable change trend of the infrared detector frame mean over time under ideal flicker-free conditions. This trend is mainly caused by low-frequency factors such as temperature drift and device aging of the infrared detector itself.

[0034] Based on the above steps, the low-frequency stable variation trend of the infrared detector frame mean was accurately extracted through linear fitting using the least squares method, providing a baseline for subsequent separation of high-frequency fluctuations caused by screen flicker. Simultaneously, the least squares fitting process effectively offsets the influence of random noise, ensuring the stability and accuracy of the fitted line and avoiding subsequent difference calculation errors caused by baseline deviation.

[0035] Step S104: Calculate the difference between the frame mean of each frame and the corresponding point value on the fitted line to obtain the difference sequence, and calculate the standard deviation of the difference sequence.

[0036] In this embodiment, the difference between the frame mean and the corresponding value of the fitted straight line is calculated frame by frame, and all differences constitute a difference sequence. The standard deviation of the difference sequence is then calculated. This standard deviation is used to quantify the severity of high-frequency fluctuations in image brightness; the larger the standard deviation, the more severe the screen flickering phenomenon.

[0037] For example, for the first frame( From 1 to N), first calculate the function value of the point corresponding to the i-th frame on the fitted line. Then calculate the first Frame average and The difference ,Depend on arrive Arrange the difference sequence in order.

[0038] Based on the above steps, the low-frequency stable change trend in the frame mean value sequence is completely canceled out by the difference calculation. The extracted difference value sequence only contains the high-frequency fluctuation features caused by the screen flickering phenomenon. This achieves effective separation of screen flickering features from low-frequency interference such as device temperature drift, greatly improving the accuracy of subsequent screen flickering judgment and effectively identifying slight screen flickering phenomena that are difficult for the human eye to detect.

[0039] Step S105: Determine the flashing state of the infrared detector under test based on the standard deviation and the preset judgment threshold.

[0040] In this embodiment, a fixed judgment threshold is preset, and the calculated standard deviation is compared with the threshold. If the standard deviation is greater than or equal to the preset judgment threshold, it is determined that the infrared detector under test has a screen flickering problem, and the screen flickering test fails. If the standard deviation is less than the preset judgment threshold, it is determined that the infrared detector under test does not have a screen flickering problem, and the screen flickering test passes.

[0041] This embodiment employs a fixed threshold judgment rule, resulting in a simple process and high operating efficiency. It is suitable for batch testing of infrared detectors of a single product category with unified quality standards. Actual testing has verified that selecting 0.3mV as the baseline judgment threshold can effectively intercept 99.9% of flickering defective products, with extremely low false negative and false positive rates.

[0042] Based on the above steps, this embodiment provides a flicker testing method. Through core technologies such as frame mean calculation, least squares linear fitting, and difference sequence standard deviation calculation, it transforms the subjective visual flicker perception into objective quantitative data, achieving rapid, quantitative, and automated detection of flicker phenomena in infrared detectors. Compared with existing manual detection techniques, this application has significant advantages in terms of objectivity, quantification, high automation efficiency, accuracy, reliability, and consistency. It effectively solves the problems of strong subjectivity, low efficiency, and insufficient reliability in existing technologies, and is fully applicable to batch rapid testing scenarios in large-scale production lines of infrared detectors.

[0043] In one embodiment, determining the flicker state of the infrared detector under test based on the standard deviation and a preset judgment threshold includes: For the infrared detector under test in the first standard, the flashing state of the infrared detector under test is determined according to the standard deviation and the first judgment threshold. For the infrared detector under test according to the second standard, the flashing state of the infrared detector under test is determined according to the standard deviation and the second judgment threshold; wherein, the first standard is higher than the second standard, and the first judgment threshold is less than the second judgment threshold.

[0044] In this embodiment, a graded threshold judgment mode is adopted, configuring different judgment thresholds for detectors of different quality levels. For example, the first standard infrared detector under test corresponds to a high-level precision infrared detector, while the second standard infrared detector under test corresponds to a general-purpose infrared detector. A high-level product threshold of 0.25mV is configured for the first standard infrared detector under test, which has extremely high requirements for image fluctuations. A general-purpose product threshold of 0.35mV is configured for the second standard infrared detector under test, which can tolerate slight brightness fluctuations.

[0045] Based on the above steps, this embodiment can flexibly switch judgment criteria, and one testing system can meet the quality inspection needs of multiple product lines and multiple product specifications, thus expanding the application scope of the solution.

[0046] In one embodiment, acquiring multi-frame image data output by the infrared detector in a stable operating state includes: With the infrared detector under test in a constant temperature environment and aligned with a heating unit with a stable temperature, the infrared detector is activated; while the infrared detector under test maintains a stable output state, N frames of image data are continuously acquired through the infrared detector under test; where N is a positive integer greater than 1.

[0047] In this embodiment, the specific steps of the image acquisition process include: First, the infrared detector under test is placed in a constant-temperature, sealed environment to ensure a constant ambient temperature, and the detector lens is aligned with a heating unit with a stable temperature to ensure that the incident infrared radiation energy remains stable. In one embodiment, the heating unit in this embodiment can be configured as a blackbody radiation source.

[0048] Second, start the infrared detector and wait for the equipment to warm up and the image output to stabilize.

[0049] Third, continuously acquire N frames of image data, where N is a positive integer greater than 1. For example, N can be set to 100 to balance data integrity and acquisition efficiency.

[0050] Based on the above steps, this embodiment can completely isolate external interference such as changes in temperature, light, and radiation by using a constant temperature environment and a stable heating unit, ensuring that fluctuations in the acquired images are caused only by the performance of the detector itself, thus guaranteeing the authenticity and reliability of the detection results from the data source.

[0051] In one embodiment, the frame mean of each frame of image data is calculated to obtain a frame mean sequence, including: For the acquired image data from frame 1 to frame N, calculate the arithmetic mean of the gray values ​​of all pixels in the image data frame by frame to obtain the frame mean value of the corresponding frame number; Based on the order of the frame numbers and the average value of each frame, a sequence of frame average values ​​is obtained.

[0052] In this embodiment, the following operations are performed on the acquired image data from frame 1 to frame N: First, traverse all pixels in the image frame by frame, calculate the arithmetic mean of the gray values ​​of all pixels in a single frame, and obtain the frame mean value corresponding to each frame.

[0053] Second, sort the frame numbers of the acquired images from smallest to largest, arrange the average values ​​of all frames in sequence, and generate a temporally continuous sequence of frame average values.

[0054] Specifically, the calculation of the full-pixel mean can represent the overall brightness of a single frame image, avoiding interference from individual bad pixels or abnormal pixels in the overall judgment. Sorting by frame number can preserve the temporal characteristics of the data and ensure the effectiveness of subsequent fitting and difference calculation.

[0055] In one embodiment, the frame mean sequence is fitted with a straight line using the least squares method to obtain a fitted straight line, including: Using frame number as the independent variable With the frame mean sequence as the dependent variable The linear fitting line is obtained by fitting using the least squares method: in, The slope of the fitted line, This is the intercept of the fitted line.

[0056] In this embodiment, the above-mentioned linear model accurately fits the slow linear change caused by the temperature drift of the detector. After stripping away this part of the low-frequency trend, the remaining difference is the high-frequency random fluctuation caused by the screen flicker, which greatly improves the sensitivity of the screen flicker detection.

[0057] In a more detailed embodiment, such as Figure 2 As shown, the execution steps of the screen flickering test method provided in this embodiment are as follows: First, place the infrared detector under test in a constant-temperature environment and align it with a temperature-stable blackbody radiation source to ensure stable incident radiation energy. Start the infrared detector and, after it has completed preheating and the overall brightness of the output image has stabilized, continuously acquire N frames of infrared image data through the data acquisition interface and transmit them to a computer for further processing. Here, N is a positive integer greater than 1.

[0058] For the first to Nth frames of infrared images, the arithmetic mean of the gray values ​​of all pixels in the image is calculated frame by frame to obtain the frame mean M1, M2, ..., MN of the corresponding frames. These frame mean values ​​are arranged in the order of the frame number to form a frame mean sequence.

[0059] Using frame numbers 1 to N as independent variables The frame mean sequence M1 to MN is used as the dependent variable. By using the least squares method for linear fitting, the functional expression of the fitted line is obtained. ,in, The slope of the fitted line, The intercept of the fitted line is given. This fitted line characterizes the stable change trend of the infrared detector frame mean over time under ideal flicker-free conditions. This trend is mainly caused by low-frequency factors such as temperature drift and device aging of the infrared detector itself.

[0060] For the frame( From 1 to N), first calculate the function value of the point corresponding to the i-th frame on the fitted line. Then calculate the first Frame average and The difference ,Depend on arrive Arrange the difference sequences in order.

[0061] Then, the difference sequence is calculated according to the statistical standard deviation formula. arrive Standard deviation The standard deviation quantifies the degree of fluctuation in the frame mean relative to its stable trend, i.e., the severity of screen flicker. A larger standard deviation indicates more drastic fluctuations in the frame mean and a more severe screen flicker. A smaller standard deviation indicates less drastic fluctuations in the frame mean and a less noticeable screen flicker.

[0062] The preset judgment threshold T is 0.3mV. This threshold is determined based on testing a large number of known high-performance infrared detectors, taking the upper limit of their standard deviation and leaving a certain margin. Actual testing has verified that this threshold can effectively isolate 99.9% of flickering devices.

[0063] Finally, the calculated standard deviation With threshold Comparison: If If so, the infrared detector is determined to have a screen flickering problem and is a defective device; if If the test is passed, the infrared detector is deemed to have no flickering problem and is considered a qualified device.

[0064] In summary, this embodiment provides a flicker testing method. By combining a constant temperature environment with a stable blackbody radiation source, it eliminates interference from external factors such as ambient temperature and changes in incident radiation on the infrared detector output. This ensures that the acquired image data reflects only the output performance characteristics of the infrared detector itself, providing reliable basic data for subsequent flicker determination. Standardized threshold comparisons enable automated and standardized judgment of flicker issues, eliminating the need for subjective human intervention. The entire testing process can be automatically completed by computer equipment, significantly improving testing efficiency and making it fully suitable for rapid batch testing on large-scale production lines. Simultaneously, the unified judgment standard ensures complete consistency in test results across different batches and under different testing environments, avoiding subjective judgment differences among different testers and improving the reliability and consistency of the test results.

[0065] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0066] Based on the same inventive concept, this application also provides a screen flickering test apparatus for implementing the aforementioned screen flickering test method. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations in one or more screen flickering test apparatus embodiments provided below can be found in the limitations of the screen flickering test method described above, and will not be repeated here.

[0067] In one embodiment, such as Figure 3 As shown, a screen flicker testing device is provided, comprising: an acquisition module 310, a first calculation module 320, a fitting module 330, a second calculation module 340, and a determination module 350, wherein: The acquisition module 310 is used to acquire multiple frames of image data output by the infrared detector under test in a stable working state. The first calculation module 320 is used to calculate the frame mean of each frame of image data to obtain a frame mean sequence. The fitting module 330 is used to perform linear fitting on the frame mean sequence using the least squares method to obtain a fitted straight line; The second calculation module 340 is used to calculate the difference between the frame mean of each frame and the corresponding point value on the fitted line, to obtain a difference sequence, and to calculate the standard deviation of the difference sequence. The determination module 350 is used to determine the flashing state of the infrared detector under test based on the standard deviation and the preset judgment threshold.

[0068] In one embodiment, the determining module 350 is further configured to determine that the infrared detector under test has a screen flickering problem and the screen flickering test fails if the standard deviation is greater than or equal to a preset judgment threshold; and to determine that the infrared detector under test does not have a screen flickering problem and the screen flickering test passes if the standard deviation is less than the preset judgment threshold.

[0069] In one embodiment, the determining module 350 is further configured to determine the screen flicker state of the infrared detector under test for a first standard based on the standard deviation and a first determination threshold; and to determine the screen flicker state of the infrared detector under test for a second standard based on the standard deviation and a second determination threshold; wherein the first standard is higher than the second standard, and the first determination threshold is lower than the second determination threshold.

[0070] In one embodiment, the acquisition module 310 is further configured to activate the infrared detector when the infrared detector under test is in a constant temperature environment and is aligned with a heating unit with a stable temperature; and to continuously acquire N frames of image data through the infrared detector under test when the infrared detector under test maintains a stable output state; wherein N is a positive integer greater than 1.

[0071] In one embodiment, the first calculation module 320 is further configured to calculate the arithmetic mean of the gray values ​​of all pixels in the acquired image data from frame 1 to frame N, and obtain the frame mean value of the corresponding frame number; and obtain the frame mean value sequence according to the order of the frame number and each frame mean value.

[0072] Each module in the aforementioned screen flickering test device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0073] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 4 As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When executed by the processor, the computer program implements a screen flicker test method. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0074] Those skilled in the art will understand that Figure 4 The structure shown 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 to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0075] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiment.

[0076] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0077] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the method embodiments described above.

[0078] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0079] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0080] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0081] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for testing screen flickering, characterized in that, The method includes: Acquire multiple frames of image data output by the infrared detector under test under stable operating conditions; Calculate the frame mean of each frame of image data to obtain a sequence of frame mean values; The frame mean sequence is fitted with a straight line using the least squares method to obtain the fitted straight line. Calculate the difference between the frame mean of each frame and the corresponding point value on the fitted line to obtain the difference sequence, and calculate the standard deviation of the difference sequence; The flashing state of the infrared detector under test is determined based on the standard deviation and the preset judgment threshold.

2. The method according to claim 1, characterized in that, The step of determining the flicker state of the infrared detector under test based on the standard deviation and a preset judgment threshold includes: If the standard deviation is greater than or equal to the preset judgment threshold, it is determined that the infrared detector under test has a screen flickering problem, and the screen flickering test fails. If the standard deviation is less than the preset judgment threshold, it is determined that the infrared detector under test does not have a screen flickering problem, and the screen flickering test is passed.

3. The method according to claim 1, characterized in that, The step of determining the flicker state of the infrared detector under test based on the standard deviation and a preset judgment threshold includes: For the infrared detector under test according to the first standard, the flashing state of the infrared detector under test is determined according to the standard deviation and the first judgment threshold. For the infrared detector under test according to the second standard, the flashing state of the infrared detector under test is determined according to the standard deviation and the second determination threshold; wherein, the first standard is higher than the second standard, and the first determination threshold is less than the second determination threshold.

4. The method according to claim 1, characterized in that, The acquisition of multi-frame image data output by the infrared detector under stable operating conditions includes: When the infrared detector under test is in a constant temperature environment and aligned with a heating unit with a stable temperature, the infrared detector is activated. While the infrared detector under test maintains a stable output state, N frames of image data are continuously acquired through the infrared detector under test; where N is a positive integer greater than 1.

5. The method according to claim 4, characterized in that, The calculation of the frame mean value of each frame of image data, resulting in a frame mean value sequence, includes: For the acquired image data from frame 1 to frame N, the arithmetic mean of the gray values ​​of all pixels in the image data is calculated frame by frame to obtain the frame mean value of the corresponding frame number. The frame mean sequence is obtained based on the order of the frame numbers and the average value of each frame.

6. The method according to claim 1, characterized in that, The step of fitting a straight line to the frame mean sequence using the least squares method to obtain a fitted straight line includes: Using frame number as the independent variable With the frame mean sequence as the dependent variable The linear fitting line is obtained by fitting using the least squares method: in, The slope of the fitted line, This is the intercept of the fitted line.

7. A screen flicker testing device, characterized in that, The device includes: The acquisition module is used to acquire multiple frames of image data output by the infrared detector under test in a stable working state; The first calculation module is used to calculate the frame mean of each frame of image data to obtain a frame mean sequence. The fitting module is used to perform linear fitting on the frame mean sequence using the least squares method to obtain a fitted straight line. The second calculation module is used to calculate the difference between the frame mean of each frame and the corresponding point value on the fitted line, to obtain a difference sequence, and to calculate the standard deviation of the difference sequence. The determination module is used to determine the flashing state of the infrared detector under test based on the standard deviation and a preset judgment threshold.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the screen flicker test method according to any one of claims 1 to 6.

9. 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 screen flicker test method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the screen flicker test method as described in any one of claims 1 to 6.

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