Backlight detection method and system, electronic equipment and storage medium

Abstract

The invention relates to a backlight detection method and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining a preset backlight execution parameter, and generating a backlight control instruction based on the backlight execution parameter; receiving a backlight control instruction, and performing differential control on the plurality of backlight areas divided by the backlight execution unit according to the backlight control instruction; and collecting a light-emitting effect picture of the backlight area, performing feature extraction and anomaly recognition on the light-emitting effect picture through a visual analysis algorithm, and outputting an anomaly detection result of the corresponding light-emitting element in each backlight area. By automatically controlling the on-off state of the backlight subareas and the brightness of the lamp beads and combining a visual identification algorithm to analyze the working state of the backlight light-emitting element in real time, efficient and accurate detection of the backlight light-emitting element is realized; the manual participation degree is effectively reduced, and the efficiency and accuracy of backlight detection are remarkably improved.

Description

Technical Field

[0001] This application relates to the field of display testing technology, and in particular to a backlight testing method, system, electronic device and storage medium. Background Technology

[0002] In the field of backlight testing, the industry generally adopts manual visual inspection, which involves lighting up the backlight beads row by row or column by column and observing their on / off state and brightness performance manually.

[0003] However, this manual inspection method is inefficient, with each inspection taking at least 10 to 45 seconds, which severely restricts the production cycle of the production line. Furthermore, long-term visual inspection in a strong light environment can easily cause visual fatigue and eye damage. More importantly, current manual inspection can only determine whether the LED beads are lit, and cannot accurately identify subtle defects such as differences in brightness, dimness, or dark spots, resulting in a high rate of missed inspections, which in turn affects the consistency and reliability of product quality.

[0004] Therefore, there is an urgent need to develop a backlight detection method, system, electronic device, and storage medium to solve one or more of the aforementioned problems. Summary of the Invention

[0005] In view of this, to solve the above-mentioned technical problems or some of the technical problems, embodiments of this application provide a backlight detection method, system, electronic device and storage medium. The method adopts automated detection technology to accurately adjust the on / off state of the backlight zone and the brightness level of each LED. At the same time, it combines a high-precision visual recognition algorithm to perform real-time dynamic monitoring and intelligent analysis of the working status of the backlight light-emitting element, thereby realizing efficient and accurate detection and evaluation of the working performance of the backlight light-emitting element. It greatly reduces the need for manual operation, significantly improves the overall efficiency and accuracy of the backlight detection process, and provides reliable technical support for product quality control.

[0006] In a first aspect, this application provides a backlight detection method, the method comprising: Obtain preset backlight execution parameters, and generate backlight control commands based on the backlight execution parameters; The backlight control command is received, and the backlight execution unit is divided into multiple backlight areas for differentiated control according to the backlight control command. The backlight area includes a number of light-emitting elements arranged in a preset array. The backlight effect image of the backlight area is collected, and the feature extraction and anomaly identification of the backlight effect image are performed by a visual analysis algorithm. The anomaly detection results of the corresponding light-emitting elements in each backlight area are output.

[0007] In one possible implementation, the backlight execution parameters include at least zone emission rule parameters, brightness control parameters, and model matching parameters; The generation of backlight control commands based on the backlight execution parameters includes: Based on the partitioned light emission rule parameters and combined with the partitioned layout logic of the backlight execution unit, partitioned control instructions are generated. Based on the brightness control parameters, the brightness current mapping model is invoked to generate a brightness control command, which includes multi-level luminous intensity control values ​​of the light-emitting element and brightness stability compensation parameters. Based on the model matching parameters, the pre-stored model hardware adaptation database is called to generate model adaptation instructions; The partition control command, brightness control command, and model adaptation command are integrated and processed to obtain the backlight control command.

[0008] In one possible implementation, the differentiated control of multiple backlight regions divided by the backlight execution unit according to the backlight control command includes: Parse the model adaptation instruction in the backlight control instruction to obtain the target model corresponding to the model adaptation instruction and the preset hardware configuration parameters of the target model; Adjust the visual detection parameters according to the preset hardware configuration parameters of the target model; Based on the zonal control instructions and brightness control instructions in the backlight control instructions, a matching zonal differential control model is selected; Based on the visual detection parameters, the partitioned differential control model performs differential control on the light-emitting elements arranged in a preset array in each backlight area. The differential control includes the on / off sequence and light intensity of the light-emitting elements in each backlight area.

[0009] In one possible implementation, after performing differentiated control on the multiple backlight regions divided by the backlight execution unit according to the backlight control command, the method further includes: Obtain feedback parameters of the control command, and detect the execution effectiveness of the differentiated control based on the feedback parameters; If the differential control is successful, perform the step of collecting the luminous effect image of the backlight area; In the event of a failure of the differentiated control, the fault type is recorded and a retry mechanism is triggered to re-execute the step of differentiated control of multiple backlight areas divided by the backlight execution unit according to the backlight control command.

[0010] In one possible implementation, the visual analysis algorithm includes a localization algorithm and an optical feature extraction algorithm; The step of extracting features and identifying anomalies in the luminous effect image using a visual analysis algorithm, and outputting the anomaly detection results for the corresponding luminous elements in each backlight area, includes: A unique identifier for each light-emitting element and its position coordinates are established using a positioning algorithm. An optical feature extraction algorithm is used to determine whether there are any abnormal light emission elements in each light-emitting element, and the judgment result is obtained. When an abnormal light-emitting element is detected in the backlight area, the abnormal characteristics of the light-emitting element are obtained, including the abnormality type and the degree of abnormal deviation. The unique identifier of the abnormal light-emitting element is associated with the corresponding abnormal feature to generate an abnormal detection result that includes the abnormal type, the location coordinates of the abnormal element, and the degree of abnormal deviation.

[0011] In one possible implementation, the optical feature extraction algorithm includes a spot capture algorithm; The step of using an optical feature extraction algorithm to determine whether each light-emitting element has any light emission abnormalities, and obtaining the determination result, includes: The light spot feature parameters corresponding to each light-emitting element are extracted using a light spot capture algorithm; The light spot characteristic parameters of each light-emitting element are compared with the preset standard characteristic threshold to obtain the comparison results; If the comparison result meets the preset matching conditions, it is determined that the light-emitting element does not have any light emission abnormalities; If the comparison result does not meet the preset matching conditions, it is determined that the light-emitting element has an abnormal light emission.

[0012] In one possible implementation, the positioning algorithm includes a four-corner positioning and recognition algorithm and an LED positioning algorithm; The step of establishing the correspondence between the unique identifier of each light-emitting element and its position coordinates through a positioning algorithm includes: The region contour is extracted from the luminous effect image by using a four-corner positioning and recognition algorithm to determine the boundary coordinates and region range of each backlight area; Based on the boundary coordinates and area range, a lamp bead positioning algorithm is used to perform coordinate mapping on the light-emitting elements in each backlight area, and to establish the correspondence between the unique identifier of each light-emitting element and its position coordinates.

[0013] Secondly, this application provides a backlight detection system, the system comprising: The upper-level control unit is used to obtain preset backlight execution parameters and generate backlight control commands based on the backlight execution parameters; The microcontroller unit is used to receive the backlight control command and perform differentiated control on multiple backlight areas divided by the backlight execution unit according to the backlight control command. The backlight area includes a number of light-emitting elements arranged in a preset array. The visual processing unit is used to acquire the light emission effect image of the backlight area, perform feature extraction and anomaly identification on the light emission effect image through visual analysis algorithms, and output the anomaly detection results of the corresponding light-emitting elements in each backlight area.

[0014] Thirdly, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the backlight detection method described in any embodiment of the first aspect.

[0015] Fourthly, this application also provides a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a microprocessor, implements the steps of the backlight detection method described in any embodiment of the first aspect.

[0016] Compared with the prior art, the technical solution provided in this application has the following advantages: The method provided in this application automatically controls the on / off state of the backlight partition and the brightness of the LED beads, and combines a visual recognition algorithm to analyze the working state of the backlight light-emitting element in real time, thereby achieving efficient and accurate detection of the backlight light-emitting element; effectively reducing the degree of manual intervention and significantly improving the efficiency and accuracy of backlight detection. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0020] Figure 1 A schematic flowchart of a backlight detection method provided in an embodiment of this application; Figure 2A flowchart illustrating a backlight control command generation method provided in an embodiment of this application; Figure 3 A schematic diagram illustrating a process for differentiated control of multiple backlight regions provided in an embodiment of this application; Figure 4 A schematic flowchart of a backlight area anomaly detection method provided in an embodiment of this application; Figure 5 A schematic diagram of the process steps of a backlight detection method provided in an embodiment of this application; Figure 6 The luminous effect of the backlight area provided in the embodiments of this application Figure 1 ; Figure 7 The luminous effect of the backlight area provided in the embodiments of this application Figure 2 ; Figure 8 This is a schematic diagram of the structure of a backlight detection system provided in an embodiment of this application; Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, 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.

[0022] The following disclosure provides numerous different embodiments or examples for implementing various structures of the invention. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the scope of the invention. Furthermore, reference numerals and / or letters may be repeated in different examples. Such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0023] To address the technical problems of low efficiency, visual fatigue, and eye damage caused by existing manual visual inspection methods, which result in inaccurate identification of subtle defects such as brightness differences, slight bright spots, or dark spots, leading to a high rate of missed detections and affecting product quality consistency and reliability, this application provides a backlight detection method, system, electronic device, and storage medium. By automatically controlling the on / off state of the backlight zones and the brightness of the LEDs, and combining a visual recognition algorithm to analyze the working status of the backlight light-emitting elements in real time, this method achieves efficient and accurate detection of the backlight light-emitting elements, effectively reducing manual intervention and improving the efficiency and accuracy of backlight detection.

[0024] Figure 1 This is a schematic flowchart of a backlight detection method provided in an embodiment of this application, as shown below. Figure 1 As shown, the method specifically includes: S101. Obtain preset backlight execution parameters and generate backlight control commands based on the backlight execution parameters; Preset backlight execution parameters refer to a set of parameters that are pre-set to enable effective control of the backlight execution unit.

[0025] The backlight execution unit refers to the hardware that performs the light-emitting operation. By receiving instructions from the microcontroller unit, it controls the light-emitting elements in each backlight area according to the instructions, thereby realizing the visual detection of each light-emitting element in the backlight execution unit.

[0026] In this embodiment, the backlight execution parameters preset by the detection method are read from a pre-stored parameter database or obtained by manually inputting them through the user interface; then, based on the obtained backlight execution parameters, a corresponding backlight control command is generated and sent to the corresponding hardware device for execution.

[0027] S102. Receive the backlight control command and perform differentiated control on multiple backlight areas divided by the backlight execution unit according to the backlight control command. The backlight area includes a number of light-emitting elements arranged in a preset array. Backlight testing is used to test backlight execution units of different sizes, different zones, and different arrangements of light-emitting elements. During the testing process, differential control can be used to precisely adjust the on / off timing and light intensity of light-emitting elements in different backlight areas to adapt to different testing requirements.

[0028] In this embodiment, after receiving the generated backlight control command, the control command is parsed to obtain the partition control command and brightness control command in the backlight control command. Then, a matching partition differential control model is selected from the pre-set model library, and differential control is performed on the light-emitting elements arranged in a preset array in each backlight area based on the adjusted visual detection parameters.

[0029] Among them, differentiated control includes the on / off timing and luminous intensity of the light-emitting elements in each backlight area, which can flexibly control the working state of the light-emitting elements according to different detection requirements and the characteristics of the backlight execution unit.

[0030] It should be noted that the division of the backlight area is a reasonable division based on the different requirements of backlight testing in different testing scenarios and product characteristics. For example, for some products with high requirements for display uniformity, the backlight area may need to be divided more finely to more accurately detect brightness differences and subtle defects in each area. For backlight execution units that include multiple types of array arrangements, different backlight areas may need to be divided according to different array types to ensure that the light-emitting elements in each area have similar characteristics and operating modes, and that the light-emitting elements in each area can be independently controlled and detected, thereby improving the accuracy and efficiency of testing.

[0031] S103. Collect the light emission effect image of the backlight area, perform feature extraction and anomaly identification on the light emission effect image through a visual analysis algorithm, and output the anomaly detection results of the corresponding light-emitting elements in each backlight area.

[0032] A light emission effect image refers to the visual image presented by the light-emitting elements in the backlight area after they emit light according to control commands, intuitively reflecting the working status of each light-emitting element. A visual analysis algorithm refers to the algorithm used to process and analyze the acquired light emission effect image. This algorithm extracts useful feature information from the image and identifies possible anomalies in the light-emitting elements.

[0033] In this embodiment, an image acquisition device is used to acquire images of the backlight area during the detection process to obtain an accurate image of the light emission effect. Then, a visual analysis algorithm is used to perform anomaly analysis on the image of the light emission effect to detect whether there are any abnormal light-emitting elements in the light-emitting elements of the backlight area.

[0034] The backlight detection method provided in this application, through an automated process, first generates control commands based on preset parameters to achieve differentiated control of the backlight area, then collects and analyzes the light emission effect image, enabling efficient and accurate detection of the working status of the backlight emitting element. This not only avoids many drawbacks of manual visual inspection and improves detection efficiency, but also reduces the false negative rate, ensuring product quality consistency and reliability.

[0035] In practical applications, this detection method can be widely applied to various types of backlight actuators. Regardless of the size, resolution, or arrangement of the light-emitting elements, products can achieve efficient detection through flexible differentiated control and precise visual analysis.

[0036] Figure 2 This is a flowchart illustrating a backlight control command generation method provided in an embodiment of this application, as shown below. Figure 2 As shown, the backlight execution parameters include at least zone emission rule parameters, brightness control parameters, and model matching parameters; The generation of backlight control commands based on the backlight execution parameters includes: S201. Based on the partition light emission rule parameters and combined with the partition layout logic of the backlight execution unit, generate partition control instructions. The zone control instructions specify when each backlight area should be turned on and off to meet different detection needs. For example, for certain areas that require focused detection, their light-emitting elements can be kept on continuously, while for other auxiliary detection areas, the on / off state can be switched according to a specific timing sequence.

[0037] In this embodiment, the on / off rules of the light-emitting elements in each backlight area are first determined according to the zoning light emission rule parameters. Then, combined with the zoning layout logic of the backlight execution unit, the specific location and range of each zoning are clarified, thereby generating zoning control instructions.

[0038] S202. Based on the brightness control parameters, call the brightness current mapping model to generate a brightness control command. The brightness control command includes the multi-level luminous intensity control value of the light-emitting element and the brightness stability compensation parameter. In this embodiment, considering the differences in hardware characteristics of different backlight execution units, such as the type and power of light-emitting elements, it is necessary to generate appropriate brightness control commands based on the brightness adjustment parameters and these hardware characteristics. These commands will specify the luminous intensity of the light-emitting elements in each backlight area, ensuring that the working status of the light-emitting elements can be clearly observed during the detection process.

[0039] For example, in some detection scenarios where high brightness is required, the luminous intensity can be increased; in scenarios where high brightness stability is required, a brightness stability compensation parameter needs to be added to ensure that the brightness of the light-emitting element remains stable during the detection process.

[0040] S203. Based on the model matching parameters, call the pre-stored model hardware adaptation database to generate model adaptation instructions; In this embodiment, to ensure that the backlight detection can accurately detect the backlight execution units of different models, it is necessary to search for the corresponding adaptation information from the pre-stored model hardware adaptation database according to the model matching parameters and generate model adaptation instructions. Subsequently, the relevant visual parameters are adjusted according to the model, and the detection process and mode are selected (e.g., checkerboard detection, odd and even row and column detection, single row and column detection, single LED detection, etc.).

[0041] By generating model adaptation instructions, backlight detection can be made more widely applicable, enabling accurate and efficient completion of backlight detection tasks for various models, further improving the accuracy and reliability of detection, and ensuring the quality consistency of products of different models. S204. The partition control command, brightness control command and model adaptation command are integrated and processed to obtain the backlight control command.

[0042] In this embodiment, the zone control command, brightness control command, and model adaptation command are integrated into a complete and unified backlight control command.

[0043] Specifically, the original three independent functional modules corresponding to the zone control command, brightness control command, and model adaptation command are integrated into a complete and unified backlight control command through a unified design logic and interface standard. This not only simplifies the operation process but also improves the system's compatibility and execution efficiency, thereby enabling better adaptation to different hardware models and achieving more precise brightness and zone adjustment functions.

[0044] The backlight control instruction generation method provided in this application generates corresponding instructions by processing the zonal light emission rule parameters, brightness adjustment parameters, and model matching parameters respectively, and then integrating them to achieve precise control of the backlight execution unit. It fully considers the needs of different detection scenarios and product characteristics, and can flexibly adjust the on / off timing, light emission intensity, and adapt to different models according to specific circumstances.

[0045] In practical applications, this method greatly improves the flexibility and accuracy of backlight testing, reducing errors and uncertainties caused by manual operation. Furthermore, its versatility allows for wide application in the testing of various backlight actuators, from small electronic device backlights to large display backlights, enabling efficient and accurate testing and further ensuring product quality and performance.

[0046] Figure 3 This application provides a schematic flowchart for differentiated control of multiple backlight areas, as illustrated in the embodiments of this application. Figure 3 As shown, the differentiated control of multiple backlight areas divided by the backlight execution unit according to the backlight control command includes: S301. Parse the model adaptation instruction in the backlight control instruction, and obtain the target model corresponding to the model adaptation instruction and the preset hardware configuration parameters of the target model; In this embodiment, the model adaptation instruction in the backlight control instruction is first parsed to extract the specific information of the target model and the preset hardware configuration parameters corresponding to the target model.

[0047] S302. Adjust the visual detection parameters according to the preset hardware configuration parameters of the target model; Visual inspection parameters include, but are not limited to, image acquisition resolution, frame rate, exposure time, contrast, and brightness. Different target devices have different hardware characteristics, and therefore different requirements for visual inspection parameters.

[0048] In this embodiment, the visual detection parameters are adjusted specifically according to the preset hardware configuration parameters of the target model. For example, for a high-resolution backlight execution unit, in order to clearly capture the working state of each light-emitting element, it is necessary to increase the resolution of image acquisition; while for rapidly changing light emission effects, it may be necessary to increase the frame rate to ensure that the complete light emission process is captured.

[0049] Meanwhile, different hardware characteristics may cause the luminescence effect image to exhibit different features, such as brightness distribution and color performance; according to the hardware configuration parameters of the target model, the relevant parameters of the visual analysis algorithm can also be adjusted; by adjusting the parameters of the visual analysis algorithm, it is possible to better adapt to these characteristics and improve the accuracy of feature extraction and anomaly recognition.

[0050] S303. Based on the zonal control command and brightness control command in the backlight control command, select a matching zonal differential control model; The differentiated control model is based on a large number of experiments and practical application scenarios, and can achieve optimal control of the light-emitting elements in each backlight area; different combinations of zone control commands and brightness control commands correspond to different zone differentiated control models.

[0051] In this embodiment, based on the on / off rules of each backlight area specified in the zoning control instruction, and the multi-level luminous intensity adjustment values ​​and brightness stability compensation parameters of the light-emitting elements specified in the brightness control instruction, a zoning differential control model matching the specified zoning control model is selected from a pre-set model library.

[0052] S304. Based on the visual detection parameters, the partitioned differential control model performs differential control on the light-emitting elements arranged in a preset array in each backlight area. The differential control includes the on / off sequence and light intensity of the light-emitting elements in each backlight area.

[0053] In this embodiment, a zoned differential control model is used, combined with adjusted visual detection parameters, to precisely control the light-emitting elements in each backlight area.

[0054] Specifically, following the brightness and darkness rules specified in the zoning control instructions, the lighting and darkness times of the light-emitting elements in each backlight area are precisely controlled to ensure that a specific light-emitting mode can be presented according to the detection requirements. For example, for specific areas that require focused detection, the light-emitting elements can be quickly controlled according to the set timing sequence to highlight any possible anomalies; for auxiliary detection areas, a more stable brightness and darkness mode can be used to facilitate overall observation and comparison.

[0055] The multiple backlight area differentiation control methods provided in this application realize precise differentiation control of light-emitting elements in each backlight area by parsing backlight control commands, adjusting visual detection parameters, and matching partition differentiation control models. This fully considers the hardware characteristics and detection requirements of different models and can flexibly adjust the on / off timing and light intensity of light-emitting elements in each backlight area according to specific circumstances, thereby improving the accuracy and efficiency of backlight detection.

[0056] In an optional embodiment of the present invention, after performing differentiated control on the multiple backlight regions divided by the backlight execution unit according to the backlight control command, the method further includes: Obtain feedback parameters of the control command and detect the effectiveness of the differentiated control based on the feedback parameters; if the differentiated control is successful, execute the step of collecting the light emission effect diagram of the backlight area; if the differentiated control fails, record the fault type and trigger a retry mechanism to re-execute the step of performing differentiated control on multiple backlight areas divided by the backlight execution unit according to the backlight control command.

[0057] In this embodiment, after the control command is sent to the microcontroller unit, the microcontroller unit sends back the relevant feedback parameters for command execution. By analyzing these feedback parameters, it can be determined whether the differentiated control is executed as expected. If the feedback parameters show that the on / off timing and luminous intensity of the light-emitting elements in each backlight area are consistent with the control command, it indicates that the differentiated control is successful. If the feedback parameters show a deviation from the control command, such as incorrect on / off timing of the light-emitting elements in some backlight areas or insufficient luminous intensity, it indicates that the differentiated control has failed. In this case, the fault type is recorded in detail, such as hardware failure or incorrect parameter settings, and a retry mechanism is triggered. The retry mechanism will re-execute the steps of differentiated control of multiple backlight areas divided by the backlight execution unit according to the backlight control command, attempting to achieve precise control again.

[0058] In addition, during the retry process, relevant parameters may be fine-tuned, such as appropriately adjusting the luminous intensity control value in the brightness control command or optimizing the on / off rules in the zone control command, to improve control accuracy. If differentiated control still fails after multiple retries, an alarm will be issued to prompt manual intervention. Operators can inspect and repair the hardware based on the recorded fault type, or reset relevant parameters to ensure the backlight detection system operates normally.

[0059] Through this feedback and retry mechanism, backlight detection can continuously optimize the control process, improve the stability and reliability of detection, and provide stronger assurance for product quality. At the same time, the automated fault handling method also reduces the frequency of manual intervention, improves detection efficiency, and reduces labor costs.

[0060] Figure 4 This is a flowchart illustrating a backlight area anomaly detection method provided in an embodiment of this application, as shown below. Figure 4 As shown, the visual analysis algorithm includes a localization algorithm and an optical feature extraction algorithm; The step of extracting features and identifying anomalies in the luminous effect image using a visual analysis algorithm, and outputting the anomaly detection results for the corresponding luminous elements in each backlight area, includes: S401. Establish the correspondence between the unique identifier of each light-emitting element and its position coordinates through a positioning algorithm; A positioning algorithm is an algorithm used to determine the specific location of a light-emitting element in a light-emitting effect diagram.

[0061] In this embodiment, each light-emitting element in the light-emitting effect diagram is precisely located using a positioning algorithm. Each light-emitting element is assigned a unique identifier, and a correspondence is established between the identifier and the position coordinates of the light-emitting element.

[0062] S402. Using an optical feature extraction algorithm, determine whether there is any abnormal light emission in each light-emitting element, and obtain the judgment result; Optical feature extraction algorithms refer to algorithms that analyze the features of light-emitting elements in a light-emitting effect image and extract their optical features such as brightness, color, saturation, and hue.

[0063] In this embodiment, by quantifying and analyzing these optical features and comparing them with a preset normal feature range, it is determined whether each light-emitting element has any light emission abnormalities.

[0064] For example, if the brightness of a light-emitting element is significantly lower than the normal range, or if the color deviates greatly from the standard color, the light-emitting element is judged to be abnormal.

[0065] S403. When an abnormal light-emitting element is detected in the backlight area, the abnormal characteristics of the light-emitting element are obtained, including the abnormality type and the degree of abnormal deviation. In this embodiment, once an abnormality in the light-emitting element is detected, its abnormal characteristics are immediately analyzed. The abnormality type may include brightness abnormality, color abnormality, saturation abnormality, hue abnormality, etc.; corresponding brightness abnormality may manifest as being too bright or too dark, while color abnormality, saturation abnormality, and hue abnormality may be due to color deviation, color distortion, etc.

[0066] The degree of deviation from the norm measures the difference between the abnormal state and the normal state. For example, in the case of abnormal brightness, the degree of deviation can be determined by calculating the difference between the actual brightness and the normal brightness range; in the case of abnormal color, the degree of deviation can be represented by distance measures in the color space. Clearly identifying the type of abnormality and the degree of deviation helps in the subsequent accurate handling of abnormal situations.

[0067] S404. Associate the unique identifier of the abnormal light-emitting element with the corresponding abnormal feature to generate an abnormal detection result that includes the abnormal type, the position coordinates of the abnormal element, and the degree of abnormal deviation.

[0068] In this embodiment, the unique identifier of the abnormal light-emitting element is associated with the corresponding abnormal feature to determine the specific situation of each abnormal light-emitting element. The generated abnormal detection result contains key information such as the abnormality type, the location coordinates of the abnormal element, and the degree of abnormal deviation, providing comprehensive and accurate data support for subsequent processing.

[0069] The faulty light-emitting element can then be quickly located based on the anomaly detection results. For example, if the detection results show that the light-emitting element at a specific coordinate is abnormally dim and the deviation is significant, the inspectors can directly conduct further inspection and repair on that element.

[0070] The backlight area anomaly detection method provided in this application can efficiently and accurately detect anomalies in the light-emitting elements within each backlight area and generate detailed anomaly detection results. This provides strong support for product quality control and production management, and helps improve production efficiency and product quality. After the anomaly detection results are generated, they can be stored in a database for convenient subsequent statistical analysis.

[0071] In one optional embodiment of the present invention, the optical feature extraction algorithm includes a spot capture algorithm; The step of using an optical feature extraction algorithm to determine whether each light-emitting element has any light emission abnormalities, and obtaining the determination result, includes: The light spot feature parameters corresponding to each light-emitting element are extracted by a light spot capture algorithm; the light spot feature parameters of each light-emitting element are compared with a preset standard feature threshold to obtain the comparison result; if the comparison result meets the preset matching condition, it is determined that the light-emitting element does not have a light emission abnormality; if the comparison result does not meet the preset matching condition, it is determined that the light-emitting element has a light emission abnormality.

[0072] The spot capture algorithm refers to an algorithm used to capture the spot formed by each light-emitting element from the light emission effect image. The preset standard feature threshold is derived from statistical analysis of a large amount of spot feature data of normal light-emitting elements, and represents the range of spot features of normal light-emitting elements.

[0073] In this embodiment, a spot capture algorithm can accurately extract the spot feature parameters corresponding to each light-emitting element. These parameters can include the size, shape, and brightness distribution of the spot. When comparing the spot feature parameters of each light-emitting element with a preset standard feature threshold, if the spot feature parameters of a certain light-emitting element are completely within the range of the preset standard feature threshold (i.e., the comparison result meets the preset matching condition), then it can be determined that the light-emitting element does not have any light emission abnormalities. Conversely, if the spot feature parameters of a certain light-emitting element exceed the range of the preset standard feature threshold (i.e., the comparison result does not meet the preset matching condition), then it indicates that the light-emitting element has any light emission abnormalities.

[0074] For example, if the size of the light spot of a certain light-emitting element is significantly larger or smaller than the range specified by the preset standard feature threshold, or if its brightness distribution is uneven and differs greatly from the standard brightness distribution, it can be determined that the light-emitting element is abnormal.

[0075] Based on the comparison method of spot capture algorithm and preset standard feature threshold, it is possible to more intuitively and accurately determine whether there is light emission abnormality in the light-emitting element, and further improve the accuracy and reliability of anomaly detection.

[0076] The luminescence anomaly detection method provided in this application performs contour detection on a binarized image and independently processes each contour region using parallel loops. For each contour, its area, geometric center, and minimum circumscribed circle radius are calculated. The average gray level and maximum gray level intensity in the original image are extracted using masking technology. The feature data is aggregated using a thread-safe concurrent container, achieving efficient capture of contour information in a multi-threaded environment. While ensuring accuracy, the image processing time is significantly shortened, exhibiting good real-time performance.

[0077] In one optional embodiment of the present invention, the positioning algorithm includes a four-corner positioning and recognition algorithm and an LED positioning algorithm; The step of establishing the correspondence between the unique identifier and position coordinates of each light-emitting element through a positioning algorithm includes: extracting the region contour of the light-emitting effect image through a four-corner positioning recognition algorithm to determine the boundary coordinates and region range of each backlight region; and, based on the boundary coordinates and region range, using a lamp bead positioning algorithm to perform coordinate mapping on the light-emitting elements in each backlight region to establish the correspondence between the unique identifier and position coordinates of each light-emitting element.

[0078] The four-corner positioning and recognition algorithm refers to an algorithm used to identify the position information of the four corners of each backlit area in a luminous effect image, thereby determining the outline of the area. The LED bead positioning algorithm refers to an algorithm that, based on a preset LED bead arrangement rule and combined with the actual distribution characteristics of the light-emitting elements in the image, accurately locates the coordinate position of each light-emitting element within the backlit area and assigns it a unique identifier.

[0079] In this embodiment, a four-corner positioning and recognition algorithm is first used to highlight the edge information in the backlight effect image using edge detection technology. Then, by analyzing the continuity and angle of the edges, pixels that match the corner characteristics are further filtered out. For example, edges at corners often have significant angular changes, and the algorithm uses this characteristic for precise judgment. After identifying potential corners, the algorithm verifies and optimizes them by comparing the distance and relative position between adjacent corners to determine if they conform to the geometric characteristics of the backlight area. If a corner's position is found to be illogical, the algorithm adjusts or removes it. Once the positions of the four corners of each backlight area are determined, the boundary coordinates and area range of each backlight area are precisely delineated based on the coordinate information of these corners, laying the foundation for subsequent LED positioning and anomaly detection of light-emitting elements. For example, a distance measurement algorithm is used, taking the four corners of the detection area as a reference, traversing the coordinate difference between all LED beads and the four corners, and calculating and determining the coordinates of the edge LED beads; after actual testing, when the machine placement angle deviates from the camera image by ≤30°, the algorithm can still identify stably, effectively avoiding the identification failure problem caused by non-standard manual operation on the production line (such as machine position offset, camera angle deviation). Then, using the edge coordinates obtained by the four-corner recognition algorithm as a reference, the coordinate interval difference of the LED in the horizontal and vertical directions is calculated respectively, and the compensation coefficient between the horizontal and vertical coordinates is calculated at the same time. Even in non-ideal shooting scenarios where the back panel angle is tilted or the angle between the camera and the back panel is not 90°, the coordinate deviation can still be corrected by the compensation coefficient to achieve accurate positioning of the LED.

[0080] Figure 5 This is a schematic diagram of the process steps of a backlight detection method provided in an embodiment of this application, as shown below. Figure 5 As shown, the backlight detection method mainly includes the following steps: After the testing process is initiated, the relevant equipment is first turned on, then the vision parameters are adjusted and the configuration is saved. Upon starting the test, a serial port command is sent to the microcontroller unit, which controls the light-emitting element of the backlight execution unit and provides feedback on the execution result. If execution fails, the process returns to the step of "sending serial port command to the microcontroller unit"; if successful, the vision processing of the backlight execution unit proceeds. During this process, error messages are printed and alarms are triggered, awaiting manual intervention. After printing is complete, it is necessary to determine if there are any unfinished testing tasks to ensure that all testing tasks have been executed.

[0081] like Figure 6 Figure 7 As shown, the general backlight detection process consists of at least two parts; Part 1: Full brightness detection, used to detect whether there are any LED beads that are not lit, and whether there are LED beads with abnormal brightness.

[0082] Part Two: Odd-Even Checkerboard Detection, used to detect whether there are LEDs that are constantly lit due to electrostatic discharge, and whether adjacent LEDs are lit simultaneously due to solder bridging.

[0083] Through the combined action of full-brightness detection and odd-even checkerboard detection, backlight detection can efficiently and accurately detect various abnormalities of light-emitting elements in the backlight area, providing a solid foundation for product quality assurance, while also helping to improve production efficiency and reduce production costs. It should be noted that the odd-even checkerboard detection in Part Two is only an example. In actual implementation, other suitable detection methods can be flexibly selected or designed according to the actual backlight detection needs and product characteristics. For example, a zoned brightness comparison detection method can be used, dividing the backlight area into multiple small areas and comparing the brightness differences between adjacent areas or specific areas to determine whether there are problems such as uneven brightness, local over-brightness, or under-brightness.

[0084] In addition, for backlight products with high requirements for color accuracy, color consistency testing can be performed. By analyzing the color of the light emitted by each light-emitting element and comparing it with a standard color sample, it can be determined whether there are any color deviations or color distortions. Furthermore, to further improve the comprehensiveness and accuracy of the testing, multiple testing methods can be combined.

[0085] Figure 8 This is a schematic diagram of a backlight detection system provided in an embodiment of this application, as shown below. Figure 8 As shown, the system specifically includes: The upper-level control unit 801 is used to acquire preset backlight execution parameters and generate backlight control commands based on the backlight execution parameters; The microcontroller unit 802 is used to receive the backlight control command and perform differentiated control on multiple backlight areas divided by the backlight execution unit according to the backlight control command. The backlight area includes a number of light-emitting elements arranged in a preset array. The visual processing unit 803 is used to acquire the light emission effect image of the backlight area, perform feature extraction and anomaly recognition on the light emission effect image through a visual analysis algorithm, and output the anomaly detection results of the corresponding light-emitting elements in each backlight area.

[0086] In one possible implementation, the upper-level control unit 801 is further configured to generate a partition control instruction based on the partition light emission rule parameters and the partition layout logic of the backlight execution unit; generate a brightness control instruction by calling the brightness current mapping model based on the brightness adjustment parameters, wherein the brightness control instruction includes multi-level light emission intensity adjustment values ​​and brightness stability compensation parameters of the light-emitting element; generate a model adaptation instruction by calling the pre-stored model hardware adaptation database based on the model matching parameters; and integrate the partition control instruction, the brightness control instruction, and the model adaptation instruction to obtain the backlight control instruction.

[0087] In one possible implementation, the microcontroller unit 802 is further configured to parse the model adaptation instruction in the backlight control instruction, obtain the target model corresponding to the model adaptation instruction and the preset hardware configuration parameters of the target model; adjust the visual detection parameters according to the preset hardware configuration parameters of the target model; select a matching partition differential control model based on the partition control instruction and brightness control instruction in the backlight control instruction; and perform differential control on the light-emitting elements arranged in a preset array in each backlight area according to the visual detection parameters through the partition differential control model, wherein the differential control includes the on / off sequence and luminous intensity of the light-emitting elements in each backlight area.

[0088] In one possible implementation, the microcontroller unit 802 is further configured to acquire feedback parameters of the control command and detect the execution effectiveness of the differentiated control based on the feedback parameters; if the differentiated control is successful, execute the step of acquiring the luminous effect diagram of the backlight area; if the differentiated control fails, record the fault type and trigger a retry mechanism to re-execute the step of performing differentiated control on the multiple backlight areas divided by the backlight execution unit according to the backlight control command.

[0089] In one possible implementation, the vision processing unit 803 is further configured to establish a correspondence between the unique identifier and position coordinates of each light-emitting element through a positioning algorithm; determine whether there is a light emission abnormality in each light-emitting element through an optical feature extraction algorithm, and obtain a judgment result; when a light-emitting element with a light emission abnormality is detected in the backlight area, obtain the abnormal features of the light-emitting element, the abnormal features including the abnormality type and the degree of abnormal deviation; associate the unique identifier of the abnormal light-emitting element with the corresponding abnormal features to generate an abnormality detection result containing the abnormality type, the position coordinates of the abnormal element, and the degree of abnormal deviation.

[0090] In one possible implementation, the visual processing unit 803 is further configured to extract the light spot feature parameters corresponding to each light-emitting element through a light spot capture algorithm; compare the light spot feature parameters of each light-emitting element with a preset standard feature threshold to obtain a comparison result; if the comparison result meets the preset matching conditions, determine that the light-emitting element does not have a light emission abnormality; if the comparison result does not meet the preset matching conditions, determine that the light-emitting element has a light emission abnormality.

[0091] In one possible implementation, the visual processing unit 803 is further configured to extract the region contour of the light emission effect image using a four-corner positioning recognition algorithm, determine the boundary coordinates and region range of each backlight region; based on the boundary coordinates and region range, use a lamp bead positioning algorithm to perform coordinate mapping on the light emission elements in each backlight region, and establish the correspondence between the unique identifier of each light emission element and its position coordinates.

[0092] The backlight detection system provided in this embodiment can be as follows: Figure 8 The backlight detection system shown can perform, for example... Figure 1-7 All steps of backlight detection are completed, thereby achieving Figure 1-7 For details on the technical effects of the backlight detection shown, please refer to [link / reference]. Figure 1-7 The relevant descriptions are presented concisely and will not be elaborated upon here.

[0093] The system embodiments described above are merely illustrative. 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 modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0094] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 9As shown, this application embodiment provides an electronic device, including a processor 901, a communication interface 902, a memory 903, and a communication bus 904. The processor 901, communication interface 902, and memory 903 communicate with each other via the communication bus 904. The memory 903 stores computer programs. When the processor 901 executes the program stored in the memory 903, it implements the backlight detection steps provided in any of the aforementioned method embodiments. Obtain preset backlight execution parameters and generate backlight control instructions based on the backlight execution parameters; receive the backlight control instructions and perform differentiated control on multiple backlight areas divided by the backlight execution unit according to the backlight control instructions, wherein the backlight area includes several light-emitting elements arranged in a preset array; collect the light emission effect image of the backlight area, perform feature extraction and anomaly identification on the light emission effect image through a visual analysis algorithm, and output the anomaly detection results of the corresponding light-emitting elements in each backlight area.

[0095] In one possible implementation, based on the partitioned light emission rule parameters and combined with the partitioned layout logic of the backlight execution unit, a partitioned control instruction is generated; based on the brightness adjustment parameters, a brightness current mapping model is invoked to generate a brightness control instruction, which includes multi-level light emission intensity adjustment values ​​and brightness stability compensation parameters of the light-emitting element; based on the model matching parameters, a pre-stored model hardware adaptation database is invoked to generate a model adaptation instruction; the partitioned control instruction, the brightness control instruction, and the model adaptation instruction are integrated and processed to obtain the backlight control instruction.

[0096] In one possible implementation, the device model adaptation instruction in the backlight control instruction is parsed to obtain the target device model corresponding to the device model adaptation instruction and the preset hardware configuration parameters of the target device model; the visual detection parameters are adjusted according to the preset hardware configuration parameters of the target device model; based on the zoning control instruction and brightness control instruction in the backlight control instruction, a matching zoning differential control model is selected; through the zoning differential control model, based on the visual detection parameters, differential control is performed on the light-emitting elements arranged in a preset array in each backlight area, the differential control including the on / off sequence and luminous intensity of the light-emitting elements in each backlight area.

[0097] In one possible implementation, feedback parameters of the control command are obtained, and the execution effectiveness of the differentiated control is detected based on the feedback parameters; if the differentiated control is successful, the step of collecting the luminous effect diagram of the backlight area is executed; if the differentiated control fails, the fault type is recorded and a retry mechanism is triggered, and the step of performing differentiated control on multiple backlight areas divided by the backlight execution unit according to the backlight control command is re-executed.

[0098] In one possible implementation, a localization algorithm is used to establish a correspondence between the unique identifier of each light-emitting element and its position coordinates; an optical feature extraction algorithm is used to determine whether each light-emitting element has a light emission abnormality, and a determination result is obtained; if a light-emitting element with a light emission abnormality is detected in the backlight area, the abnormal features of the light-emitting element are obtained, and the abnormal features include the abnormality type and the degree of abnormal deviation; the unique identifier of the abnormal light-emitting element is associated with the corresponding abnormal features to generate an abnormality detection result containing the abnormality type, the position coordinates of the abnormal element, and the degree of abnormal deviation.

[0099] In one possible implementation, spot feature parameters corresponding to each light-emitting element are extracted using a spot capture algorithm; the spot feature parameters of each light-emitting element are compared with a preset standard feature threshold to obtain a comparison result; if the comparison result meets the preset matching conditions, it is determined that the light-emitting element does not have a light emission abnormality; if the comparison result does not meet the preset matching conditions, it is determined that the light-emitting element has a light emission abnormality.

[0100] In one possible implementation, the region contour of the light-emitting effect image is extracted by a four-corner positioning and recognition algorithm to determine the boundary coordinates and region range of each backlight region; based on the boundary coordinates and region range, the light-emitting element in each backlight region is mapped by an LED positioning algorithm to establish the correspondence between the unique identifier of each light-emitting element and its position coordinates.

[0101] The system embodiments described above are merely illustrative. 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 modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0102] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, or of course, using hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0103] It should be understood that the terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” as used herein may also include the plural forms. The terms “comprising,” “including,” “containing,” and “having” are inclusive and therefore indicate the presence of the stated features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or combinations thereof. The method steps, processes, and operations described herein are not construed as requiring them to be performed in a particular order described or illustrated unless the order of performance is explicitly indicated. It should also be understood that additional or alternative steps may be used.

[0104] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A backlight detection method, characterized by, The method comprises the following steps: acquiring preset backlight execution parameters and generating backlight control instructions based on the backlight execution parameters; receiving the backlight control instructions and differentiating control of a plurality of backlight areas divided by a backlight execution unit according to the backlight control instructions, wherein the backlight areas comprise a plurality of light emitting elements arranged in a preset array; collecting light emitting effect images of the backlight areas, performing feature extraction and anomaly identification on the light emitting effect images through a visual analysis algorithm, and outputting anomaly detection results of corresponding light emitting elements in each backlight area.

2. The method of claim 1, wherein, The backlight execution parameters at least include partition light emitting rule parameters, brightness regulation parameters and model matching parameters; The generation of the backlight control instructions based on the backlight execution parameters comprises: generating partition control instructions based on the partition light emitting rule parameters and combining the partition layout logic of the backlight execution unit; generating brightness control instructions by calling a brightness current mapping model based on the brightness regulation parameters, wherein the brightness control instructions comprise multi-level light emitting intensity regulation values of the light emitting elements and brightness stability compensation parameters; generating model adaptation instructions by calling a pre-stored model hardware adaptation database based on the model matching parameters; integrating the partition control instructions, the brightness control instructions and the model adaptation instructions to obtain the backlight control instructions.

3. The method of claim 1, wherein, The differentiating control of the plurality of backlight areas divided by the backlight execution unit according to the backlight control instructions comprises: analyzing the model adaptation instructions in the backlight control instructions to obtain a target model corresponding to the model adaptation instructions and preset hardware configuration parameters of the target model; adjusting visual detection parameters according to the preset hardware configuration parameters of the target model; selecting a matched partition differentiating control model based on the partition control instructions and the brightness control instructions in the backlight control instructions; performing differentiating control on the light emitting elements arranged in the preset array in each backlight area according to the visual detection parameters through the partition differentiating control model, wherein the differentiating control comprises light emitting intensity and light-on / off timing of the light emitting elements in each backlight area.

4. The method of claim 1, wherein, After the differentiating control of the plurality of backlight areas divided by the backlight execution unit according to the backlight control instructions, the method further comprises: obtaining feedback parameters of the control instructions and detecting the execution effectiveness of the differentiating control based on the feedback parameters; performing the step of collecting the light emitting effect images of the backlight areas in the case of successful differentiating control; in the case of failed differentiating control, recording a fault type and triggering a retry mechanism to re-perform the step of differentiating control of the plurality of backlight areas divided by the backlight execution unit according to the backlight control instructions.

5. The method of claim 1, wherein, The visual analysis algorithm comprises a positioning algorithm and an optical feature extraction algorithm; The feature extraction and anomaly identification on the light emitting effect images through the visual analysis algorithm and the output of the anomaly detection results of the corresponding light emitting elements in each backlight area comprise: establishing a corresponding relationship between unique identifiers and position coordinates of each light emitting element through the positioning algorithm; judging whether each light emitting element has light emitting anomaly through the optical feature extraction algorithm to obtain a judgment result; In the case of detecting a light-emitting element with abnormal light emission in the backlight area, an abnormal feature of the light-emitting element is obtained, the abnormal feature including an abnormal type and an abnormal deviation degree; The unique identifier of the abnormal light-emitting element is associated with the corresponding abnormal feature to generate an abnormal detection result including the abnormal type, the abnormal element position coordinates, and the abnormal deviation degree.

6. The method of claim 5, wherein, The optical feature extraction algorithm includes a light spot capturing algorithm; The optical feature extraction algorithm includes a light spot capturing algorithm; The optical feature extraction algorithm includes a light spot capturing algorithm; The light spot feature parameters of each light-emitting element are compared with the preset standard feature threshold respectively to obtain a comparison result; In the case of satisfying the preset matching condition, it is determined that the light-emitting element does not have abnormal light emission; In the case of not satisfying the preset matching condition, it is determined that the light-emitting element has abnormal light emission.

7. The method of claim 5, wherein, The positioning algorithm includes a four-corner positioning recognition algorithm and a lamp bead positioning algorithm; The positioning algorithm includes a four-corner positioning recognition algorithm and a lamp bead positioning algorithm; The positioning algorithm includes a four-corner positioning recognition algorithm and a lamp bead positioning algorithm; Based on the boundary coordinates and the area range, the light-emitting elements in each backlight area are mapped by the lamp bead positioning algorithm to establish the corresponding relationship between the unique identifier of each light-emitting element and the position coordinates.

8. A back light detection system characterized by, Including: The upper control unit is used to obtain a preset backlight execution parameter and generate a backlight control instruction based on the backlight execution parameter; The micro control unit is used to receive the backlight control instruction and perform differential control on the multiple backlight areas divided by the backlight execution unit according to the backlight control instruction, the backlight areas including a plurality of light-emitting elements arranged according to a preset array; The visual processing unit is used to collect the light-emitting effect diagram of the backlight area, extract features and identify abnormalities of the light-emitting effect diagram by a visual analysis algorithm, and output the abnormal detection result of the corresponding light-emitting element in each backlight area.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to realize the steps of the backlight detection method in any one of claims 1-7.

10. A storage medium having stored thereon a computer program, characterized in that The computer program is executed by the processor to realize the steps of the backlight detection method in any one of claims 1-7.

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