Screen aging detection method and device and electronic equipment

Abstract

The invention discloses a screen aging detection method and device and electronic equipment, and belongs to the technical field of screen detection. The method comprises the following steps: obtaining detection values of a plurality of photosensitive channels corresponding to each detection picture, wherein the detection pictures comprise a black detection picture and a plurality of reference color detection pictures; based on the detection value of each photosensitive channel corresponding to each reference color detection picture and the detection value of each photosensitive channel corresponding to the black detection picture, obtaining a screen light component of each photosensitive channel corresponding to each reference color detection picture; and obtaining a screen aging detection result based on the screen light component of each photosensitive channel corresponding to each reference color detection picture.

Description

Technical Field

[0001] This application belongs to the field of screen testing technology, specifically relating to a screen aging testing method, device, and electronic equipment. Background Technology

[0002] Screen aging prediction technology has wide applications in the electronics field. For example, adaptive tuning improves the accuracy of automatic backlighting and adaptive color temperature by adjusting the compensation model based on the degree of screen aging; residual value assessment provides screen lifespan reports during second-hand transactions, enhancing transaction transparency; and warranty services allow manufacturers to remotely diagnose whether screen aging has caused malfunctions.

[0003] Existing screen aging detection technologies mainly rely on traditional optical detection methods, current detection methods, and camera detection methods. The first method is greatly affected by ambient light in daily scenarios, resulting in inaccurate detection results. The second method cannot distinguish between ambient temperature and the current difference caused by screen aging, which also leads to inaccurate detection results. The third method increases module costs, is highly dependent on hardware, and the detection results are affected by lens contamination. Summary of the Invention

[0004] The purpose of this application is to provide a screen aging detection method, apparatus, and electronic device that can solve the problem of inaccurate screen aging detection results.

[0005] In a first aspect, embodiments of this application provide a screen aging detection method, including: The detection values ​​of multiple photosensitive channels corresponding to each detection screen are obtained, and the detection screen includes a black detection screen and multiple reference color detection screens; Based on the detection values ​​of each photosensitive channel corresponding to each reference color detection image and the detection values ​​of each photosensitive channel corresponding to the black detection image, the screen light component of each photosensitive channel corresponding to each reference color detection image is obtained. Based on the screen light components of each photosensitive channel corresponding to each reference color detection image, the screen aging detection results are obtained.

[0006] Secondly, embodiments of this application provide a screen aging detection device, comprising: The acquisition module is used to acquire the detection values ​​of multiple photosensitive channels corresponding to each detection screen, wherein the detection screen includes a black detection screen and multiple reference color detection screens; Based on the detection values ​​of each photosensitive channel corresponding to each reference color detection image and the detection values ​​of each photosensitive channel corresponding to the black detection image, the screen light component of each photosensitive channel corresponding to each reference color detection image is obtained. The processing module is used to obtain the screen aging test results based on the screen light components of each photosensitive channel corresponding to each reference color detection image.

[0007] Thirdly, embodiments of this application provide an electronic device including a processor and a memory, wherein the memory stores programs or instructions executable on the processor, and the programs or instructions, when executed by the processor, implement the steps of the method described in the first aspect.

[0008] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0009] Fifthly, embodiments of this application provide a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the method as described in the first aspect.

[0010] In a sixth aspect, embodiments of this application provide a computer program product stored in a storage medium, which is executed by at least one processor to implement the method described in the first aspect.

[0011] In this embodiment, the detection values ​​of multiple photosensitive channels corresponding to each detection screen are obtained. The detection screens include a black detection screen and multiple reference color detection screens. The detection values ​​of each photosensitive channel corresponding to each detection screen are the superposition values ​​of ambient light and screen light. Based on the detection values ​​of each photosensitive channel corresponding to each reference color detection screen and the detection values ​​of each photosensitive channel corresponding to the black detection screen, the screen light components of each photosensitive channel corresponding to each reference color detection screen are obtained. The detection values ​​of each photosensitive channel corresponding to the black detection screen are used to filter out ambient light interference, thereby obtaining the screen light components of each photosensitive channel corresponding to each reference color detection screen after filtering out ambient light, which can effectively eliminate the measurement error caused by ambient light fluctuations. Based on the screen light components of each photosensitive channel corresponding to each reference color detection screen, the screen aging detection results are obtained, and the screen aging detection results can achieve a high degree of accuracy in predicting the screen aging degree. Attached Figure Description

[0012] Figure 1 This is a schematic flowchart of the screen aging detection method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the display for enabling the screen aging detection function according to an embodiment of this application; Figure 3 This is a schematic diagram of the switching of the detection screen provided in the embodiments of this application; Figure 4This is one of the display diagrams of the screen aging coefficient provided in the embodiments of this application; Figure 5 This is the second schematic diagram of the screen aging coefficient provided in the embodiments of this application; Figure 6 This is the third schematic diagram of the screen aging coefficient provided in the embodiments of this application; Figure 7 This is a flowchart of the screen aging detection model provided in the embodiments of this application; Figure 8 This is a schematic diagram of the specific process of the screen aging detection method provided in the embodiments of this application; Figure 9 This is a schematic diagram illustrating the screen usage suggestions provided in the embodiments of this application; Figure 10 This is a schematic diagram showing the prompt information for screen repair locations provided in an embodiment of this application; Figure 11 This is a schematic diagram of the screen aging detection device provided in the embodiments of this application; Figure 12 This is a structural block diagram of an electronic device provided in an embodiment of this application; Figure 13 This is a structural block diagram of another electronic device provided in the embodiments of this application. Detailed Implementation

[0013] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0014] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0015] Existing screen aging detection technologies mainly rely on the following two methods: 1. Pixel uniformity analysis method: This method involves capturing a full-screen solid color image with a camera and analyzing brightness / chromaticity deviations. However, it is greatly affected by ambient light and requires additional equipment.

[0016] 2. Current monitoring method: tracks changes in the driving current of organic light-emitting diode (OLED) pixels to predict aging, but cannot distinguish between current differences caused by ambient temperature and screen aging.

[0017] The aforementioned screen aging detection technologies all lead to inaccurate screen aging detection results. Therefore, this application provides a screen aging detection method, apparatus, and electronic device that can filter out ambient light interference, effectively eliminate measurement errors caused by ambient light fluctuations, and thus improve the accuracy of screen aging degree prediction.

[0018] The screen aging detection method provided in this application will be described below with reference to the accompanying drawings, through specific embodiments and application scenarios.

[0019] like Figure 1 As shown in the figure, this application provides a screen aging detection method, which may specifically include the following steps: Step 101: Obtain the detection values ​​of multiple photosensitive channels corresponding to each detection screen, wherein the detection screen includes a black detection screen and multiple reference color detection screens.

[0020] There are many reasons for screen aging, including degradation of organic materials, cathode oxidation, backlight module attenuation, and packaging failure. Under the influence of these factors, the transmittance decreases, pixel brightness deteriorates, and current distribution becomes uneven, which in turn affects the measurement value of screen aging by the photosensitive chip (Integrated Circuit, IC), thereby reducing the accuracy of the photosensitive compensation model and affecting the actual backlight experience.

[0021] When the screen displays the same color and backlight level, the measurement values ​​of the photosensitive IC will vary depending on the degree of aging. Considering the influence of ambient light, different colors of the detection screen need to be switched frequently within a cycle to ensure that the ambient light is the same for two consecutive detection screens. Utilizing this principle, different colors of the detection screen are switched at a frequency exceeding a preset frequency (e.g., 100Hz or 200Hz) to collect the detection values ​​of multiple photosensitive channels corresponding to different colors of the detection screen under the same backlight level.

[0022] The driving circuit design employs a dual-buffered frame switching method. While color buffer frame A displays the current color frame (i.e., the detection screen for the current color), the next color frame (the detection screen for the next color) is pre-written into color buffer frame B, reducing the latency of color switching. Timing control uses a hardware timer to trigger precise timing. A sampling signal is emitted 3ms after the current color detection screen is displayed (this is just an example and can be set as needed), acquiring the detection values ​​of the five photosensitive channels (C, RGB, W) of the currently displayed detection screen.

[0023] Regarding color selection, the detection screens that switch sequentially within one cycle consist of multiple reference color detection screens and a black detection screen. The multiple reference color detection screens include: a white (W) detection screen (i.e., the entire screen is pure white), a red (R) detection screen (i.e., the entire screen is pure red), a green (G) detection screen (i.e., the entire screen is pure green), and a blue (B) detection screen (i.e., the entire screen is pure blue). A frequency of 200Hz is chosen to minimize human visual perception. The detection values ​​for the five photosensitive channels corresponding to the white detection screen are: The detection values ​​of the five photosensitive channels corresponding to the red detection screen are: The detection values ​​of the five photosensitive channels corresponding to the green detection screen are: The detection values ​​of the five photosensitive channels corresponding to the blue detection screen are: The detection values ​​of the five photosensitive channels corresponding to the black detection screen are: .

[0024] For example, such as Figure 2 As shown, the current interface displays a "Settings" control 21. Clicking the "Settings" control 21 displays a "Screen Aging Detection" control 22. Clicking the "Screen Aging Detection" control 22 displays a "Start Detection" control 23. Clicking the "Start Detection" control 23 starts the automated screen aging detection. Once the detection begins, the screen switches colors at a high frequency, displaying white, red, green, blue, and black detection images respectively. Figure 3 As shown, the detection values ​​of each photosensitive channel corresponding to the detection screen are read by the photosensitive IC.

[0025] Step 102: Based on the detection values ​​of each photosensitive channel corresponding to each reference color detection screen and the detection values ​​of each photosensitive channel corresponding to the black detection screen, obtain the screen light components of each photosensitive channel corresponding to each reference color detection screen.

[0026] The detection values ​​of each photosensitive channel corresponding to each reference color detection screen obtained by the photosensitive IC are the superposition values ​​of ambient light and screen light. The high-frequency switching is to keep the ambient light the same. The black detection screen is used to filter out ambient light interference, thereby obtaining the screen light component of each photosensitive channel of each reference color detection screen.

[0027] Specifically, the detection values ​​of each photosensitive channel of each reference color detection image acquired in step 101 include ambient light interference components. To filter out ambient light, a black detection image is inserted in each cycle to correct zero-point drift. Since the color switching frequency is relatively fast, the ambient light within one cycle can be equated to a fixed value. Subtracting the detection values ​​of each photosensitive channel corresponding to the black detection image from the detection values ​​of each photosensitive channel corresponding to each reference color detection image within that cycle yields the screen light component of each photosensitive channel corresponding to each reference color detection image. Taking the C photosensitive channel of the white detection image as an example:

[0028] in, This represents the screen light component of the C photosensitive channel of the white detection image; This represents the detection value of the C photosensitive channel in the white detection image; This represents the detection value of the C photosensitive channel in the black detection image.

[0029] The screen light component of the C photosensitive channel of the white detection screen is obtained by subtracting the detection value of the C photosensitive channel of the black detection screen from the detection value of the C photosensitive channel of the white detection screen.

[0030] It should be noted that the calculation method for the screen light components of the RGBW photosensitive channels of the white detection image can be the same as the calculation method for the screen light components of the C photosensitive channel of the white detection image. Similarly, the calculation method for the screen light components of the CRGBW photosensitive channels of the red, green, and blue detection images can all be the same as the calculation method for the screen light components of the C photosensitive channel of the white detection image. This yields the screen light components of the CRGBW photosensitive channels for each reference color detection image.

[0031] Step 103: Obtain the screen aging test results based on the screen light components of each photosensitive channel corresponding to each reference color detection image.

[0032] Based on the screen light components of the CRGBW photosensitive channels corresponding to each reference color detection image, the screen aging detection results are obtained. These results can be expressed as an aging coefficient, indicating the degree of screen aging; a higher coefficient indicates more severe aging. The aging coefficient can be displayed on the screen as a percentage, ranging from 0 to 100%. Figure 4 The displayed 10%, such as Figure 5 The displayed 50%, such as Figure 6 80% is displayed.

[0033] In this embodiment, the detection values ​​of multiple photosensitive channels corresponding to each detection screen are obtained. The detection screens include a black detection screen and multiple reference color detection screens. The detection values ​​of each photosensitive channel corresponding to each detection screen are the superposition values ​​of ambient light and screen light. Based on the detection values ​​of each photosensitive channel corresponding to each reference color detection screen and the detection values ​​of each photosensitive channel corresponding to the black detection screen, the screen light components of each photosensitive channel corresponding to each reference color detection screen are obtained. The detection values ​​of each photosensitive channel corresponding to the black detection screen are used to filter out ambient light interference, thereby obtaining the screen light components of each photosensitive channel corresponding to each reference color detection screen after filtering out ambient light, which can effectively eliminate the measurement error caused by ambient light fluctuations. Based on the screen light components of each photosensitive channel corresponding to each reference color detection screen, the screen aging detection results are obtained, and the screen aging detection results can achieve a high degree of accuracy in predicting the screen aging degree.

[0034] In an optional specific embodiment, step 103 obtains the screen aging test result based on the screen light components of each photosensitive channel corresponding to each reference color detection image, including: Based on the average screen light component of each photosensitive channel corresponding to each reference color detection image, screen aging characteristics are obtained. The screen aging characteristics are input into the screen aging detection model to obtain the screen aging detection results.

[0035] To further eliminate ambient light fluctuation interference, N consecutive sampling periods (e.g., N equals 3) are performed to obtain the screen light components of each photosensitive channel corresponding to each reference color detection image within the N sampling periods. The average screen light component (i.e., average screen light component) is then calculated based on the screen light components of each photosensitive channel corresponding to each reference color detection image obtained within the N sampling periods. Taking the C photosensitive channel of the white detection image as an example:

[0036] in, This represents the average screen light component of the C photosensitive channel of the white detection image; The number of cycles is represented by i, where i takes any integer value between 1 and N. This represents the screen light component of the C photosensitive channel of the white detection image in the i-th cycle.

[0037] It should be noted that the calculation method for the average screen light component of the RGBW photosensitive channels of the white detection image can be the same as the calculation method for the average screen light component of the C photosensitive channel of the white detection image. Similarly, the calculation method for the average screen light component of the CRGBW photosensitive channels of the red, green, and blue detection images can all be the same as the calculation method for the average screen light component of the C photosensitive channel of the white detection image. This yields the average screen light component of the CRGBW photosensitive channels for each reference color detection image.

[0038] Based on the average screen light component of the CRGBW photosensitive channel corresponding to each reference color detection image, the screen aging characteristics are obtained and input into the screen aging detection model. The screen aging detection model automatically calculates the screen aging detection results and displays the screen aging detection results on the screen.

[0039] In one optional embodiment, the screen aging characteristics include, but are not limited to, at least one of the following four: The first item: the target screen light components of each photosensitive channel corresponding to each reference color detection image; The second item: the attenuation rate of each photosensitive channel corresponding to each reference color detection screen; The third item: the chromaticity ratio of each photosensitive channel corresponding to each other reference color detection screen, wherein the other reference color detection screen represents the reference color detection screen other than the white detection screen among multiple reference color detection screens; The fourth item: the screen color deviation value corresponding to each photosensitive channel.

[0040] Specifically, the target screen light component of the CRGBW photosensitive channel corresponding to each reference color detection image is obtained based on the screen light component of the CRGBW photosensitive channel corresponding to each reference color detection image. The attenuation rate of the CRGBW photosensitive channel corresponding to each reference color detection image is obtained based on the screen light component of the CRGBW photosensitive channel corresponding to each reference color detection image. The chromaticity ratio of the CRGBW photosensitive channel corresponding to each of the other reference color detection images (i.e., red detection image, green detection image, and blue detection image) is obtained based on the screen light component of the CRGBW photosensitive channel corresponding to each reference color detection image. The screen color deviation value corresponding to each photosensitive channel is obtained based on the screen light component of the CRGBW photosensitive channel corresponding to each reference color detection image.

[0041] In an optional specific embodiment, when the screen aging characteristics include the target screen light component of the first item, obtaining the screen aging characteristics based on the average screen light component of each photosensitive channel corresponding to each reference color detection image includes: Based on the screen light component and average screen light component of each photosensitive channel corresponding to each reference color detection image obtained in N consecutive cycles, the standard deviation of each photosensitive channel corresponding to each reference color detection image is calculated. When the standard deviation of each photosensitive channel corresponding to each reference color detection image is less than or equal to a preset threshold, the average screen light component of each photosensitive channel corresponding to each reference color detection image is determined as the target screen light component.

[0042] Specifically, the standard deviation of each photosensitive channel corresponding to each reference color detection image is calculated by using the screen light component and average screen light component of each photosensitive channel corresponding to each reference color detection image over N consecutive periods. Taking the C photosensitive channel of the white detection image as an example:

[0043] in, This represents the average screen light component of the C photosensitive channel of the white detection image; The number of cycles is represented by i, where i takes any integer value between 1 and N. This represents the screen light component of the C photosensitive channel of the white detection image in the i-th cycle; This represents the standard deviation of the C photosensitive channel in the white detection image.

[0044] It should be noted that the standard deviation of the RGBW photosensitive channels of the white detection image can be calculated using the same method as the standard deviation of the C photosensitive channel of the white detection image. Similarly, the standard deviations of the CRGBW photosensitive channels of the red, green, and blue detection images can all be calculated using the same method as the standard deviation of the C photosensitive channel of the white detection image. This yields the standard deviations of the CRGBW photosensitive channels for each reference color detection image.

[0045] The standard deviation of each photosensitive channel corresponding to each reference color detection image is compared with a preset threshold (e.g., 50 count). If the standard deviation of each photosensitive channel corresponding to each reference color detection image is less than or equal to the preset threshold, the average screen light component of each photosensitive channel corresponding to each reference color detection image is determined as the target screen light component. If the standard deviation of at least one photosensitive channel corresponding to at least one reference color detection image is greater than the preset threshold, a resampling step is triggered.

[0046] In an optional specific embodiment, when the screen aging characteristics include the attenuation rate of the second item, obtaining the screen aging characteristics based on the average screen light component of each photosensitive channel corresponding to each reference color detection image includes: Obtain the initial screen light components of each photosensitive channel corresponding to each reference color detection image; Based on the average screen light component and initial screen light component of each photosensitive channel corresponding to each reference color detection image, the attenuation rate of each photosensitive channel corresponding to each reference color detection image is calculated.

[0047] Specifically, N consecutive sampling cycles are performed at the moment the electronic device is deactivated, and the average screen light component of each photosensitive channel corresponding to each reference color detection image at the moment of deactivation is calculated. This average screen light component is then used as the initial screen light component. The attenuation rate of each photosensitive channel corresponding to each reference color detection image is calculated using the average screen light component and the initial screen light component. Taking the C photosensitive channel of the white detection image as an example:

[0048] in, This indicates the attenuation rate of the C photosensitive channel in the white detection image; This represents the average screen light component of the C photosensitive channel of the white detection image; This represents the initial screen light component of the C photosensitive channel of the white detection screen.

[0049] It should be noted that the calculation method for the attenuation rate of the RGBW photosensitive channels of the white detection image can be the same as the calculation method for the attenuation rate of the C photosensitive channel of the white detection image. Similarly, the calculation method for the attenuation rate of the CRGBW photosensitive channels of the red, green, and blue detection images can be the same as the calculation method for the attenuation rate of the C photosensitive channel of the white detection image. This yields the attenuation rate of the CRGBW photosensitive channels for each reference color detection image.

[0050] In an optional specific embodiment, when the screen aging characteristics include the chromaticity ratio of the third item, obtaining the screen aging characteristics based on the average screen light component of each photosensitive channel corresponding to each reference color detection image includes: Based on the reference color corresponding to the photosensitive chip, the target reference color detection screen is determined among multiple reference color detection screens; The chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image is obtained by comparing the average screen light component of each photosensitive channel with the average screen light component of each photosensitive channel corresponding to the target reference color detection image.

[0051] Specifically, the chromaticity ratio varies depending on the degree of screen aging. Based on the response values ​​of the photosensitive IC to different colors, the color with the highest response value is used as the reference color. The standard color detection screen corresponding to the reference color is used as the target reference color detection screen. For example, if the reference color is green, the green detection screen is the target reference detection screen.

[0052] The chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image is obtained by comparing the average screen light component of each photosensitive channel with the average screen light component of each photosensitive channel corresponding to the target reference color detection image. For example, if the reference color is green and the target detection image is a green detection image, taking the C photosensitive channel as an example:

[0053]

[0054]

[0055] in, This represents the chromaticity ratio of the C photosensitive channel corresponding to the red detection image; This represents the chromaticity ratio of the C photosensitive channel corresponding to the blue detection image; This represents the average screen light component of the C photosensitive channel corresponding to the red detection image; This represents the average screen light component of the C photosensitive channel corresponding to the green detection image; This represents the average screen light component of the C photosensitive channel corresponding to the blue detection image.

[0056] It should be noted that the calculation method for the chromaticity ratio of the RGBW photosensitive channels in the red detection image can be the same as that for the C photosensitive channel in the red detection image. Similarly, the calculation method for the chromaticity ratio of the RGBW photosensitive channels in the green detection image can be the same as that for the C photosensitive channel in the green detection image. Likewise, the calculation method for the RGBW photosensitive channels in the blue detection image can be the same as that for the C photosensitive channel in the blue detection image.

[0057] In an optional specific embodiment, when the screen aging characteristics include the screen color deviation value of the fourth item, the step of obtaining the screen aging characteristics based on the average screen light component of each photosensitive channel corresponding to each reference color detection image includes: The screen color deviation value corresponding to the photosensitive channel is calculated based on the average screen light component of the same photosensitive channel corresponding to each other reference color detection image, thus obtaining the screen color deviation value corresponding to each photosensitive channel.

[0058] Specifically, based on the average screen light components of the C photosensitive channel corresponding to the red detection image, the average screen light components of the C photosensitive channel corresponding to the green detection image, and the average screen light components of the C photosensitive channel corresponding to the blue detection image, the screen color shift value corresponding to the C photosensitive channel is calculated. Based on the average screen light components of the R photosensitive channel corresponding to the red detection image, the average screen light components of the R photosensitive channel corresponding to the green detection image, and the average screen light components of the R photosensitive channel corresponding to the blue detection image, the screen color shift value corresponding to the G photosensitive channel is calculated. Based on the average screen light components of the G photosensitive channel corresponding to the red detection image, the average screen light components of the G photosensitive channel corresponding to the green detection image, and the average screen light components of the G photosensitive channel corresponding to the blue detection image, the screen color shift value corresponding to the B photosensitive channel is calculated. Based on the average screen light component of the W photosensitive channel corresponding to the red detection image, the average screen light component of the W photosensitive channel corresponding to the green detection image, and the average screen light component of the W photosensitive channel corresponding to the blue detection image, the screen color shift value corresponding to the W photosensitive channel is calculated. Taking the C photosensitive channel as an example:

[0059]

[0060]

[0061]

[0062]

[0063] in, to , , All are different fixed conversion factors; , and This represents the three intermediate features corresponding to the C photosensitive channel; y represents the color coordinates corresponding to the C photosensitive channel; This represents the screen color shift value corresponding to the C photosensitive channel.

[0064] It should be noted that the screen color deviation values ​​corresponding to the R photosensitive channel, G photosensitive channel, B photosensitive channel, and W photosensitive channel can all be calculated using the same method as the screen color deviation value corresponding to the C photosensitive channel.

[0065] In an optional specific embodiment, step 103 inputs the screen aging features into the screen aging detection model to obtain the screen aging detection result, including: The target screen light component and attenuation rate of each photosensitive channel corresponding to each reference color detection image, the chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image, and the screen color deviation value corresponding to each photosensitive channel are respectively input into the screen aging detection model to obtain the first intermediate feature, the second intermediate feature, the third intermediate feature and the fourth intermediate feature. The first intermediate feature, the second intermediate feature, the third intermediate feature, and the fourth intermediate feature are concatenated to obtain the concatenated feature; The splicing features are passed through the first fully connected layer and the second fully connected layer respectively to obtain the screen aging detection results.

[0066] Specifically, such as Figure 7 As shown, to avoid feature confusion caused by direct splicing, the four sets of screen aging features are fed into an independent branch 2 in the screen aging detection model for separate processing. The target screen light components of CRGBW corresponding to the white detection image, the red detection image, the green detection image, and the blue detection image are normalized and then used as input vectors into the screen aging detection model to obtain the first intermediate feature.

[0067] The attenuation rates of CRGBW corresponding to the white detection image, the red detection image, the green detection image, and the blue detection image are used as input vectors into the screen aging detection model to obtain the second intermediate feature.

[0068] The chromaticity ratios of CRGBW corresponding to the red detection image, the green detection image, and the blue detection image are used as input vectors and fed into the screen aging detection model to obtain the third intermediate feature.

[0069] The screen color deviation values ​​corresponding to the C photosensitive channel, R photosensitive channel, G photosensitive channel, B photosensitive channel, and W photosensitive channel are used as input vectors and input into the screen aging detection model to obtain the fourth intermediate feature.

[0070] The first, second, third, and fourth intermediate features are concatenated (in...). Figure 7 (represented by F in the diagram) to obtain the splicing features. The splicing features are then passed through a first fully connected layer with 32 neurons and a second fully connected layer with 1 neuron to obtain the screen aging detection results.

[0071] It should be noted that the training method of the screen aging detection model is as follows: obtain screen aging feature samples (i.e., targets) and corresponding actual screen aging detection results, input the screen aging feature samples into the initial screen aging detection model before training to obtain the predicted screen aging detection results, calculate the loss value based on the actual screen aging detection results and the predicted screen aging detection results, and iteratively train the initial screen aging detection model based on the loss value until the convergence condition is met to obtain the trained screen aging detection model.

[0072] In an optional specific embodiment, the steps of inputting the target screen light component and attenuation rate of each photosensitive channel corresponding to each reference color detection image, the chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image, and the screen color deviation value corresponding to each photosensitive channel into the screen aging detection model to obtain the first intermediate feature, the second intermediate feature, the third intermediate feature, and the fourth intermediate feature specifically include: The target screen light components of each photosensitive channel corresponding to each reference color detection image are input into the screen aging detection model, and the first intermediate features are obtained after passing through the first convolutional layer and the first global average pooling layer. The attenuation rate of each photosensitive channel corresponding to each reference color detection image is input into the screen aging detection model, and the second intermediate feature is obtained after passing through the second convolutional layer and the second global average pooling layer. The chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image is input into the screen aging detection model, and the third intermediate feature is obtained after passing through the third convolutional layer and the third global average pooling layer. The screen color deviation value corresponding to each photosensitive channel is input into the screen aging detection model, and the fourth intermediate feature is obtained after passing through the third fully connected layer.

[0073] Specifically, such as Figure 7 As shown, to avoid feature confusion caused by direct splicing, the four sets of screen aging features are fed into an independent branch 2 in the screen aging detection model for separate processing. The target screen light components (CRGBW) corresponding to the white detection image, red detection image, green detection image, and blue detection image are normalized and then used as input vectors into the screen aging detection model. After passing through the shallow feature extraction branch 1, the first intermediate feature is obtained. The shallow feature extraction branch 1 consists of a one-dimensional convolutional layer Conv1D (i.e., the first convolutional layer) with 16 kernels and a kernel size of 3, and a first global average pooling (GAP) layer. That is, the four sets of 5-dimensional feature vectors are input vectors into the screen aging detection model, and after passing through the first convolutional layer, the first intermediate feature is obtained. The features are then obtained through the first global average pooling layer. The first intermediate feature.

[0074] The attenuation rates of CRGBW corresponding to the white, red, green, and blue detection images are used as input vectors into the screen aging detection model. After passing through the second shallow feature extraction branch, the second intermediate feature is obtained. This branch consists of a one-dimensional convolutional layer Conv1D (the second convolutional layer) with 16 kernels and a kernel size of 3, and a second global average pooling layer. In other words, four sets of 5-dimensional feature vectors are input into the screen aging detection model and passed through the second convolutional layer to obtain... The characteristics are then obtained through a second global average pooling layer. The second intermediate feature.

[0075] The chromaticity ratios of the red, green, and blue detection images (corresponding to CRGBW) are input vectors into the screen aging detection model. After passing through the third shallow feature extraction branch, the third intermediate feature is obtained. This branch consists of a one-dimensional convolutional layer Conv1D (the third convolutional layer) with 8 kernels and a kernel size of 3, and a third global average pooling layer. In other words, these three sets of 5-dimensional feature vectors are input vectors into the screen aging detection model and, after passing through the third convolutional layer, the resulting chromaticity ratios are obtained. The characteristics are then obtained through a third global average pooling layer. The third intermediate feature.

[0076] The screen color deviation values ​​corresponding to the C, R, G, B, and W photosensitive channels are input as input vectors into the screen aging detection model. After passing through the fourth shallow feature extraction branch, a fourth intermediate feature is obtained. This fourth shallow feature extraction branch consists of a first fully connected layer (Dense) with 8 neurons. Specifically, a set of 5-dimensional feature vectors is input as input vectors into the screen aging detection model, and after passing through the first fully connected layer, the fourth intermediate feature is obtained. The fourth intermediate feature.

[0077] Will First intermediate feature The second intermediate feature The third intermediate feature and The fourth intermediate feature is used for feature concatenation (in Figure 7 (represented by F in Chinese) to obtain The splicing characteristics. The splicing features are passed through a second fully connected layer with 32 neurons and a third fully connected layer with 1 neuron to obtain the screen aging detection results.

[0078] like Figure 8 As shown, the process of obtaining the screen aging test results described above will be explained below through a specific embodiment: Step 801: Within one cycle, the detection screens of different colors are switched sequentially for display, and the detection values ​​of the CRGBW photosensitive channels corresponding to the white, red, green, blue, and black detection screens are obtained respectively.

[0079] Step 802: Calculate the screen light components of the CRGBW photosensitive channels corresponding to the white detection screen, red detection screen, green detection screen, and blue detection screen, respectively.

[0080] Step 803: Calculate the target screen light components of the CRGBW photosensitive channel corresponding to the white detection screen, red detection screen, green detection screen, and blue detection screen respectively.

[0081] Step 804: Calculate the attenuation rate of the CRGBW photosensitive channel corresponding to the white detection screen, red detection screen, green detection screen, and blue detection screen respectively.

[0082] Step 805: Calculate the chromaticity ratio of the CRGBW photosensitive channels corresponding to the red detection screen, green detection screen, and blue detection screen, respectively.

[0083] Step 806: Calculate the screen color shift values ​​corresponding to the CRGBW photosensitive channels respectively.

[0084] Step 807: Input the target screen light component, attenuation rate, chromaticity ratio, and screen color deviation value into the screen aging detection model to obtain the screen aging detection results.

[0085] In an optional specific embodiment, after obtaining the screen aging test result in step 103, the method further includes: Displays the screen aging level corresponding to the screen aging test results, or displays screen usage recommendations corresponding to the screen aging level corresponding to the screen aging test results.

[0086] Specifically, after obtaining the screen aging test results, the system can also display the corresponding screen aging level based on the results. For screen aging test results between 0% and 30%, a message indicating "Good screen aging" will be displayed. Figure 4 As shown. Screen aging test results between 30% and 60% display a "High Screen Aging Level" message, such as... Figure 5 As shown. Screen aging test results between 60% and 100% will display "Severe screen aging," as indicated. Figure 6 As shown.

[0087] like Figure 9 As shown, if the system receives the first input from the user to the information icon 24 next to the screen aging test result (i.e., clicking to input), it will respond to the first input by displaying screen usage suggestions corresponding to the screen aging level (e.g., appropriately reducing screen brightness, avoiding displaying static content for a long time, and regularly updating the system) as well as detailed information about the screen aging test result (e.g., the aging coefficient will gradually increase with the increase of usage time). This will allow the user to use the screen reasonably according to the suggestions and improve the screen's lifespan. It can also display information such as screen lifespan and transaction value.

[0088] In one optional embodiment, if the screen aging level is a preset level, a prompt message indicating the screen repair location is displayed.

[0089] If the screen aging level is a preset level (e.g., high screen aging, severe screen aging), the screen repair location will be displayed on the test completion screen, and a "Screen Maintenance and Replacement" control 25 will pop up. Figure 10 As shown, when a user clicks the "Screen Maintenance and Replacement" control 25, the system displays nearby repair service stations. The user can select the corresponding station to view its relevant information so that the user can have their screen repaired and maintained in a timely manner.

[0090] In summary, the embodiments of this application reuse existing photosensitive ICs and screen driving circuits, achieving screen aging prediction without the need for additional spectrometers or high-precision current sensors, thus reducing hardware dependence. Utilizing the high-frequency switching of the screen's own white, red, green, and blue + black detection images, the photosensitive IC acquires the detection values ​​of the photosensitive channels for the corresponding detection images. The detection values ​​of the photosensitive channels for the black detection images are used to eliminate measurement errors caused by ambient light fluctuations. Screen aging characteristics are obtained through the screen's light components and input into the screen aging detection model to achieve high-accuracy detection of screen aging results. Screen aging degree prediction can be achieved automatically without other external equipment, thereby assessing information such as screen lifespan and transaction value, improving real-time performance, and allowing users and manufacturers to quickly and accurately assess the degree of screen aging.

[0091] The screen aging detection method provided in this application can be executed by a screen aging detection device. This application uses a screen aging detection device executing the screen aging detection method as an example to illustrate the screen aging detection device provided in this application.

[0092] like Figure 11 As shown in the figure, this application embodiment also provides a screen aging detection device 1100, which specifically includes: The acquisition module 1101 is used to acquire the detection values ​​of multiple photosensitive channels corresponding to each detection screen, wherein the detection screen includes a black detection screen and multiple reference color detection screens; Based on the detection values ​​of each photosensitive channel corresponding to each reference color detection image and the detection values ​​of each photosensitive channel corresponding to the black detection image, the screen light component of each photosensitive channel corresponding to each reference color detection image is obtained. Based on the screen light components of each photosensitive channel corresponding to each reference color detection image, the screen aging detection results are obtained.

[0093] Optionally, when the acquisition module 1101 acquires the screen aging detection result based on the screen light components of each photosensitive channel corresponding to each reference color detection image, it is specifically used for: Based on the average screen light component of each photosensitive channel corresponding to each reference color detection image, screen aging characteristics are obtained. The screen aging characteristics are input into the screen aging detection model to obtain the screen aging detection results.

[0094] Optionally, the screen aging characteristics include at least one of the following: The target screen light components of each photosensitive channel corresponding to each reference color detection image; The attenuation rate of each photosensitive channel corresponding to each reference color detection screen; The chromaticity ratio of each photosensitive channel corresponding to each other reference color detection screen, wherein the other reference color detection screen represents the reference color detection screen other than the white detection screen among multiple reference color detection screens; The screen color deviation value corresponding to each photosensitive channel.

[0095] Optionally, when the screen aging characteristics include a decay rate, the acquisition module 1101, when acquiring screen aging characteristics based on the average screen light component of each photosensitive channel corresponding to each reference color detection image, is specifically used for: Obtain the initial screen light components of each photosensitive channel corresponding to each reference color detection image; Based on the average screen light component and initial screen light component of each photosensitive channel corresponding to each reference color detection image, the attenuation rate of each photosensitive channel corresponding to each reference color detection image is calculated.

[0096] Optionally, when the screen aging characteristics include chromaticity ratios, the acquisition module 1101, when acquiring screen aging characteristics based on the average screen light component of each photosensitive channel corresponding to each reference color detection image, is specifically used for: Based on the reference color corresponding to the photosensitive chip, the target reference color detection screen is determined among multiple reference color detection screens; The chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image is obtained by comparing the average screen light component of each photosensitive channel with the average screen light component of each photosensitive channel corresponding to the target reference color detection image.

[0097] Optionally, when the screen aging characteristics include screen color deviation, the acquisition module 1101, when acquiring the screen aging characteristics based on the average screen light component of each photosensitive channel corresponding to each reference color detection image, is specifically used for: The screen color deviation value corresponding to the photosensitive channel is calculated based on the average screen light component of the same photosensitive channel corresponding to each other reference color detection image, thus obtaining the screen color deviation value corresponding to each photosensitive channel.

[0098] Optionally, when the acquisition module 1101 inputs the screen aging features into the screen aging detection model to obtain the screen aging detection result, it is specifically used for: The target screen light component and attenuation rate of each photosensitive channel corresponding to each reference color detection image, the chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image, and the screen color deviation value corresponding to each photosensitive channel are respectively input into the screen aging detection model to obtain the first intermediate feature, the second intermediate feature, the third intermediate feature and the fourth intermediate feature. The first intermediate feature, the second intermediate feature, the third intermediate feature, and the fourth intermediate feature are concatenated to obtain the concatenated feature; The splicing features are passed through the first fully connected layer and the second fully connected layer respectively to obtain the screen aging detection results.

[0099] Optionally, when the acquisition module 1101 inputs the target screen light component and attenuation rate of each photosensitive channel corresponding to each reference color detection image, the chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image, and the screen color deviation value corresponding to each photosensitive channel into the screen aging detection model to obtain the first intermediate feature, the second intermediate feature, the third intermediate feature, and the fourth intermediate feature, it is specifically used for: The target screen light components of each photosensitive channel corresponding to each reference color detection image are input into the screen aging detection model, and the first intermediate features are obtained after passing through the first convolutional layer and the first global average pooling layer. The attenuation rate of each photosensitive channel corresponding to each reference color detection image is input into the screen aging detection model, and the second intermediate feature is obtained after passing through the second convolutional layer and the second global average pooling layer. The chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image is input into the screen aging detection model, and the third intermediate feature is obtained after passing through the third convolutional layer and the third global average pooling layer. The screen color deviation value corresponding to each photosensitive channel is input into the screen aging detection model, and the fourth intermediate feature is obtained after passing through the third fully connected layer.

[0100] Optionally, after the acquisition module 1101 acquires the screen aging test result, the device further includes: Display module 1102 is used to display the screen aging level corresponding to the screen aging test result, or to display screen usage suggestions corresponding to the screen aging level corresponding to the screen aging test result.

[0101] The screen aging detection device in this application embodiment can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the device.

[0102] The screen aging detection device in this application embodiment can be a device with an operating system. The operating system can be Android, iOS, or other possible operating systems, and this application embodiment does not specifically limit it.

[0103] The screen aging detection device provided in this application embodiment can achieve... Figures 1 to 10 The various processes implemented in the method implementation examples will not be described again here to avoid repetition.

[0104] Optionally, such as Figure 12 As shown, this application embodiment also provides an electronic device 1200, including a processor 1201 and a memory 1202. The memory 1202 stores a program or instructions that can run on the processor 1201. When the program or instructions are executed by the processor 1201, they implement the various steps of the above-described screen aging detection method embodiment and can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0105] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0106] Figure 13 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of this application. The electronic device 1000 includes, but is not limited to, the following components: radio frequency unit 1001, network module 1002, audio output unit 1003, input unit 1004, sensor 1005, display unit 1006, user input unit 1007, interface unit 1008, memory 1009, and processor 1010.

[0107] Those skilled in the art will understand that the electronic device 1000 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 1010 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 13 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0108] The processor 1010 is used to acquire the detection values ​​of multiple photosensitive channels corresponding to each detection screen, and the detection screen includes a black detection screen and multiple reference color detection screens. Based on the detection values ​​of each photosensitive channel corresponding to each reference color detection image and the detection values ​​of each photosensitive channel corresponding to the black detection image, the screen light component of each photosensitive channel corresponding to each reference color detection image is obtained. Based on the screen light components of each photosensitive channel corresponding to each reference color detection image, the screen aging detection results are obtained.

[0109] Optionally, when the processor 1010 obtains the screen aging detection results based on the screen light components of each photosensitive channel corresponding to each reference color detection image, it is specifically used for: Based on the average screen light component of each photosensitive channel corresponding to each reference color detection image, screen aging characteristics are obtained. The screen aging characteristics are input into the screen aging detection model to obtain the screen aging detection results.

[0110] Optionally, the screen aging characteristics include at least one of the following: The target screen light components of each photosensitive channel corresponding to each reference color detection image; The attenuation rate of each photosensitive channel corresponding to each reference color detection screen; The chromaticity ratio of each photosensitive channel corresponding to each other reference color detection screen, wherein the other reference color detection screen represents the reference color detection screen other than the white detection screen among multiple reference color detection screens; The screen color deviation value corresponding to each photosensitive channel.

[0111] Optionally, when the screen aging characteristics include a decay rate, the processor 1010, when acquiring the screen aging characteristics based on the average screen light component of each photosensitive channel corresponding to each reference color detection image, specifically uses the following methods: Obtain the initial screen light components of each photosensitive channel corresponding to each reference color detection image; Based on the average screen light component and initial screen light component of each photosensitive channel corresponding to each reference color detection image, the attenuation rate of each photosensitive channel corresponding to each reference color detection image is calculated.

[0112] Optionally, when the screen aging characteristics include a chromaticity ratio, the processor 1010, when acquiring the screen aging characteristics based on the average screen light component of each photosensitive channel corresponding to each reference color detection image, specifically uses the following methods: Based on the reference color corresponding to the photosensitive chip, the target reference color detection screen is determined among multiple reference color detection screens; The chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image is obtained by comparing the average screen light component of each photosensitive channel with the average screen light component of each photosensitive channel corresponding to the target reference color detection image.

[0113] Optionally, when the screen aging characteristics include screen color deviation, the processor 1010, when acquiring the screen aging characteristics based on the average screen light component of each photosensitive channel corresponding to each reference color detection image, specifically uses the following methods: The screen color deviation value corresponding to the photosensitive channel is calculated based on the average screen light component of the same photosensitive channel corresponding to each other reference color detection image, thus obtaining the screen color deviation value corresponding to each photosensitive channel.

[0114] Optionally, when the processor 1010 inputs the screen aging features into the screen aging detection model to obtain the screen aging detection result, it is specifically used for: The target screen light component and attenuation rate of each photosensitive channel corresponding to each reference color detection image, the chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image, and the screen color deviation value corresponding to each photosensitive channel are respectively input into the screen aging detection model to obtain the first intermediate feature, the second intermediate feature, the third intermediate feature and the fourth intermediate feature. The first intermediate feature, the second intermediate feature, the third intermediate feature, and the fourth intermediate feature are concatenated to obtain the concatenated feature; The splicing features are passed through the first fully connected layer and the second fully connected layer respectively to obtain the screen aging detection results.

[0115] Optionally, when the processor 1010 inputs the target screen light component and attenuation rate of each photosensitive channel corresponding to each reference color detection image, the chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image, and the screen color deviation value corresponding to each photosensitive channel into the screen aging detection model to obtain the first intermediate feature, the second intermediate feature, the third intermediate feature, and the fourth intermediate feature, it is specifically used for: The target screen light components of each photosensitive channel corresponding to each reference color detection image are input into the screen aging detection model, and the first intermediate features are obtained after passing through the first convolutional layer and the first global average pooling layer. The attenuation rate of each photosensitive channel corresponding to each reference color detection image is input into the screen aging detection model, and the second intermediate feature is obtained after passing through the second convolutional layer and the second global average pooling layer. The chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image is input into the screen aging detection model, and the third intermediate feature is obtained after passing through the third convolutional layer and the third global average pooling layer. The screen color deviation value corresponding to each photosensitive channel is input into the screen aging detection model, and the fourth intermediate feature is obtained after passing through the third fully connected layer.

[0116] Optionally, after the processor 1010 obtains the screen aging detection result, the display unit 1006 is specifically used for: Displays the screen aging level corresponding to the screen aging test results, or displays screen usage recommendations corresponding to the screen aging level corresponding to the screen aging test results.

[0117] It should be understood that, in this embodiment, the input unit 1004 may include a graphics processing unit (GPU) 10041 and a microphone 10042. The GPU 10041 processes image data of still images or videos obtained by an image capture device (such as a camera) in video capture mode or image capture mode. The display unit 1006 may include a display panel 10061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, etc. The user input unit 1007 includes at least one of a touch panel 10071 and other input devices 10072. The touch panel 10071 is also called a touch screen. The touch panel 10071 may include a touch detection device and a touch controller. Other input devices 10072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, joysticks, etc., which will not be described in detail here.

[0118] The memory 1009 can be used to store software programs and various data. The memory 1009 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 1009 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 1009 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0119] The processor 1010 may include one or more processing units; optionally, the processor 1010 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into the processor 1010.

[0120] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described screen aging detection method embodiments and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0121] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0122] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described screen aging detection method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0123] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0124] This application provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the screen aging detection method embodiment described above, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0125] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0126] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0127] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for detecting screen aging, characterized in that, include: The detection values ​​of multiple photosensitive channels corresponding to each detection screen are obtained, and the detection screen includes a black detection screen and multiple reference color detection screens; Based on the detection values ​​of each photosensitive channel corresponding to each reference color detection image and the detection values ​​of each photosensitive channel corresponding to the black detection image, the screen light component of each photosensitive channel corresponding to each reference color detection image is obtained. Based on the screen light components of each photosensitive channel corresponding to each reference color detection image, the screen aging detection results are obtained.

2. The method according to claim 1, characterized in that, The process of obtaining screen aging test results based on the screen light components of each photosensitive channel corresponding to each reference color detection image includes: Based on the average screen light component of each photosensitive channel corresponding to each reference color detection image, screen aging characteristics are obtained. The screen aging characteristics are input into the screen aging detection model to obtain the screen aging detection results.

3. The method according to claim 2, characterized in that, The screen aging characteristics include at least one of the following: The target screen light components of each photosensitive channel corresponding to each reference color detection image; The attenuation rate of each photosensitive channel corresponding to each reference color detection screen; The chromaticity ratio of each photosensitive channel corresponding to each other reference color detection screen, wherein the other reference color detection screen represents the reference color detection screen other than the white detection screen among multiple reference color detection screens; The screen color deviation value corresponding to each photosensitive channel.

4. The method according to claim 2, characterized in that, When the screen aging characteristics include a decay rate, obtaining the screen aging characteristics based on the average screen light component of each photosensitive channel corresponding to each reference color detection image includes: Obtain the initial screen light components of each photosensitive channel corresponding to each reference color detection image; Based on the average screen light component and initial screen light component of each photosensitive channel corresponding to each reference color detection image, the attenuation rate of each photosensitive channel corresponding to each reference color detection image is calculated.

5. The method according to claim 2, characterized in that, When the screen aging characteristics include the chromaticity ratio, the step of obtaining the screen aging characteristics based on the average screen light component of each photosensitive channel corresponding to each reference color detection image includes: Based on the reference color corresponding to the photosensitive chip, the target reference color detection screen is determined among multiple reference color detection screens; The chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image is obtained by comparing the average screen light component of each photosensitive channel with the average screen light component of each photosensitive channel corresponding to the target reference color detection image.

6. The method according to claim 2, characterized in that, When the screen aging characteristics include screen color deviation, the step of obtaining screen aging characteristics based on the screen light components of each photosensitive channel corresponding to each reference color detection image includes: The screen color deviation value corresponding to the photosensitive channel is calculated based on the average screen light component of the same photosensitive channel corresponding to each other reference color detection image, thus obtaining the screen color deviation value corresponding to each photosensitive channel.

7. The method according to claim 3, characterized in that, The step of inputting the screen aging features into the screen aging detection model to obtain the screen aging detection results includes: The target screen light component and attenuation rate of each photosensitive channel corresponding to each reference color detection image, the chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image, and the screen color deviation value corresponding to each photosensitive channel are respectively input into the screen aging detection model to obtain the first intermediate feature, the second intermediate feature, the third intermediate feature and the fourth intermediate feature. The first intermediate feature, the second intermediate feature, the third intermediate feature, and the fourth intermediate feature are concatenated to obtain the concatenated feature; The splicing features are passed through the first fully connected layer and the second fully connected layer respectively to obtain the screen aging detection results.

8. The method according to claim 7, characterized in that, The process involves inputting the target screen light component and attenuation rate of each photosensitive channel corresponding to each reference color detection image, the chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image, and the screen color deviation value corresponding to each photosensitive channel into the screen aging detection model to obtain the first intermediate feature, the second intermediate feature, the third intermediate feature, and the fourth intermediate feature, including: The target screen light components of each photosensitive channel corresponding to each reference color detection image are input into the screen aging detection model, and the first intermediate features are obtained after passing through the first convolutional layer and the first global average pooling layer. The attenuation rate of each photosensitive channel corresponding to each reference color detection image is input into the screen aging detection model, and the second intermediate feature is obtained after passing through the second convolutional layer and the second global average pooling layer. The chromaticity ratio of each photosensitive channel corresponding to each other reference color detection image is input into the screen aging detection model, and the third intermediate feature is obtained after passing through the third convolutional layer and the third global average pooling layer. The screen color deviation value corresponding to each photosensitive channel is input into the screen aging detection model, and the fourth intermediate feature is obtained after passing through the third fully connected layer.

9. The method according to claim 1, characterized in that, After obtaining the screen aging test results, the method further includes: Displays the screen aging level corresponding to the screen aging test results, or displays screen usage recommendations corresponding to the screen aging level corresponding to the screen aging test results.

10. A screen aging detection device, characterized in that, include: The acquisition module is used to acquire the detection values ​​of multiple photosensitive channels corresponding to each detection screen, wherein the detection screen includes a black detection screen and multiple reference color detection screens; Based on the detection values ​​of each photosensitive channel corresponding to each reference color detection image and the detection values ​​of each photosensitive channel corresponding to the black detection image, the screen light component of each photosensitive channel corresponding to each reference color detection image is obtained. Based on the screen light components of each photosensitive channel corresponding to each reference color detection image, the screen aging detection results are obtained.

11. An electronic device, characterized in that, It includes a processor and a memory, the memory storing a program or instructions that can run on the processor, the program or instructions being executed by the processor to implement the steps of the screen aging detection method as described in any one of claims 1-9.

12. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the screen aging detection method as described in any one of claims 1-9.

Images