Projector polarization phenomenon detection method, device, equipment and medium

Abstract

The invention relates to the technical field of projectors, in particular to a projector polarization phenomenon detection method, device and equipment and a medium, and the method comprises the steps: obtaining a projection picture image projected to an LCD panel by a projector, preprocessing the projection picture image, obtaining a target projection picture image, and obtaining the polarization phenomenon of the projector based on a preset image algorithm; and performing feature analysis on the target projection picture image, determining the LCD polarization degree of the projector, and determining whether the projector has a polarization phenomenon according to the LCD polarization degree. It can be seen that according to the method, the preset image algorithm is used for conducting feature analysis on the target projection picture image, the LCD polarization degree of the projector is determined, whether the polarization phenomenon occurs on the projector or not is rapidly and accurately determined according to the LCD polarization degree, and therefore the detection success rate is guaranteed, the projection picture quality is improved, and the user experience feeling is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of projectors, and in particular to a method, device, equipment and medium for detecting polarization phenomena of a projector. Background Art

[0002] With the maturity of projection technology, new projection devices such as projectors have gradually become important display and entertainment devices, widely used in business offices, education and teaching, home entertainment and other occasions. However, during the use of projectors, prolonged display of static images or long-term playback in a small window can easily cause polarization of the LCD panel, resulting in color deviation, uneven brightness, or reduced contrast in the projected image.

[0003] In existing technology, manual identification is often used to check for polarization in projector LCD panels. However, this method cannot detect polarization quickly and accurately, is time-consuming and labor-intensive, and results in an insured detection success rate, significantly impacting the user experience. Therefore, how to quickly and accurately detect polarization and enhance the user experience is a pressing technical issue. Summary of the Invention

[0004] Based on this, it is necessary to address the above technical problems. The embodiments of the present invention provide a projector polarization phenomenon detection method, device, equipment and medium to solve the problem that the existing technology cannot detect polarization phenomena quickly and accurately, which greatly affects the user experience.

[0005] A first aspect of an embodiment of the present application provides a method for detecting polarization phenomenon in a projector, the method comprising: Obtaining a projection screen image projected by a projector onto an LCD panel; Preprocessing the projection screen image to obtain a target projection screen image; Based on a preset image algorithm, feature analysis is performed on the target projection screen image to determine the LCD polarization degree of the projector; Whether polarization occurs in the projector is determined according to the polarization degree of the LCD.

[0006] A second aspect of an embodiment of the present application provides a projector polarization phenomenon detection device, the projector polarization phenomenon detection device comprising: An acquisition module is used to acquire the projection screen image projected by the projector onto the LCD panel; A processing module, configured to pre-process the projection screen image to obtain a target projection screen image; An analysis module, configured to perform feature analysis on the target projection screen image based on a preset image algorithm to determine the polarization degree of the LCD of the projector; A determination module is used to determine whether the projector has a polarization phenomenon according to the polarization degree of the LCD.

[0007] In a third aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the projector polarization phenomenon detection method as described in the first aspect is implemented.

[0008] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the projector polarization phenomenon detection method as described in the first aspect is implemented.

[0009] In summary, the present invention provides a method, device, equipment, and medium for detecting polarization phenomena in a projector. The method obtains a projection screen image projected by the projector onto the LCD panel, pre-processes the projection screen image, obtains a target projection screen image, and performs feature analysis on the target projection screen image based on a preset image algorithm to determine the LCD polarization degree of the projector. Based on the LCD polarization degree, it is determined whether the projector has a polarization phenomenon. It can be seen that the present application uses a preset image algorithm to perform feature analysis on the target projection screen image to determine the LCD polarization degree of the projector, and then, based on the LCD polarization degree, quickly and accurately determines whether the projector has a polarization phenomenon, thereby ensuring the detection success rate, improving the projection image quality, and enhancing the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0011] Figure 1 This is a diagram of an application environment of a method for detecting polarization phenomenon in a projector provided by an embodiment of the present invention; Figure 2 1 is a flow chart of a method for detecting polarization phenomenon in a projector provided by one embodiment of the present invention; Figure 3 1 is a schematic structural diagram of a projector polarization phenomenon detection device provided by one embodiment of the present invention; Figure 4 It is a structural diagram of a computer device provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0012] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0013] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0014] It will also be understood that the term "and / or" used in the present description and appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0015] As used in the present specification and the appended claims, the term “if” may be interpreted as “when” or “upon” or “in response to determining”, depending on the context. Similarly, the phrase “if it is determined” or “if compared to [described condition or event]” may be interpreted as meaning “upon determination” or “in response to determination” or “upon comparison to [described condition or event]” or “in response to comparison to [described condition or event]”, depending on the context.

[0016] In addition, in the description of the present specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0017] References to "one embodiment" or "some embodiments" in the present specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present invention. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in yet other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0018] It should be understood that the order of execution of the steps in the following embodiments does not necessarily mean the order in which they are executed. The order in which each process is executed should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0019] In order to illustrate the technical solution of the present invention, specific embodiments are provided below.

[0020] In some embodiments, as Figure 1 As shown in FIG. 1 , it is an application environment diagram of a method for detecting polarization phenomenon of a projector provided by an embodiment of the present invention. The method for detecting polarization phenomenon of a projector provided by an embodiment of the present application can be applied to the following situations: Figure 1 In the application environment shown. The projector projects the picture onto the LCD panel for display. The projector can acquire the image of the LCD panel through the image acquisition unit provided thereon to obtain the projection picture image, and the projector can execute the projector polarization phenomenon detection method in each embodiment of the present application based on the projection picture image to determine whether the projector has a polarization phenomenon. Among them, the projector can be a device specially used for projection, or it can be a terminal or other device with a projection function. For example: the projector can be an ultra-short-throw projection device, and the LCD panel is a screen for presenting the picture projected by the projection device.

[0021] The projector provided in this embodiment can obtain the projection screen image projected by the projector to the LCD panel by using a single camera with ordinary resolution of 720P. No additional sensor is required to detect the projection distance. Only an ordinary 720P camera is required to detect the clarity of the projection image in real time and drive the motor for real-time focusing. No additional hardware equipment is required, which reduces the cost of the module. In addition, other functions of the camera can be expanded on this basis, such as automatic keystone correction, automatic screen entry, automatic obstacle avoidance and other functions. This application does not impose any restrictions on this.

[0022] See also Figure 2 , is a flow chart of a method for detecting polarization phenomenon of a projector provided by an embodiment of the present invention, such as Figure 2 As shown, the projector polarization phenomenon detection method can be implemented through the following steps.

[0023] S201: Acquire a projection screen image projected by a projector onto an LCD panel.

[0024] In step S201, the projector is connected to the LCD panel via HDMI, VGA, or wireless projection (such as Miracast or AirPlay). If wireless projection is used, ensure that the devices are on the same Wi-Fi network and adjust the projector output resolution so that the physical resolution of the projector and the LCD panel (such as 1920×1080) are consistent to avoid image stretching or compression. The signal can be directly transmitted to an image capture card or recording device through the projector's HDMI output interface, and then the display content of the LCD panel can be recorded using computer software (such as OBSStudio), or the screen can be photographed using an industrial camera to obtain the projected screen image projected by the projector onto the LCD panel. That is, after the projector projects the projection test screen onto the LCD panel, the projector's built-in camera can be used to capture the projection test screen to obtain the captured projection screen image. The execution entity can obtain the projection screen image without the need for additional hardware equipment, thereby reducing costs.

[0025] It should be noted that the projection screen image includes the area where the test projection screen is located (i.e., the projection screen area), and the projection screen image also includes the area outside the projection screen area (i.e., the projection screen area). The execution subject can then extract the projection screen area and the projection screen area from the captured image.

[0026] In an embodiment of the present application, by acquiring the projection screen image projected by the projector to the LCD panel, the acquisition of the projection screen image can be accurately controlled so that the polarization phenomenon can be detected more quickly for the projection screen image later, thereby improving the detection efficiency of the polarization phenomenon.

[0027] S202: Preprocessing the projection screen image to obtain a target projection screen image.

[0028] In step S202, after obtaining the projection screen image, the projection screen image is pre-processed to obtain a target projection screen image, wherein the target projection screen image is the effective information part (such as text, image, video, etc.) extracted from the projection screen, removing background noise or irrelevant areas, and then undergoing perspective transformation, color correction and other processing to ensure that the image is consistent with the actual size and color of the LCD panel.

[0029] In one embodiment of the invention, preprocessing the projection screen image to obtain a target projection screen image includes: Performing image conversion processing on the projection screen image to obtain a grayscale image; Performing image denoising on the grayscale image to obtain a denoised grayscale image; Perform image enhancement processing on the denoised grayscale image to obtain a target projection screen image.

[0030] Specifically, the projected image is converted to a grayscale image. This grayscale image is then subjected to image denoising to remove noise (e.g., Gaussian noise and salt and pepper noise) while preserving edge details, resulting in a denoised grayscale image. This denoised grayscale image is then subjected to image enhancement (e.g., contrast stretching, histogram equalization, etc.) to obtain the target projected image. This converts the acquired projected image into a grayscale image to simplify subsequent processing and reduce computational complexity. Image denoising and image enhancement are then performed to obtain the target projected image. Image denoising can utilize a median filter algorithm to remove salt and pepper noise from the image, thereby reducing its interference with feature extraction (e.g., edge detection). Alternatively, bilateral filtering or Gaussian filtering can be used to remove image noise while preserving edge details. Image enhancement can utilize histogram equalization or a CLAHE algorithm to enhance image contrast. These steps reduce computational complexity, eliminate errors and artifacts caused by noise, and improve the quality of the projected image, facilitating better recognition and analysis.

[0031] In this embodiment, the target projection screen image is obtained by preprocessing the projection screen image, thereby achieving a significant improvement in the quality of the projection screen, being able to more accurately reflect the target features, reduce misidentification and missed identification, and provide a reliable data basis for subsequent polarization phenomenon detection.

[0032] S203: Based on a preset image algorithm, perform feature analysis on the target projection screen image to determine the LCD polarization degree of the projector.

[0033] In step S203, the Sobel operator or Canny edge detection is used to extract image gradient information, capturing differences in brightness distribution caused by polarization. The gray-level co-occurrence matrix (GLCM) is used to extract texture features such as contrast and entropy, reflecting surface texture changes caused by polarization. Fourier transforms or wavelet transforms are used to analyze the image's frequency domain characteristics and identify changes in frequency components caused by polarization. The extracted gradient, texture, and frequency domain features are then fused to construct a comprehensive feature vector. A machine learning model, such as a support vector machine (SVM), random forest, or convolutional neural network (CNN), is used to train a polarization classification or regression model based on labeled data. The features of the target projected image are then input into the trained polarization detection model, which outputs a polarization value (such as polarization ratio and polarization angle). The LCD polarization value ranges from 0 to 100. This range is a standardized indicator used to measure the polarization degree of an LCD panel. When the polarization degree is 0, the LCD panel is not polarized, and the brightness, color, and other characteristics of the display remain stable. As the polarization degree gradually increases, the polarization of the LCD panel becomes increasingly severe, which may cause problems such as uneven brightness and color distortion on the display, affecting the display quality. When the polarization degree reaches 100, the polarization of the LCD panel is at its most severe, and the display may no longer display images properly and require repair or replacement. As can be seen from the above steps, the polarization degree of the LCD panel can be quantitatively evaluated, providing an important basis for LCD panel quality inspection and fault diagnosis.

[0034] In one embodiment of the invention, based on a preset image algorithm, feature analysis is performed on the target projection screen image to determine the LCD polarization degree of the projector, including: Extracting a region of interest from the target projection screen image using an image segmentation algorithm; Performing image feature extraction on the region of interest to obtain an image feature vector; The image feature vector is input into a pre-trained polarization detection model to calculate the LCD polarization degree of the projector.

[0035] Specifically, in image processing, a region of interest refers to an area in an image that we pay special attention to, namely, a ROI. For example, when analyzing the target projection screen image, the region of interest may be a specific area of the display screen, such as the center of the screen, a certain pixel block area, etc. By extracting the region of interest, we can focus on the key parts of the image, reduce the amount of data for subsequent processing, and improve processing efficiency and accuracy. It should be noted that there are many methods for extracting the region of interest, such as segmentation based on features such as color, shape, texture, or using manual annotation to determine the boundaries of the region of interest. This application does not impose any restrictions on this. After extracting the region of interest from the target projection screen image using an image segmentation algorithm, information that can represent the characteristics of the region is extracted from the region of interest. In image processing, common image features include color features (such as average color, color histogram), texture features (such as grayscale co-occurrence matrix, wavelet transform coefficients), shape features (such as contour, area, perimeter), etc.

[0036] For the target projected screen image, feature extraction aims to obtain information that reflects the display's characteristics, such as brightness distribution and color uniformity. These features are used for subsequent analysis and processing. Finally, the extracted features are combined into a vector, known as the image feature vector. An image feature vector is a mathematical representation of an image, containing key information about the image and can be used for tasks such as image classification, recognition, and retrieval. For example, for a region of interest (ROI) in a target projected screen image, we can extract its average brightness, color histogram, and texture features. These features are then combined into a feature vector. This feature vector is then input into a pre-trained polarization detection model (such as a support vector machine (SVM), random forest, or deep learning model) to calculate the projector's LCD polarization level. This method effectively utilizes image segmentation techniques to extract the ROI. Through feature extraction and modeling, efficient and accurate detection of the LCD polarization level is achieved, reducing manual intervention. By combining multi-feature fusion with a machine learning model, the accuracy of polarization detection is improved, enhancing the user experience.

[0037] In one embodiment of the invention, extracting a region of interest from the target projection screen image using an image segmentation algorithm includes: Identify the target projection screen image using an edge detection algorithm to determine edge information of the target projection screen image; Extracting contour information of the target projection screen image using a contour extraction algorithm according to edge information of the target projection screen image; Determining whether the contour information of the target projection screen image conforms to a preset contour range; If the contour information of the target projection screen image meets the preset contour range, a region of interest is extracted from the target projection screen image according to the contour information of the target projection screen image.

[0038] Specifically, Canny edge detection is a multi-stage edge detection algorithm that detects edges by finding local maxima in image gradients. The steps include Gaussian filtering, calculating gradient magnitude and direction, non-maximum suppression, dual-threshold detection, and edge connection. First, the target projection image is Gaussian filtered to smooth the image and reduce noise. The Gaussian filter convolves the target projection image with a Gaussian kernel, suppressing high-frequency noise in the target projection image. The Sobel operator is used to calculate the horizontal and vertical gradients of the target projection image, and then the gradient magnitude and direction are calculated based on the gradients. The gradient magnitude represents the intensity of the grayscale change in the image pixel, while the gradient direction represents the direction of the grayscale change. In the gradient magnitude image, only the points with the local maximum gradient magnitude are retained, while other non-maximum points are suppressed, thereby refining the edges. Two thresholds are set: pixels with a gradient magnitude greater than the high threshold are marked as strong edges, pixels with a gradient magnitude less than the low threshold are marked as non-edges, and pixels between the high and low thresholds are marked as weak edges. A complete edge image is then obtained by connecting strong edge points with adjacent weak edge points. The Canny edge detection algorithm can identify edge information in the target projected image. This edge information typically corresponds to the outline of objects in the image. This edge information may include the border of the display screen or the boundary of the projected image.

[0039] After obtaining the edge information of the target projection image, a contour extraction algorithm (such as the findContours function in OpenCV) can be used to extract the contour information of the target projection image. Contour information is a closed curve consisting of a series of continuous edge points, representing the shape of the object in the image. For each extracted contour, its area and shape characteristics (such as perimeter, circularity, and rectangularity) are calculated. The area can be obtained by counting the number of pixels within the contour, the perimeter by calculating the length of the pixels at the contour edge, and the circularity and rectangularity are calculated based on the relationship between the area and perimeter. Based on the characteristics of the projection image area, area and shape thresholds are set to determine whether the contour information of the target projection image meets the preset contour range. If the contour information of the target projection image meets the preset contour range, the contour information of the target projection image is filtered to identify the contours that meet the criteria as the region of interest (ROI). For example, the projection image area is typically large and has a nearly rectangular shape. Therefore, area and rectangularity thresholds can be set to retain only contours with large areas and high rectangularity as ROI. Through the above steps, edge detection and contour extraction can accurately identify the region of interest, avoid background interference, reduce the amount of data for subsequent image analysis, and improve the detection efficiency and accuracy of projector polarization phenomena.

[0040] It should be noted that the contour range, area threshold and rectangularity threshold can be set according to actual conditions, and this application does not impose any restrictions on this.

[0041] In one embodiment of the invention, the image feature vector is input into a pre-trained polarization detection model to calculate the LCD polarization degree of the projector, including: Input the image feature vector into a pre-trained polarization detection model to calculate the average brightness of each region of interest; Calculating the average brightness change rate of each region of interest in two adjacent images according to the average brightness of each region of interest; The LCD polarization degree of the projector is determined based on the average brightness change rate and a pre-calibrated first mapping relationship, wherein the first mapping relationship is a correspondence between the pre-calibrated average brightness change rate and the LCD polarization degree of the projector.

[0042] Specifically, the image feature vectors (such as grayscale value, color histogram, texture features, etc.) of each region of interest are input into a pre-trained polarization detection model (such as convolutional neural network CNN, support vector machine SVM, etc.), and the average brightness is calculated based on the pixel values in the region of interest. The average brightness can be obtained by averaging the brightness values of all pixels in the region. Based on the average brightness of each region of interest, the average brightness change rate of each region of interest in two adjacent images is calculated. The change rate can be obtained by calculating the ratio of the difference between the average brightness of the region in the two adjacent images to the average brightness of the previous image. For example, for the i-th and i+1-th images, the average brightness of a region of interest is respectively and , then the brightness change rate It can be expressed as: in, It is expressed as the average brightness of one of the regions of interest in the i-th image, It is expressed as the average brightness of one of the regions of interest in the i+1th image, Expressed as brightness change rate. Through a large number of experiments and analyses, the correspondence between the pre-calibrated average brightness change rate and the projector's LCD polarization degree is determined. Then, based on the average brightness change rate and the pre-calibrated first mapping relationship, the projector's LCD polarization degree is determined. For example, assuming that when the brightness change rate is 0%, the polarization degree is 0; when the brightness change rate reaches a certain threshold When the polarization degree is 100, the LCD polarization degree ranges from 0 to 100, where 0 indicates no polarization and 100 indicates the most severe polarization. Zero Polarization: When the polarization degree is 0, the LCD panel exhibits no polarization, and the display's brightness, color, and other characteristics remain stable, resulting in a good display quality. When the polarization degree is between 0 and 100, it indicates a certain degree of polarization on the LCD panel. The higher the polarization degree, the worse the display quality, potentially exhibiting problems such as uneven brightness and color distortion. When the polarization degree reaches 100, the LCD panel exhibits the most severe polarization, and the display may no longer display images properly and require repair or replacement. By analyzing the target projected image and calculating the LCD polarization degree through the above steps, the projector's LCD polarization degree can be accurately detected and quantitatively evaluated, providing an important basis for projector quality testing and fault diagnosis.

[0043] In this embodiment, by utilizing a preset image algorithm to perform feature analysis on the target projection screen image, the LCD polarization degree of the high-precision projector can be predicted, thereby effectively improving the reliability and consistency of detection, reducing manual intervention, improving efficiency, and reducing human errors.

[0044] S204: Determine whether polarization occurs in the projector according to the polarization degree of the LCD.

[0045] In step S204, after calculating the LCD polarization degree, the LCD polarization degree is mapped to a polarization degree range of 0-100%. A qualified threshold for the polarization degree (e.g., PUI < 15% is considered normal) is set based on the LCD panel's specifications or historical data. If the detected polarization degree exceeds the threshold, the projector is determined to have polarization (e.g., a faulty polarizer or abnormal liquid crystal molecular alignment). If the detected polarization degree does not exceed the threshold, the projector is determined to have no polarization.

[0046] In one embodiment of the invention, determining whether the projector has a polarization phenomenon according to the polarization degree of the LCD includes: Determining whether the LCD polarization degree exceeds a preset polarization threshold; If the polarization degree of the LCD does not exceed a preset polarization threshold, determining that the projector does not exhibit polarization; If the polarization degree of the LCD exceeds a preset polarization threshold, it is determined that the projector has a polarization phenomenon, and a refresh tool is used to refresh the LCD panel, and a warning prompt is issued to the user.

[0047] Specifically, the projector determines whether the LCD polarization level exceeds a preset threshold. If the LCD polarization level does not exceed the threshold, the projector is determined to be free of polarization. If the LCD polarization level exceeds the threshold, the projector is determined to be polarized. A refresh tool is then used to refresh the LCD panel, and a warning alert is issued to the user. For example, if the preset threshold is 70 and the LCD polarization level is 88, then 88 > 70, indicating that the projector is polarized. A prompt message is superimposed on the projected image, which may include: "LCD panel polarization detected. Automatically refreshing. Please wait patiently." This alerts the user to LCD polarization issues. The LCD polarization level is recorded for subsequent maintenance and servicing. The historical LCD polarization level record can be saved in the projector's built-in memory and used to analyze the LCD panel's service life. Through these steps, the LCD polarization level can be accurately quantified, avoiding subjective misjudgments. The refresh tool automatically refreshes the LCD panel, reducing manual user intervention. Once polarization exceeds the threshold, an alert is immediately triggered, and a user alert is issued based on the detected polarization level, raising user awareness of LCD polarization issues.

[0048] It should be noted that the preset polarization threshold can be customized and adjusted according to specific actual needs, and this application does not impose any limitation on this.

[0049] In one embodiment of the invention, refreshing an LCD panel using a refresh tool includes: Determining a playback duration of a Pixel Refresher video of the projector based on the LCD polarization degree and a pre-calibrated second mapping relationship, wherein the second mapping relationship is a correspondence between the pre-calibrated LCD polarization degree and the playback duration of the Pixel Refresher video of the projector; The LCD panel is refreshed according to the duration of the Pixel Refresher video playback of the projector.

[0050] Specifically, the correspondence between the pre-calibrated LCD polarization degree and the projector's Pixel Refresher video playback time is automatically adjusted according to the detected LCD polarization degree and the pre-calibrated second mapping relationship. The playback time is proportional to the LCD polarization degree. The higher the polarization degree, the longer the playback time. The playback time range can be set to 5-30 minutes. Then, according to the projector's automatic adjustment of the Pixel Refresher video playback time, the LCD panel is refreshed. Through the above steps, the Pixel Refresher video is used to alleviate the LCD polarization phenomenon, effectively improve the projection image quality, and extend the service life of the LCD panel.

[0051] In this embodiment, the polarization phenomenon of the projector LCD panel can be automatically detected based on the LCD polarization degree without manual intervention, thereby improving the user experience and achieving efficient and accurate detection of the projector polarization phenomenon.

[0052] In summary, the present invention provides a method, device, equipment, and medium for detecting polarization phenomena in a projector. The method obtains a projection screen image projected by the projector onto the LCD panel, pre-processes the projection screen image, obtains a target projection screen image, and performs feature analysis on the target projection screen image based on a preset image algorithm to determine the LCD polarization degree of the projector. Based on the LCD polarization degree, it is determined whether the projector has a polarization phenomenon. It can be seen that the present application uses a preset image algorithm to perform feature analysis on the target projection screen image to determine the LCD polarization degree of the projector, and then, based on the LCD polarization degree, quickly and accurately determines whether the projector has a polarization phenomenon, thereby ensuring the detection success rate, improving the projection image quality, and enhancing the user experience.

[0053] See also Figure 3 , Figure 3 Schematic diagram of the structure of the projector polarization phenomenon detection device provided by the embodiment of the present invention. The projector polarization phenomenon detection device corresponds to the projector polarization phenomenon detection method in the above embodiment. Figure 2 as well as Figure 2For the convenience of explanation, only the parts related to this embodiment are shown. Figure 3 The projector polarization phenomenon detection device 30 includes: an acquisition module 31, a processing module 32, an analysis module 33, and a determination module 34.

[0054] An acquisition module 31 is configured to acquire a projection screen image projected by a projector onto an LCD panel; The processing module 32 is used to pre-process the projection screen image to obtain a target projection screen image; An analysis module 33 is configured to perform feature analysis on the target projection screen image based on a preset image algorithm to determine the LCD polarization degree of the projector; The determination module 34 is configured to determine whether the projector has a polarization phenomenon according to the polarization degree of the LCD.

[0055] Optionally, the processing module 32 is specifically configured to: Performing image conversion processing on the projection screen image to obtain a grayscale image; Performing image denoising on the grayscale image to obtain a denoised grayscale image; Perform image enhancement processing on the denoised grayscale image to obtain a target projection screen image.

[0056] Optionally, the analysis module 33 is specifically configured to: Extracting a region of interest from the target projection screen image using an image segmentation algorithm; Performing image feature extraction on the region of interest to obtain an image feature vector; The image feature vector is input into a pre-trained polarization detection model to calculate the LCD polarization degree of the projector.

[0057] Optionally, the analysis module 33 is further configured to: Identify the target projection screen image using an edge detection algorithm to determine edge information of the target projection screen image; Extracting contour information of the target projection screen image using a contour extraction algorithm according to edge information of the target projection screen image; Determining whether the contour information of the target projection screen image conforms to a preset contour range; If the contour information of the target projection screen image meets the preset contour range, a region of interest is extracted from the target projection screen image according to the contour information of the target projection screen image.

[0058] Optionally, the analysis module 33 is further configured to: Input the image feature vector into a pre-trained polarization detection model to calculate the average brightness of each region of interest; Calculating the average brightness change rate of each region of interest in two adjacent images according to the average brightness of each region of interest; The LCD polarization degree of the projector is determined based on the average brightness change rate and a pre-calibrated first mapping relationship, wherein the first mapping relationship is a correspondence between the pre-calibrated average brightness change rate and the LCD polarization degree of the projector.

[0059] Optionally, the determination module 34 is specifically configured to: Determining whether the LCD polarization degree exceeds a preset polarization threshold; If the polarization degree of the LCD does not exceed a preset polarization threshold, determining that the projector does not exhibit polarization; If the polarization degree of the LCD exceeds a preset polarization threshold, it is determined that the projector has a polarization phenomenon, and a refresh tool is used to refresh the LCD panel, and a warning prompt is issued to the user.

[0060] Optionally, the determining module 34 is further configured to: Determining a playback duration of a Pixel Refresher video of the projector based on the LCD polarization degree and a pre-calibrated second mapping relationship, wherein the second mapping relationship is a correspondence between the pre-calibrated LCD polarization degree and the playback duration of the Pixel Refresher video of the projector; The LCD panel is refreshed according to the duration of the Pixel Refresher video playback of the projector.

[0061] It should be noted that the information interaction, execution process and other contents between the above-mentioned units are based on the same concept as the embodiment of the method of the present invention. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0062] Figure 4 This is a schematic diagram of the structure of a computer device provided by an embodiment of the present invention. Figure 4 As shown, the computer device of this embodiment includes: at least one processor ( Figure 4 Only one is shown), a memory, and a computer program stored in the memory and executable on at least one processor, wherein when the processor executes the computer program, the steps in any of the above-mentioned projector polarization phenomenon detection method embodiments are implemented.

[0063] The computer device may include, but is not limited to, a processor and a memory. Figure 4The above is merely an example of a computer device and does not constitute a limitation on the computer device. The computer device may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include a network interface, a display screen, and an input system.

[0064] In one embodiment, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by a processor in a computer device, the computer device is enabled to perform the steps of any embodiment of a projector polarization detection method disclosed in the present invention. The details are not repeated here. The computer-readable storage medium can be either non-volatile or volatile.

[0065] The processor may be a CPU, other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0066] Memory includes readable storage media, internal memory, and the like. Internal memory can be the internal memory of a computer device, providing an environment for the operation of the operating system and computer-readable instructions stored in the readable storage medium. The readable storage medium can be the computer device's hard drive. In other embodiments, it can also be an external storage device, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, or a flash memory card. Furthermore, memory can include both the computer device's internal storage unit and external storage devices. Memory is used to store the operating system, associated applications, a boot loader, data, and other programs, such as the program code of a computer program. Memory can also be used to temporarily store data that has been output or is about to be output.

[0067] It is understood by those skilled in the art that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0068] Those skilled in the art can clearly understand that for the sake of convenience and brevity in description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other and are not used to limit the scope of protection of the present invention. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here. If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0069] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, persons skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A method for detecting polarization phenomenon of a projector, characterized in that: include: Obtaining a projection screen image projected by a projector onto an LCD panel; Preprocessing the projection screen image to obtain a target projection screen image; Based on a preset image algorithm, feature analysis is performed on the target projection screen image to determine the LCD polarization degree of the projector; According to the polarization degree of the LCD, it is determined whether the projector has a polarization phenomenon.

2. The method for detecting polarization phenomenon of a projector according to claim 1, wherein: The preprocessing of the projection screen image to obtain a target projection screen image includes: Performing image conversion processing on the projection screen image to obtain a grayscale image; Performing image denoising on the grayscale image to obtain a denoised grayscale image; Perform image enhancement processing on the denoised grayscale image to obtain a target projection screen image.

3. The method for detecting polarization phenomenon of a projector according to claim 1, wherein: The step of performing feature analysis on the target projection screen image based on a preset image algorithm to determine the LCD polarization degree of the projector includes: Extracting a region of interest from the target projection screen image using an image segmentation algorithm; Performing image feature extraction on the region of interest to obtain an image feature vector; The image feature vector is input into a pre-trained polarization detection model to calculate the LCD polarization degree of the projector.

4. The method for detecting polarization phenomenon of a projector according to claim 3, wherein: The extracting the region of interest from the target projection screen image by using an image segmentation algorithm comprises: Identify the target projection screen image using an edge detection algorithm to determine edge information of the target projection screen image; Extracting contour information of the target projection screen image using a contour extraction algorithm according to edge information of the target projection screen image; Determining whether the contour information of the target projection screen image conforms to a preset contour range; If the contour information of the target projection screen image meets the preset contour range, a region of interest is extracted from the target projection screen image according to the contour information of the target projection screen image.

5. The method for detecting polarization phenomenon of a projector according to claim 3, wherein: Inputting the image feature vector into a pre-trained polarization detection model to calculate the LCD polarization degree of the projector includes: Input the image feature vector into a pre-trained polarization detection model to calculate the average brightness of each region of interest; Calculating the average brightness change rate of each region of interest in two adjacent images according to the average brightness of each region of interest; The LCD polarization degree of the projector is determined based on the average brightness change rate and a pre-calibrated first mapping relationship, wherein the first mapping relationship is a correspondence between the pre-calibrated average brightness change rate and the LCD polarization degree of the projector.

6. The method for detecting polarization phenomenon of a projector according to claim 1, wherein: The determining whether the projector has a polarization phenomenon according to the polarization degree of the LCD includes: Determining whether the LCD polarization degree exceeds a preset polarization threshold; If the polarization degree of the LCD does not exceed a preset polarization threshold, determining that the projector does not exhibit polarization; If the polarization degree of the LCD exceeds a preset polarization threshold, it is determined that the projector has a polarization phenomenon, and a refresh tool is used to refresh the LCD panel, and a warning prompt is issued to the user.

7. The method for detecting polarization phenomenon of a projector according to claim 6, wherein: The method of refreshing the LCD panel by using a refresh tool includes: Determining a playback duration of a Pixel Refresher video of the projector based on the LCD polarization degree and a pre-calibrated second mapping relationship, wherein the second mapping relationship is a correspondence between the pre-calibrated LCD polarization degree and the playback duration of the Pixel Refresher video of the projector; The LCD panel is refreshed according to the duration of the Pixel Refresher video playback of the projector.

8. A projector polarization phenomenon detection device, characterized in that: include: An acquisition module is used to acquire the projection screen image projected by the projector onto the LCD panel; A processing module, configured to pre-process the projection screen image to obtain a target projection screen image; An analysis module, configured to perform feature analysis on the target projection screen image based on a preset image algorithm to determine the LCD polarization degree of the projector; A determination module is used to determine whether the projector has a polarization phenomenon according to the polarization degree of the LCD.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the projector polarization phenomenon detection method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the projector polarization phenomenon detection method according to any one of claims 1 to 7 is implemented.

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