An anti-photographing screen display control method and system based on dynamic grating interference

Abstract

The present invention relates to the field of display technology and discloses a method and system for controlling screen display to prevent filming based on dynamic grating interference. The method comprises: acquiring display screen data; identifying sensitive content areas, enhancing dynamic grating density in these areas, and generating a non-periodic dynamic grating interference pattern; acquiring ambient light parameters surrounding the display screen, and determining whether to adjust the contrast and transparency of the dynamic grating interference pattern based on the ambient light parameters; storing the adjusted dynamic grating interference pattern and characteristic index in a historical adjustment scheme, and displaying the adjusted dynamic grating interference pattern on the display screen. This application achieves protection of sensitive content through regional dynamic monitoring and differentiated interference.

Description

Technical Field

[0001] The present invention relates to the field of display technology, and in particular to a method and system for controlling an anti-shooting screen display based on dynamic grating interference. Background Art

[0002] With the rapid development of the digital age, the security of screen content has become increasingly prominent. Whether it's commercial secrets, copyrighted film and television content, or sensitive information in public places, all face the risk of being illegally filmed or recorded. Traditional information protection methods (such as encrypted transmission and rights management) mainly target data theft in digital environments, but lack effective protection against physical screen capture. Especially with the prevalence of smartphones and compact cameras, stealing screen content by taking photos or recording screens has become a major channel for information leakage.

[0003] Patent document CN117037270A discloses a screen anti-shooting system and method based on image processing. Its processing method is to monitor the environment around the display screen through a monitoring module, and trigger screen switching by identifying the human action information in the image information, thereby preventing leakage. However, this technical method relies on post-monitoring of shooting actions or environmental threats. It must first identify the risk and then trigger screen switching. There are algorithm delays in its action recognition, feature matching and other links, and the monitoring of human actions is easily affected by environmental interference, which may frequently trigger false alarms and cause unnecessary interface switching.

[0004] Therefore, it is necessary to design an anti-shooting screen display control method and system based on dynamic grating interference to solve the problems existing in the current technology. Summary of the Invention

[0005] In view of this, the present invention proposes an anti-shooting screen display control method and system based on dynamic grating interference, aiming to solve the problem of poor anti-shooting effect in the current situation.

[0006] In one aspect, the present invention provides an anti-shooting screen display control method based on dynamic grating interference, comprising:

[0007] Acquiring display screen data, dividing the display screen into N monitoring areas, and constructing a dynamic grating interference pattern based on the display screen data;

[0008] Based on the N monitoring areas, a sensitive content area is identified. When a sensitive content area is detected, the dynamic grating density is enhanced for the sensitive content area, and a non-periodic dynamic grating interference pattern is generated.

[0009] Acquiring ambient light parameters around the display screen, and determining whether to adjust the contrast and transparency of the dynamic grating interference pattern based on the ambient light parameters;

[0010] When it is determined that the dynamic grating interference pattern is to be adjusted, the dynamic grating density and the display screen data are used as characteristic indices of the ambient light parameter, the characteristic indices are compared with historical adjustment schemes, and an adjustment coefficient is determined based on the comparison result to adjust the dynamic grating interference pattern;

[0011] The adjusted dynamic grating interference pattern and characteristic index are stored in the historical adjustment scheme, and the adjusted dynamic grating interference pattern is displayed on the display screen.

[0012] Furthermore, when constructing a dynamic grating interference pattern based on the display screen data, it includes:

[0013] The display screen data includes screen resolution, screen brightness, and screen refresh rate; a change frequency of the grating interference pattern is synchronized based on the screen refresh rate, and the change frequency is greater than 60 Hz; the grating interference pattern is superimposed on normal display content with low transparency based on the screen brightness; and a pixel density of the grating interference pattern is determined based on the screen resolution;

[0014] Build a security database based on existing camera data;

[0015] The grating interference pattern includes a stripe high-frequency pattern, a dot matrix high-frequency pattern, and a grid high-frequency pattern, and the pixel density of the grating interference pattern matches the pixel spacing in the security database.

[0016] Furthermore, based on N monitoring areas, identifying sensitive content areas includes:

[0017] Storing sensitive content in the security database, the sensitive content includes text-based sensitive content, image-based sensitive content, and dynamic content-based sensitive content;

[0018] Perform word frequency statistics on the text-based sensitive content and construct a text feature vector, extract deep image features from the image-based sensitive content and construct a sensitive image feature library, and perform sensitive marking on the dynamic content-based sensitive content;

[0019] Obtain the text content in the monitoring area and perform cosine similarity comparison based on the text feature vector;

[0020] When the text content matches sensitive text, triggering a sensitive sub-region mark for the text content;

[0021] When the text content is ambiguous text, inferring its semantic risk and triggering sensitive sub-region marking based on its semantic risk;

[0022] Acquire sensitive image content within the monitoring area, extract feature vectors of the sensitive image content, compare the feature vectors of the sensitive image content with a sensitive image feature library, and trigger a sensitive sub-area marker based on the comparison results;

[0023] Acquire dynamic content-type sensitive content within the monitoring area, perform continuous inter-frame differential analysis on the dynamic content-type sensitive content data, and trigger a sensitive sub-area marker.

[0024] Furthermore, when a sensitive content area is detected, the method of increasing the dynamic grating density for the sensitive content area includes:

[0025] Based on the detected discrete sensitive sub-regions, density clustering based on Euclidean distance is performed, the adjacent or overlapping sensitive sub-regions are merged, and edge smoothing processing is performed on the merged adjacent or overlapping sensitive sub-regions;

[0026] enhancing the dynamic grating density based on the sensitive sub-region, and transitioning the dynamic grating density based on linear interpolation at the boundary between the sensitive sub-region and the non-sensitive sub-region;

[0027] Creating an independent raster layer based on the N monitoring areas, and generating a dynamic mask matrix for the N monitoring areas;

[0028] The detected sensitive sub-region and non-sensitive sub-region are marked based on the dynamic mask matrix, and the dynamic mask matrix is bound to the dynamic raster density through a shader.

[0029] Furthermore, when generating the non-periodic dynamic grating interference pattern, the method includes:

[0030] generating a dynamic rotation pattern within a predetermined time by a pseudo-random number generator based on the sensitive sub-region and the non-sensitive sub-region;

[0031] generating a non-repeating zoom pattern based on the sensitive sub-region and the non-sensitive sub-region;

[0032] Dividing the sensitive sub-area into sensitive sub-blocks, and independently running the dynamic rotation mode or the non-repetitive scaling mode based on the sensitive sub-blocks;

[0033] The dynamic grating interference pattern is merged with the content of the display screen based on Alpha blending, and the grating operation mode is re-randomized based on a preset time.

[0034] Furthermore, obtaining ambient light parameters around the display screen and determining whether to adjust the contrast and transparency of the dynamic grating interference pattern based on the ambient light parameters includes:

[0035] Obtaining light intensity based on the ambient light parameter, and dividing light levels based on the light intensity;

[0036] The light levels are divided into strong light, dim light and normal light;

[0037] When it is determined to be dark light, the contrast of the dynamic grating interference pattern is reduced and the transparency of the dynamic grating interference pattern is increased;

[0038] When it is determined to be normal light, maintaining the contrast and transparency of the current dynamic grating interference pattern;

[0039] When it is determined to be strong light, the contrast of the dynamic grating interference pattern is increased, and the transparency of the dynamic grating interference pattern is reduced.

[0040] Furthermore, comparing the characteristic index with a historical adjustment scheme and determining an adjustment coefficient according to the comparison result to adjust the dynamic grating interference pattern includes:

[0041] The historical adjustment plan includes a historical characteristic index and a historical adjustment coefficient;

[0042] Calculating the similarity between the characteristic index and each of the historical characteristic indices, and determining an adjustment coefficient based on the similarity comparison result to adjust the dynamic grating interference pattern;

[0043] When there is data in the historical adjustment scheme whose similarity to the characteristic index is greater than a similarity threshold, adjusting the dynamic grating interference pattern according to a historical adjustment coefficient corresponding to a maximum similarity value;

[0044] When there is no data in the historical adjustment scheme whose similarity with the characteristic index is greater than the similarity threshold, a similarity set is determined and the historical characteristic index corresponding to the maximum similarity in the similarity set is selected as the initial value, and the initial value is adjusted according to the remaining historical adjustment coefficients in the similarity set to obtain the adjustment coefficient to adjust the dynamic grating interference pattern.

[0045] Furthermore, determining a similarity set and selecting a historical characteristic index corresponding to a maximum similarity value in the similarity set as an initial value, and adjusting the initial value according to the remaining historical adjustment coefficients in the similarity set, includes:

[0046] evaluating the moiré coverage and readability scores of all the historical feature indices, and sorting them based on the moiré coverage and the readability scores to select the historical feature indices with the highest moiré coverage and the lowest readability scores as candidates;

[0047] Based on the candidate historical characteristic index, performing univariate iteration on grating density, transparency and dynamic speed respectively;

[0048] When the coverage difference between two adjacent iterations is less than 5%, the iteration is stopped;

[0049] The rule is solidified based on the historical characteristic index after the iteration is stopped, and the adjustment coefficient is determined based on the historical characteristic index after the rule is solidified, and the dynamic grating interference pattern is adjusted.

[0050] Furthermore, the rule solidification includes:

[0051] Take the mean of the grating density interval and round it to 5% step size;

[0052] Limit the transparency adjustment range to ≤±15%;

[0053] The dynamic speed is limited to ≤15 rpm.

[0054] Compared with existing technologies, the present invention offers the following advantages: protection of sensitive content through dynamic regional monitoring and differentiated interference. Dynamic grating density enhancement based on real-time content recognition can apply high-intensity interference to core sensitive areas, enhancing active defense against surreptitious filming. The aperiodic grating generation algorithm breaks the temporal and spatial regularity of traditional static interference patterns, making it more difficult for cameras to crack. Real-time matching of dynamic grating parameters with screen content and ambient lighting creates a multi-layered optical interference barrier, making it difficult for illegal cameras to circumvent protection through conventional parameter adjustments. Transparent overlay and regional control ensure effective protection while minimizing the impact on normal viewing. By targeting sensitive areas and reducing interference in non-sensitive areas, visual fatigue caused by uniform interference across the entire screen is avoided. Environmentally adaptive adjustment of grating transparency and contrast ensures content visibility under varying lighting conditions. Fusion analysis of ambient light parameters dynamically adjusts the grating interference effect according to lighting conditions. Interference contrast is enhanced in strong light environments and reduced in low-light conditions, ensuring robust protection in various lighting scenarios. Feature matching and parameter adjustment based on historical data, combined with random perturbations of aperiodic grating patterns, protect against cracking attempts based on multi-frame synthesis, deep learning, and other algorithms. The synchronization of dynamic parameters with the screen refresh rate eliminates protection vulnerabilities caused by timing misalignment.

[0055] On the other hand, the present application also provides an anti-shooting screen display control system based on dynamic grating interference, comprising:

[0056] an acquisition module configured to acquire display screen data, and further configured to acquire ambient light parameters around the display screen;

[0057] a determination module configured to identify a sensitive content area, and when a sensitive content area is detected, enhance the dynamic grating density for the sensitive content area and generate the non-periodic dynamic grating interference pattern, the determination module being further configured to determine whether to adjust the contrast and transparency of the dynamic grating interference pattern based on the ambient light parameter;

[0058] a storage module configured to store the adjusted dynamic grating interference pattern and characteristic index into the historical adjustment scheme;

[0059] The adjustment module is configured to use the dynamic grating density and the display screen data as characteristic indices of the ambient light parameters, compare the characteristic indices with historical adjustment schemes, and determine an adjustment coefficient based on the comparison result to adjust the dynamic grating interference pattern.

[0060] It is understandable that the above-mentioned anti-shooting screen display control method and system based on dynamic grating interference have the same beneficial effects, which will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0062] Figure 1 This is a flow chart of an anti-shooting screen display control method based on dynamic grating interference provided by an embodiment of the present invention.

[0063] Figure 2 This is a functional block diagram of an anti-shooting screen display control system based on dynamic grating interference provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0064] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0065] In some embodiments of the present application, see Figure 1 As shown, a method for controlling an anti-shooting screen display based on dynamic grating interference includes:

[0066] S100: Acquire display screen data, divide the display screen into N monitoring areas, and construct a dynamic grating interference pattern based on the display screen data.

[0067] S200: Based on N monitoring areas, a sensitive content area is identified. When a sensitive content area is detected, the dynamic grating density is enhanced for the sensitive content area, and a non-periodic dynamic grating interference pattern is generated.

[0068] S300: Acquire ambient light parameters around the display screen, and determine whether to adjust the contrast and transparency of the dynamic grating interference pattern based on the ambient light parameters.

[0069] S400: When it is determined that the dynamic grating interference pattern is to be adjusted, the dynamic grating density and the display screen data are used as characteristic indices of the ambient light parameters, the characteristic indices are compared with historical adjustment schemes, and an adjustment coefficient is determined based on the comparison result to adjust the dynamic grating interference pattern.

[0070] S500: storing the adjusted dynamic grating interference pattern and the characteristic index in a historical adjustment scheme, and displaying the adjusted dynamic grating interference pattern on a display screen.

[0071] Specifically, the screen is divided into a grid of equal areas, each analyzed independently. The displayed content (text, images, dynamic video) and pixel distribution characteristics (such as edge density and color histogram) are captured in real time. OCR is used to extract text, match it to a keyword library (such as passwords and identity information), and semantic analysis is combined to identify sensitive passages. Lightweight object detection models (such as YOLOLite) can also be used to locate sensitive elements such as faces, QR codes, and copyright logos. When a video stream window or live image is detected, it is automatically marked as a highly sensitive area. Dynamic grating interference generates a non-periodic pattern based on a chaotic model (logistic mapping) to generate random rotation angular velocity and scaling factors, disrupting temporal regularity. Perlin noise is then superimposed to deform the grating pattern and prevent spatial frequency prediction. Sensitive areas use a high-frequency, dense grating (e.g., 20% density), while non-sensitive areas have the frequency reduced or the interference is disabled. An ambient light sensor collects light intensity (lux) and color temperature (kelvin) in real time. Light levels are categorized as follows: Low light (<50 lux): grating contrast is reduced to 15% and transparency is increased to 20%. Normal light (50-1000 Lux): Maintain standard parameters. Strong light (>1000 Lux): Contrast is increased to 25%, and transparency is reduced to 10%. When constructing the feature index, the grating density distribution, sensitive area ratio, and ambient light intensity are encoded as a multi-dimensional feature vector. The cosine similarity and Euclidean distance fusion algorithm are used to retrieve the TopK similar scenario solutions from the historical library, and the adjustment coefficients of similar historical solutions are weighted averaged. The weight is determined by the matching similarity and the protection effect score. It is only stored in the historical library when the interference effect meets the standard (moiré coverage>80%, readability score<20%). If the effect of the new solution decreases after three consecutive applications, it will automatically roll back to the previous stable version. When applying this embodiment, a high refresh rate screen (≥120Hz), an ambient light sensor, and a GPU acceleration unit are deployed.

[0072] Set the N value according to the screen resolution (e.g. N=8 divides a 1080P screen into 64 135×135 pixel areas). , where W is the total screen width (in pixels), H is the total screen height (in pixels), and N is the number of single-sided partitions (e.g., N=8 means the screen is divided into 8*8=64 regions). is the i-th monitoring area, indexed by row and column and Uniquely determine that (x, y) is the pixel location. Preset sensitive keywords, logo feature vectors, sensitive videos, and more are stored in a security database. When detected, sensitive content can be compared against the security database to determine if it's sensitive. Each area independently runs OCR and target detection, outputting a sensitive content marker. This increases the density of grating interference for sensitive content areas. Simultaneously, the system captures ambient light data on the screen and adjusts the contrast, transparency, and other aspects of the grating based on the ambient light, ensuring the screen remains protected from camera capture under varying lighting conditions. When the grating (e.g., stripes or grid) on the screen approaches the spatial frequency of the camera sensor's pixel array, the superposition of the two creates a moiré pattern, blurring or distorting the captured image. Dynamic gratings break the camera's adaptability to fixed frequencies through periodic changes (such as rotation and scaling), causing moiré patterns to persist and be impossible to repair through algorithms. The human eye's persistence of vision makes it insensitive to patterns with high-frequency changes (>60Hz), and the camera's sampling frequency (usually 30-60fps) will capture the transient changes of the dynamic grating due to discrete sampling, resulting in stripes, flickering or blurring in the captured image. Through low-transparency overlay and regional control technology, dynamic gratings can be seamlessly integrated into normal display content, achieving protection functions with almost no impact on visual perception.

[0073] In some embodiments of the present application, constructing a dynamic grating interference pattern based on display screen data includes:

[0074] The display screen data includes screen resolution, screen brightness and screen refresh rate. The change frequency of the grating interference pattern is synchronized based on the screen refresh rate, and the change frequency is greater than 60Hz. The grating interference pattern is superimposed on the normal display content with low transparency based on the screen brightness, and the pixel density of the grating interference pattern is determined based on the screen resolution.

[0075] Build a security database based on existing camera data.

[0076] The grating interference pattern includes a stripe high-frequency pattern, a dot matrix high-frequency pattern, and a grid high-frequency pattern, and the pixel density of the grating interference pattern matches the pixel pitch in the security database.

[0077] As can be understood, by dynamically synchronizing the screen refresh rate with the grating pattern's frequency, the interference frequency exceeds the threshold of the human eye's persistence of vision, ensuring that the interference pattern is imperceptible to the naked eye while also forming a dynamic optical interference barrier for the camera. High-frequency, multi-modal patterns such as stripes and dots can produce moiré and pixel aliasing during image capture, disrupting the camera's ability to fully capture the screen content. Matching pixel density with display resolution ensures that the interference pattern corresponds to the physical pixel layout of the screen, further distorting the effective information in the captured image and increasing the difficulty of screen theft through optical capture. Transparent overlay control based on screen brightness adjusts interference intensity and display quality. While ensuring readability of basic display content, low-transparency overlay maintains a normal visual experience while creating an optical interference layer for the long exposure characteristics of the camera. This avoids the screen brightness attenuation problem associated with traditional privacy films and addresses the visual fatigue caused by fixed-intensity interference patterns, creating a dynamic balance between information protection and user experience. By adjusting pixel density driven by resolution parameters, the interference pattern adapts to different display specifications. For high-resolution screens, a jamming pattern with fine pixel arrangement is used, while for low-resolution devices, large-scale pattern units are automatically matched, ensuring optimal jamming effects for all display devices. The continuous updating of the security database provides a foundation for dynamic optimization of jamming strategies. By collecting and analyzing the imaging characteristics of the camera, the frequency combination and spatial distribution parameters of the jamming pattern can be adjusted specifically. Especially for advanced shooting technologies such as high-frame rate video and multi-frame synthesis, database feature analysis can be used to quickly generate targeted jamming patterns, forming a continuously evolving dynamic defense capability.

[0078] In some embodiments of the present application, identifying a sensitive content area based on N monitoring areas includes:

[0079] Sensitive content is stored in a secure database. Sensitive content includes text-based sensitive content, image-based sensitive content, and dynamic content-based sensitive content.

[0080] Perform word frequency statistics on text-related sensitive content and construct text feature vectors; extract deep image features from image-related sensitive content and build a sensitive image feature library; and mark dynamic content as sensitive.

[0081] Obtain the text content in the monitoring area and perform cosine similarity comparison based on the text feature vector.

[0082] When the text content matches the sensitive text, the sensitive sub-region mark is triggered for the text content.

[0083] When the text content is ambiguous, its semantic risk is inferred and sensitive sub-region marking is triggered based on its semantic risk.

[0084] Obtain image-sensitive content in the monitoring area, extract the feature vector of the image-sensitive content, compare the feature vector of the image-sensitive content with the sensitive image feature library, and trigger the sensitive sub-area marking based on the comparison results.

[0085] Acquire dynamic content-sensitive content within the monitoring area, perform continuous inter-frame differential analysis on dynamic content-sensitive content data, and trigger sensitive sub-area marking.

[0086] As can be understood, by storing sensitive content in a secure database, unified management of sensitive content across text, image, and dynamic content is achieved. This not only facilitates subsequent rapid retrieval and comparison, but also enhances data security and prevents sensitive information leakage. Furthermore, differentiated processing strategies are employed for different types of sensitive content, ensuring targeted and effective detection. In terms of text processing, word frequency statistics are calculated for sensitive text and text feature vectors are constructed, enabling a quantitative description of text content. This allows for rapid identification of content similar to sensitive text, triggering the marking of sensitive sub-regions. Furthermore, for ambiguous text, semantic risk inference is used to further enhance detection accuracy, avoiding missed or false positives caused by ambiguous text. In terms of image processing, deep image features are extracted and a sensitive image feature library is constructed, enabling in-depth analysis of sensitive image content. This feature vector-based comparison method can identify content similar to sensitive images, triggering the marking of sensitive sub-regions. Compared to traditional image recognition methods, this method places greater emphasis on image feature extraction and comparison, improving detection accuracy and efficiency. In terms of video stream data processing, continuous inter-frame differential analysis enables real-time monitoring of dynamic content. This allows for the timely detection, labeling, and processing of sensitive content within the video stream. While video stream data processing is more complex than static image processing, continuous inter-frame differential analysis ensures real-time and accurate detection.

[0087] In some embodiments of the present application, when a sensitive content area is detected, the dynamic grating density is enhanced for the sensitive content area, including:

[0088] Based on the detection of discrete sensitive sub-regions, density clustering is performed based on Euclidean distance, adjacent or overlapping sensitive sub-regions are merged, and edge smoothing is performed on the merged adjacent or overlapping sensitive sub-regions.

[0089] The dynamic grating density is enhanced based on the sensitive sub-region, and the dynamic grating density is transitioned based on linear interpolation at the junction of the sensitive sub-region and the non-sensitive sub-region.

[0090] Create independent raster layers based on N monitoring areas, and generate dynamic mask matrices for the N monitoring areas.

[0091] The detected sensitive sub-regions and insensitive sub-regions are marked based on the dynamic mask matrix, and the dynamic mask matrix is bound to the dynamic raster density through the shader.

[0092] Specifically, density clustering based on Euclidean distance: ,in, is the center coordinate set of the detected sensitive sub-area , is the neighborhood radius threshold (pixel distance), such as =20, is the minimum number of neighborhood points, such as =2, and finally the clustered sensitive area set is obtained , by traversing all sensitive sub-areas, marking the core points (the number of points in the neighborhood ≥ ), and then merge the adjacent core points and their neighborhood points to form clusters, and then calculate the bounding rectangle of each cluster , edge smoothing: ,in, For morphological dilation operation, use the structural element SE (such as 3*3 rectangular kernel), This is a morphological corrosion operation that eliminates jagged edges and ultimately obtains a smoothed rectangular area. , by dilating the bounding rectangle of each cluster, filling the holes, and then corroding the dilated area to restore the approximate original size and smooth the edges, and then enhancing the density of sensitive areas: ,in, For the enhanced density of sensitive areas, is the base raster density, is the enhancement coefficient, and then the transition at the junction is performed by linear interpolation: ,in, is the shortest distance (in pixels) from the pixel point (x, y) to the boundary of the sensitive area, is the width of the transition region (e.g. w = 10 pixels), and finally the transition region grating density is obtained (from Linear decay to ), by calculating the sensitive area boundary distance field , in the transition region Interpolate the density within the region and create a raster layer for each region: ,in, is the i-th monitoring area, For the region The grating density, For the region The rotation angle of (generated by the chaos model), For the region The scaling factor (driven by Perlin noise) is used to generate the image in parallel by assigning independent raster parameters (density, rotation, scale) to each monitoring area. Raster layers, dynamic mask matrix: ,in, is the dynamic mask matrix, 1 represents the sensitive area, 0 represents the non-sensitive area, To smooth the boundaries of the sensitive areas, the coordinates of the clustered and merged sensitive areas are mapped into a binary matrix to generate a mask in GPU texture format (such as an 8-bit grayscale image). Finally, the composite image is output through shader binding rendering.

[0093] In some embodiments of the present application, when generating a non-periodic dynamic grating interference pattern, the method includes:

[0094] A dynamic rotation pattern is generated within a predetermined time by a pseudo-random number generator based on the sensitive sub-region and the non-sensitive sub-region.

[0095] A non-repeating scaling pattern is generated based on the sensitive sub-region and the non-sensitive sub-region.

[0096] Sensitive sub-blocks are divided based on the sensitive sub-regions, and a dynamic rotation mode or a non-repetitive scaling mode is independently run based on the sensitive sub-blocks.

[0097] Alpha blending is used to combine dynamic grating interference patterns with the content of the display screen, and the grating operation mode is re-randomized based on a preset time.

[0098] Specifically, the pseudo-random number generator: ,in, is the rotation angle (radians) of sensitive sub-region i at time t, is the base rotation angle, is the maximum angular velocity (e.g. =π / 30 radians / frame), Based on time t and regional seed The pseudo-random number generator is generated by assigning a unique seed to each sensitive sub-region , calculate the new rotation angle for each frame to ensure that the rotation modes of adjacent areas are not synchronized and the scaling mode is non-repeated: ,in, is the scaling factor of sensitive sub-block j at time t, and are the lower and upper limits of the scaling factor, The scaling factor is obtained by calculating the 64-bit hash value after concatenating the timestamp t and the sub-block index j. The scaling factor is calculated by dividing the sensitive sub-region into M*M sub-blocks, and the hash-driven scaling factor is calculated independently for each sub-block. Then, the parameters are assigned to the sub-blocks:

[0099] ,in, is the sub-block coordinate range within the sensitive sub-region, W and H are the width and height (pixels) of the sensitive sub-region, , is the starting coordinate of the sub-block, which is determined by the position of the parent sensitive sub-region, and M is the number of sub-blocks divided on one side. Each sensitive sub-region is evenly divided into M*M sub-blocks, and a mode (such as rotation or scaling) is randomly assigned to each sub-block with a probability of 50%, and then applied. Perform dynamic rotation, apply Perform non-repeated scaling, assign independent threads to each sub-block through GPU Compute Shader, and finally use Alpha blending: ,in, Blends the original content and the raster noise for the final rendered pixel color. is the original screen pixel color (RGB value), is the dynamic grating interference value, For global transparency, the mixed color is calculated in real time using the fragment shader, with the sensitive area increased to 0.2 and the non-sensitive area reduced to 0.05. All sub-block seeds are periodically regenerated and the rotation and scale parameters are reset.

[0100] In some embodiments of the present application, obtaining ambient light parameters around the display screen and determining whether to adjust the contrast and transparency of the dynamic grating interference pattern based on the ambient light parameters includes:

[0101] The light intensity is obtained based on the ambient light parameters, and the light levels are divided based on the light intensity.

[0102] Light levels are divided into strong light, dim light and normal light.

[0103] When it is determined to be dark light, the contrast of the dynamic grating interference pattern is reduced and the transparency of the dynamic grating interference pattern is increased.

[0104] When it is determined to be normal light, the contrast and transparency of the current dynamic grating interference pattern are maintained.

[0105] When it is determined to be strong light, the contrast of the dynamic grating interference pattern is increased and the transparency of the dynamic grating interference pattern is reduced.

[0106] Specifically, in dark light environments, the contrast is reduced by 20% and the transparency is increased to 18% (not more than 25%). In normal light environments, it remains unchanged. In strong light environments, the contrast is increased by 30% (not more than 1.5 times) and the transparency is reduced to 10.5% (not less than 5%).

[0107] In some embodiments of the present application, comparing the characteristic index with the historical adjustment scheme and determining the adjustment coefficient according to the comparison result to adjust the dynamic grating interference pattern includes:

[0108] The historical adjustment plan includes the historical characteristic index and the historical adjustment coefficient.

[0109] The similarity between the characteristic index and each historical characteristic index is calculated, and the adjustment coefficient is determined according to the similarity comparison result to adjust the dynamic grating interference pattern.

[0110] When there is data in the history adjustment scheme whose similarity with the characteristic index is greater than the similarity threshold, the dynamic grating interference pattern is adjusted according to the history adjustment coefficient corresponding to the maximum similarity value.

[0111] When there is no data in the historical adjustment scheme whose similarity with the characteristic index is greater than the similarity threshold, the similarity set is determined and the historical characteristic index corresponding to the maximum similarity in the similarity set is selected as the initial value. The initial value is adjusted according to the remaining historical adjustment coefficients in the similarity set to obtain the adjustment coefficient to adjust the dynamic grating interference pattern.

[0112] Specifically, the characteristic exponent vector: ,in, is the characteristic index vector, is the ambient light intensity, is the proportion of sensitive areas, For dynamic grating average density, historical adjustment scheme: ,in, is the historical characteristic index vector, , is the historical adjustment coefficient (contrast coefficient , transparency coefficient ), and then calculate the feature similarity: ,in, For the current feature Similarity with historical plan j, To adjust the weight of coefficient differences and prevent mismatching when coefficient differences are too large, is the current grating parameter. When the threshold exceeds 0.8, it is considered a valid match. If there is a matching history solution, the optimal history coefficient is selected. If there is no matching history solution, a similar candidate set is generated, and the one with the greatest similarity is selected as the initial value. This initial value is then adjusted to obtain the adjustment coefficient to adjust the dynamic grating interference pattern.

[0113] In some embodiments of the present application, determining a similarity set and selecting a historical characteristic index corresponding to the maximum similarity value in the similarity set as an initial value, and adjusting the initial value according to the remaining historical adjustment coefficients in the similarity set include:

[0114] All historical feature indices are evaluated for moiré coverage and readability scores, and sorted based on the moiré coverage and readability scores to select the historical feature indices with the highest moiré coverage and the lowest readability scores as candidates.

[0115] Based on the candidate historical characteristic indices, univariate iterations are performed on grating density, transparency, and dynamic speed, respectively.

[0116] When the coverage difference between two adjacent iterations is less than 5%, the iteration is stopped.

[0117] The rule is solidified based on the historical characteristic index after the iteration is stopped, and the adjustment coefficient is determined based on the historical characteristic index after the rule is solidified to adjust the dynamic grating interference pattern.

[0118] In some embodiments of the present application, rule solidification includes:

[0119] The average value of the grating density interval is taken and rounded to 5% step size.

[0120] Limit transparency adjustments to ≤±15%.

[0121] Limit dynamic speed to ≤15 rpm.

[0122] Specifically, by obtaining moiré coverage and readability scores (the readability score is an indicator that quantifies the degree to which original sensitive content can be identified in screen images captured by an attacker using a camera (such as a mobile phone or camera)), we select a solution with high moiré coverage and low readability scores to ensure the maximum interference effect. We then obtain a ranking based on the overall score, select the highest historical solution, and determine its adjustment coefficient. Using the golden section method for single-variable iteration, we first control the iteration variable range and the initial grating density range: , step size is 0.05, transparency: , step size is 0.02, dynamic speed: (rev / s), with a step size of 0.5, where is the historical adjustment factor for grating density, is the historical adjustment factor for transparency, is the historical adjustment coefficient of dynamic speed. Taking grating density as an example, define the search interval: , and then calculate the trial point: , and then evaluate the objective function: , by maximizing (The higher the moiré coverage, the lower the readability score, the better), and then narrow the interval. > , then retain the interval Otherwise, keep , when the interval length When the value is less than 0.05, the iteration is stopped and the optimal value is output. The grating density, transparency and dynamic speed are iterated in turn, and only one parameter is adjusted each time. The other parameters keep the initial values of the candidate solution. Finally, the adjustment coefficient is obtained and passed to the GPU shader to adjust the grating parameters in real time.

[0123] In summary, the present invention achieves the following beneficial effects: protection of sensitive content is achieved through dynamic regional monitoring and differentiated interference. Dynamic grating density enhancement based on real-time content recognition can apply high-intensity interference to core sensitive areas, improving active defense capabilities against voyeurism. The non-periodic grating generation algorithm breaks the temporal and spatial regularity of traditional static interference patterns, increasing the difficulty of cracking the camera. The real-time matching of dynamic grating parameters with screen content and ambient lighting forms a multi-layered optical interference barrier, making it difficult for illegal cameras to circumvent protection through conventional parameter adjustments. The use of transparent overlay and regional control ensures effective protection while minimizing the impact on normal viewing. By locating sensitive areas and weakening interference in non-sensitive areas, visual fatigue caused by uniform interference across the entire screen is avoided. Environmentally adaptive adjustment of grating transparency and contrast ensures content visibility under different lighting conditions. Fusion analysis of ambient light parameters allows the grating interference effect to dynamically change with lighting conditions. Interference contrast is enhanced in strong light environments and grating visibility is reduced in low light scenes, ensuring protection stability under different lighting scenarios. Feature matching and parameter adjustment based on historical data, combined with random perturbations of aperiodic grating patterns, protect against cracking attempts based on multi-frame synthesis, deep learning, and other algorithms. The synchronization of dynamic parameters with the screen refresh rate eliminates protection vulnerabilities caused by timing misalignment.

[0124] In another preferred embodiment based on the above embodiment, refer to Figure 2 As shown, this embodiment provides an anti-shooting screen display control system based on dynamic grating interference, which is used to apply the above-mentioned anti-shooting screen display control method based on dynamic grating interference, including:

[0125] The acquisition module is configured to acquire display screen data and is further configured to acquire ambient light parameters around the display screen.

[0126] The judgment module is configured to identify sensitive content areas. When a sensitive content area is detected, the dynamic grating density is enhanced for the sensitive content area and a non-periodic dynamic grating interference pattern is generated. The judgment module is also configured to determine whether to adjust the contrast and transparency of the dynamic grating interference pattern based on ambient light parameters.

[0127] The storage module is configured to store the adjusted dynamic grating interference pattern and characteristic index into a historical adjustment scheme.

[0128] The adjustment module is configured to use the dynamic grating density and display screen data as characteristic indices of ambient light parameters, compare the characteristic indices with historical adjustment schemes, and adjust the dynamic grating interference pattern based on the adjustment coefficient determined by the comparison result.

[0129] Specifically, the acquisition module obtains screen data and ambient light parameters, identifies sensitive content areas through the judgment module, and then enhances the density of the dynamic grating in the sensitive content area. At the same time, by obtaining ambient light parameters, it determines whether to adjust the contrast and transparency. The historical schemes are stored in the storage module to facilitate subsequent judgment on whether there are similar adjustment schemes. Similar adjustment schemes can be applied, and the adjustment module determines the adjustment coefficient based on the comparison results to adjust the dynamic grating interference pattern.

[0130] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0131] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0132] These computer program instructions may also be stored in a computer-readable storage device that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable storage device produce an article of manufacture comprising an instruction device that implements the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0133] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A method for controlling screen display to prevent shooting based on dynamic grating interference, characterized in that: include: Acquiring display screen data, dividing the display screen into N monitoring areas, and constructing a dynamic grating interference pattern based on the display screen data; Based on the N monitoring areas, a sensitive content area is identified. When a sensitive content area is detected, the dynamic grating density is enhanced for the sensitive content area, and a non-periodic dynamic grating interference pattern is generated. Acquiring ambient light parameters around the display screen, and determining whether to adjust the contrast and transparency of the dynamic grating interference pattern based on the ambient light parameters; When it is determined that the dynamic grating interference pattern is to be adjusted, the dynamic grating density and the display screen data are used as characteristic indices of the ambient light parameter, the characteristic indices are compared with historical adjustment schemes, and an adjustment coefficient is determined based on the comparison result to adjust the dynamic grating interference pattern; storing the adjusted dynamic grating interference pattern and characteristic index in the historical adjustment scheme, and displaying the adjusted dynamic grating interference pattern on the display screen; When constructing a dynamic grating interference pattern based on the display screen data, the method includes: The display screen data includes screen resolution, screen brightness, and screen refresh rate; a change frequency of the grating interference pattern is synchronized based on the screen refresh rate, and the change frequency is greater than 60 Hz; the grating interference pattern is superimposed on normal display content with low transparency based on the screen brightness; and a pixel density of the grating interference pattern is determined based on the screen resolution; Build a security database based on existing camera data; The grating interference pattern includes a stripe high-frequency pattern, a dot matrix high-frequency pattern, and a grid high-frequency pattern, and the pixel density of the grating interference pattern matches the pixel spacing in the security database.

2. The anti-shooting screen display control method based on dynamic grating interference according to claim 1 is characterized in that: Based on N monitoring areas, identifying sensitive content areas includes: Storing sensitive content in the security database, the sensitive content includes text-based sensitive content, image-based sensitive content, and dynamic content-based sensitive content; Perform word frequency statistics on the text-based sensitive content and construct a text feature vector, extract deep image features from the image-based sensitive content and construct a sensitive image feature library, and perform sensitive marking on the dynamic content-based sensitive content; Obtain the text content in the monitoring area and perform cosine similarity comparison based on the text feature vector; When the text content matches sensitive text, triggering a sensitive sub-region mark for the text content; When the text content is ambiguous text, inferring its semantic risk and triggering sensitive sub-region marking based on its semantic risk; Acquire sensitive image content within the monitoring area, extract feature vectors of the sensitive image content, compare the feature vectors of the sensitive image content with a sensitive image feature library, and trigger a sensitive sub-area marker based on the comparison results; Acquire dynamic content-sensitive content within the monitoring area, perform continuous inter-frame difference analysis on the data of the dynamic content-sensitive content, and trigger a sensitive sub-area mark.

3. The anti-shooting screen display control method based on dynamic grating interference according to claim 2, characterized in that: When a sensitive content area is detected, the method further includes: Based on the detected discrete sensitive sub-regions, density clustering based on Euclidean distance is performed, the adjacent or overlapping sensitive sub-regions are merged, and edge smoothing processing is performed on the merged adjacent or overlapping sensitive sub-regions; enhancing the dynamic grating density based on the sensitive sub-region, and transitioning the dynamic grating density based on linear interpolation at the boundary between the sensitive sub-region and the non-sensitive sub-region; Creating an independent raster layer based on the N monitoring areas, and generating a dynamic mask matrix for the N monitoring areas; The detected sensitive sub-region and non-sensitive sub-region are marked based on the dynamic mask matrix, and the dynamic mask matrix is bound to the dynamic raster density through a shader.

4. The anti-shooting screen display control method based on dynamic grating interference according to claim 3 is characterized in that: When generating the non-periodic dynamic grating interference pattern, the method includes: generating a dynamic rotation pattern within a predetermined time by a pseudo-random number generator based on the sensitive sub-region and the non-sensitive sub-region; generating a non-repeating zoom pattern based on the sensitive sub-region and the non-sensitive sub-region; Dividing the sensitive sub-area into sensitive sub-blocks, and independently running the dynamic rotation mode or the non-repetitive scaling mode based on the sensitive sub-blocks; The dynamic grating interference pattern is merged with the content of the display screen based on Alpha blending, and the grating operation mode is re-randomized based on a preset time.

5. The anti-shooting screen display control method based on dynamic grating interference according to claim 4 is characterized in that: Acquiring ambient light parameters around the display screen and determining whether to adjust the contrast and transparency of the dynamic grating interference pattern based on the ambient light parameters includes: Obtaining light intensity based on the ambient light parameter, and dividing light levels based on the light intensity; The light levels are divided into strong light, dim light and normal light; When it is determined to be dark light, the contrast of the dynamic grating interference pattern is reduced and the transparency of the dynamic grating interference pattern is increased; When it is determined to be normal light, maintaining the contrast and transparency of the current dynamic grating interference pattern; When it is determined to be strong light, the contrast of the dynamic grating interference pattern is increased, and the transparency of the dynamic grating interference pattern is reduced.

6. The anti-shooting screen display control method based on dynamic grating interference according to claim 5, characterized in that: Comparing the characteristic index with a historical adjustment plan, and determining an adjustment coefficient based on the comparison result to adjust the dynamic grating interference pattern, includes: The historical adjustment plan includes a historical characteristic index and a historical adjustment coefficient; Calculating the similarity between the characteristic index and each of the historical characteristic indices, and determining an adjustment coefficient based on the similarity comparison result to adjust the dynamic grating interference pattern; When there is data in the historical adjustment scheme whose similarity to the characteristic index is greater than a similarity threshold, adjusting the dynamic grating interference pattern according to a historical adjustment coefficient corresponding to a maximum similarity value; When there is no data in the historical adjustment scheme whose similarity with the characteristic index is greater than the similarity threshold, a similarity set is determined and the historical characteristic index corresponding to the maximum similarity in the similarity set is selected as the initial value, and the initial value is adjusted according to the remaining historical adjustment coefficients in the similarity set to obtain the adjustment coefficient to adjust the dynamic grating interference pattern.

7. The anti-shooting screen display control method based on dynamic grating interference according to claim 6, characterized in that: Determining a similarity set and selecting a historical characteristic index corresponding to a maximum similarity value in the similarity set as an initial value, and adjusting the initial value according to the remaining historical adjustment coefficients in the similarity set, including: evaluating the moiré coverage and readability scores of all the historical feature indices, and sorting them based on the moiré coverage and the readability scores to select the historical feature indices with the highest moiré coverage and the lowest readability scores as candidates; Based on the candidate historical characteristic index, performing univariate iteration on dynamic grating density, transparency and dynamic speed respectively; When the coverage difference between two adjacent iterations is less than 5%, the iteration is stopped; The rule is solidified based on the historical characteristic index after the iteration is stopped, and the adjustment coefficient is determined based on the historical characteristic index after the rule is solidified, and the dynamic grating interference pattern is adjusted.

8. The anti-shooting screen display control method based on dynamic grating interference according to claim 7, characterized in that: The rule solidification includes: Taking the mean of the interval of the dynamic grating density and rounding it to 5% step size; Limit the transparency adjustment range to ≤±15%; The dynamic speed is limited to ≤15 rpm.

9. A screen display control system for preventing shooting based on dynamic grating interference, for applying the screen display control method for preventing shooting based on dynamic grating interference according to any one of claims 1 to 8, characterized in that: include: an acquisition module configured to acquire display screen data, and further configured to acquire ambient light parameters around the display screen; a determination module configured to identify a sensitive content area, and when a sensitive content area is detected, enhance the dynamic grating density for the sensitive content area and generate the non-periodic dynamic grating interference pattern, the determination module being further configured to determine whether to adjust the contrast and transparency of the dynamic grating interference pattern based on the ambient light parameter; a storage module configured to store the adjusted dynamic grating interference pattern and characteristic index into a historical adjustment scheme; The adjustment module is configured to use the dynamic grating density and the display screen data as characteristic indices of the ambient light parameters, compare the characteristic indices with historical adjustment schemes, and determine an adjustment coefficient based on the comparison result to adjust the dynamic grating interference pattern.

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