Display brightness adjustment optimization method and system

Abstract

The invention provides a display brightness adjustment optimization method and system, and relates to the technical field of brightness adjustment, and the method comprises the steps: obtaining a first region and a second region of the information of a region where a display is located; obtaining the relative distance of the dynamic feature information, carrying out the analysis of the shortest relative distance, obtaining an associated feature region, a combined feature region and a comprehensive feature region, and obtaining the weight setting information; obtaining a relative position variable of the dynamic feature information, performing position flow judgment and flow area judgment, and obtaining flow area judgment information; and calculating a display brightness adjustment coefficient according to the weight setting information and the brightness decay index average value, performing display brightness adjustment and updating, and obtaining display brightness updating adjustment data. According to the invention, comprehensive consideration of personnel area distribution and dynamic information in a scene can be realized, and accurate adjustment of the brightness of the display is realized.

Description

Technical Field

[0001] The present invention provides a display brightness adjustment optimization method and system, which relate to the field of brightness adjustment technology, and particularly to the field of display brightness adjustment optimization technology. Background Art

[0002] In the digital age, displays are widely used, but traditional brightness adjustment methods have significant limitations. In complex application scenarios, the display area contains multiple target features such as people and equipment. These features have different dynamic characteristics and spatial distribution, which significantly affect brightness adjustment.

[0003] Existing technologies struggle to comprehensively consider the distribution of information, such as people, when adjusting brightness. When target features dynamically change, the lack of real-time monitoring and response capabilities prevents timely brightness adjustments, impacting visual comfort and wasting energy. Different areas have varying importance in brightness adjustment, and existing technologies fail to fully account for these differences in regional weighting, failing to comprehensively adjust brightness for multiple scenarios. This results in suboptimal adjustment results. Summary of the Invention

[0004] The present invention provides a display brightness adjustment optimization method and system to solve the above problems:

[0005] The present invention provides a method and system for optimizing display brightness adjustment, the method comprising:

[0006] S1. Extract and analyze target features of the area where the display is located to obtain a comprehensive first area and a second area;

[0007] The obtaining of the comprehensive first area includes:

[0008] Obtaining the relative distance of the dynamic feature information of the regional target feature information, performing a shortest relative distance analysis on the relative distance, obtaining the associated feature area, the combined feature area and the comprehensive feature area and obtaining the weight setting information;

[0009] S2. Obtain relative position variables of dynamic feature information, perform position flow determination and flow area determination, and obtain flow area determination information;

[0010] S3. Calculate the display brightness adjustment coefficient according to the weight setting information and the average value of the brightness attenuation index, adjust and update the display brightness, and obtain display brightness update adjustment data.

[0011] Furthermore, the system includes:

[0012] A region division module is used to extract and analyze target features of the region where the display is located to obtain a comprehensive first region and a second region;

[0013] The obtaining of the comprehensive first area includes:

[0014] Obtaining the relative distance of the dynamic feature information of the regional target feature information, performing a shortest relative distance analysis on the relative distance, obtaining the associated feature area, the combined feature area and the comprehensive feature area and obtaining the weight setting information;

[0015] A flow determination module is used to obtain relative position variables of dynamic feature information, perform position flow determination and flow area determination, and obtain flow area determination information;

[0016] The brightness adjustment module is used to calculate the display brightness adjustment coefficient according to the weight setting information and the average value of the brightness attenuation index, adjust and update the display brightness, and obtain the display brightness update adjustment data.

[0017] The present invention provides the following beneficial effects: Through in-depth analysis and feature extraction of the display's regional information, the system can adjust brightness based on the characteristics and dynamic changes of each region. This brightness adjustment takes into account multiple factors, including the number, size, distance, and dynamic changes of regions, achieving a balance between energy conservation and brightness. For example, comprehensive brightness adjustments ensure that the display brightness better meets the user's actual needs and visual experience.

[0018] By acquiring the relative position variables of dynamic feature information and determining the flow area, the system can perceive dynamic changes in the display's environment in real time. When dynamic features change position, the system can promptly adjust the brightness control strategy to ensure that the display brightness always adapts to the changing environment, providing a clear and comfortable viewing experience.

[0019] The brightness adjustment coefficient is calculated by combining weight settings and the average brightness decay index, making brightness adjustment more precise and standardized. The weight settings highlight the importance of different areas to brightness adjustment, while the average brightness decay index takes into account the natural decay of brightness with factors such as distance, thus avoiding blindness and inaccuracy in brightness adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A schematic diagram of a display brightness adjustment optimization method. DETAILED DESCRIPTION

[0021] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0022] One embodiment of the present invention provides a method and system for optimizing display brightness adjustment, the method comprising:

[0023] S1. Extract and analyze target features of the area where the display is located to obtain a comprehensive first area and a second area;

[0024] The obtaining of the comprehensive first area includes:

[0025] Obtaining the relative distance of the dynamic feature information of the regional target feature information, performing a shortest relative distance analysis on the relative distance, obtaining the associated feature area, the combined feature area and the comprehensive feature area and obtaining the weight setting information;

[0026] S2. Obtain relative position variables of dynamic feature information, perform position flow determination and flow area determination, and obtain flow area determination information;

[0027] S3. Calculate the display brightness adjustment coefficient according to the weight setting information and the average value of the brightness attenuation index, adjust and update the display brightness, and obtain display brightness update adjustment data.

[0028] The working principle and technical effect of the above technical solution are as follows: Target feature extraction is performed. Regional information includes various types, such as images and ambient light distribution, while target features include brightness, color, object outline, etc.

[0029] From the extracted target feature information, dynamic feature information is obtained and the relative distance between these dynamic features is calculated. The relative distance is the diameter between two locations.

[0030] Based on the shortest relative distance analysis results, the system further divides the regions into associated feature regions, combined feature regions, and comprehensive feature regions. Associated feature regions are regions where dynamic features are directly associated; combined feature regions are regions with specific significance formed by combining associated features; and comprehensive feature regions are the result of integrating combined feature regions. Furthermore, weighting information is obtained for each region, and the weighting is determined based on factors such as the region's importance.

[0031] Obtain the relative position variables of the dynamic feature information. The variables describe the position changes of the dynamic feature in space, such as the position coordinate changes of the dynamic feature over a period of time.

[0032] The acquired relative position variables are used to perform position flow determination to determine whether the dynamic feature has moved, as well as the direction and speed of the movement. Based on this, flow area determination is performed to determine the area involved in the dynamic feature flow, thereby obtaining flow area determination information.

[0033] Based on the weight setting information obtained in step S1 and the pre-collected average value of the brightness attenuation index (which reflects the attenuation pattern of the display brightness with factors such as vertical distance from the screen), the display brightness adjustment coefficient is calculated. This coefficient comprehensively considers the degree to which different regional characteristics affect brightness adjustment and the brightness attenuation.

[0034] The brightness of the display is adjusted using the calculated brightness adjustment coefficient. The adjusted brightness information is updated to obtain the display brightness update adjustment data, ensuring that the display brightness can adapt to changes in the current area information.

[0035] By deeply analyzing and extracting features from the display's area, the system can adjust brightness based on the characteristics and dynamic changes of each area. This brightness adjustment takes into account multiple factors, including the number, size, distance, and dynamic changes of the areas, achieving a balance between energy conservation and brightness. For example, comprehensive brightness adjustments can ensure that the display brightness is more in line with the user's actual needs and visual experience.

[0036] By acquiring the relative position variables of dynamic feature information and determining the flow area, the system can perceive dynamic changes in the display's environment in real time. When dynamic features change position, the system can promptly adjust the brightness control strategy to ensure that the display brightness always adapts to the changing environment, providing a clear and comfortable viewing experience.

[0037] The brightness adjustment coefficient is calculated by combining weight settings and the average brightness decay index, making brightness adjustment more precise and standardized. The weight settings highlight the importance of different areas to brightness adjustment, while the average brightness decay index takes into account the natural decay of brightness with factors such as distance, thus avoiding blindness and inaccuracy in brightness adjustment.

[0038] In one embodiment of the present invention, the S1 includes:

[0039] Acquire information about the area where the display is located, perform target feature extraction on the information about the area where the display is located, and obtain regional feature information; the regional feature information includes people, seats, and equipment, etc.;

[0040] Preprocessing the regional feature information to obtain preprocessed regional target feature information;

[0041] Analyze the regional target characteristic information to obtain the comprehensive first region;

[0042] Extracting light information features from the area where the display is located to obtain regional light information;

[0043] Preprocessing the regional light information to obtain preprocessed regional light feature information;

[0044] The regional light characteristic information is analyzed to obtain a second region, where the second region is the region illuminated by the display brightness.

[0045] The working principle and technical effect of the above technical solution are: obtaining original information of the area where the display is located through various sensors (such as cameras, infrared sensors, etc.), including various data types such as images and positions.

[0046] Target feature extraction is performed on the acquired regional information. Using image processing algorithms and pattern recognition techniques, representative target features such as people, seats, and equipment are identified and extracted from the raw information, thereby obtaining regional feature information. These target features can reflect the distribution of major objects and human activity within the area.

[0047] The extracted regional feature information may contain noise and incomplete data, so preprocessing is required. The preprocessing process includes filtering (removing noise), normalization (consolidating data to a specific range), and data completion (filling in missing data) to obtain preprocessed regional target feature information.

[0048] The pre-processed regional target feature information is analyzed, and target feature regions with similar or related features are integrated to obtain a comprehensive first region. The comprehensive first region can comprehensively reflect the overall distribution and correlation of people, etc. in the region.

[0049] Light characteristics are also extracted from the display's area. This is achieved through devices like light sensors, which capture light characteristics such as light intensity and color distribution within the area, generating regional light information. These characteristics reflect the lighting environment and brightness distribution of the current area.

[0050] Obtain pre-processed regional light feature information. This pre-processed light feature information is more accurate and stable, better reflecting actual lighting conditions and determining the area illuminated by the display brightness, i.e., the second area. Obtaining the second area can clarify the extent to which the display brightness affects the surrounding environment.

[0051] By extracting target features and light information, we can accurately locate people and other objects within the display area, as well as the lighting distribution. Based on this, through analysis and preprocessing, we can obtain a comprehensive first and second zone, effectively dividing the area. We can also integrate the needs of people and the lighting environment in different areas to obtain comprehensive brightness adjustment data that balances these factors.

[0052] Preprocessing the regional feature information and light feature information avoids brightness adjustment errors caused by inaccurate data or unreasonable analysis, and improves the efficiency and accuracy of brightness adjustment.

[0053] The system can adjust the brightness of the display according to actual needs to avoid unnecessary high brightness. Under the premise of not affecting user use, it can reduce the power consumption of the display and achieve the purpose of energy saving and environmental protection.

[0054] In one embodiment of the present invention, analyzing the regional target characteristic information to obtain the comprehensive first region includes:

[0055] Classify the regional target feature information according to dynamic features and static features to obtain dynamic feature information and static feature information; dynamic features mainly include people, and static features include seats and equipment, etc.;

[0056] Obtaining relative positions between multiple pieces of dynamic feature information, and obtaining relative distances between the dynamic feature information based on the relative positions;

[0057] Obtaining the shortest relative distance between each dynamic feature information and other dynamic feature information, comparing the shortest relative distance with a preset relative distance threshold, and obtaining a feature distance comparison result for each dynamic feature information;

[0058] The associated feature area is obtained based on the feature distance comparison result.

[0059] The working principle and technical effect of the above technical solution are as follows: Regional target feature information is divided into dynamic and static features by utilizing the properties of the target features themselves. This is based on the determination of the target feature's motion characteristics. For example, people have the ability to move autonomously, which is a dynamic feature; while seats and equipment are generally relatively fixed in position, which are static features. This allows the determination of dynamic and static feature information, as well as the relative distance between the dynamic feature information.

[0060] For each dynamic feature information, the relative distances between it and all other dynamic feature information are traversed to find the shortest relative distance. This shortest relative distance is numerically compared with a pre-set relative distance threshold, and the feature distance comparison result of each dynamic feature information is obtained based on the comparison result.

[0061] The areas covered by the dynamic feature information with associated relationships are integrated to obtain associated feature areas.

[0062] By analyzing and comparing the relative distances between dynamic feature information, dynamic features with spatial correlation can be accurately identified, and the associated feature areas can be accurately obtained.

[0063] The associated feature regions reflect the clustering and activity range of dynamic features. Based on these regions, brightness influence weights are obtained to improve the accuracy of brightness adjustment.

[0064] This method is adaptable to the distribution of dynamic and static features in different types of areas. The system can automatically classify, calculate, and analyze feature information acquired in real time, enhancing the system's adaptability and flexibility.

[0065] By accurately obtaining the associated feature areas, the system can more reasonably calculate the brightness adjustment resources, thereby improving the system's operating efficiency and resource utilization.

[0066] In one embodiment of the present invention, obtaining the associated feature region based on the feature distance comparison result includes:

[0067] When the shortest relative distance is greater than the preset relative distance threshold, two dynamic feature information corresponding to the shortest relative distance are obtained, the two dynamic feature information are marked as non-associated features, and two dynamic feature areas are obtained; each dynamic feature information is a dynamic feature area, and the shortest relative distance is greater than the preset relative distance threshold, indicating that the two corresponding dynamic features are far apart and do not need to be combined.

[0068] When the shortest relative distance is less than or equal to a preset relative distance threshold, two dynamic feature information corresponding to the shortest relative distance are obtained, the two dynamic feature information are marked as associated features, and an associated feature area is obtained; the associated feature area is a combined area of ​​the two dynamic feature information;

[0069] Obtaining the shortest relative distance between each correlation feature and other correlation features, comparing the shortest relative distance with a preset correlation relative distance threshold, and obtaining a correlation distance comparison result for each correlation feature;

[0070] The combined feature region and the comprehensive feature region are obtained according to the correlation distance comparison result, and the weight setting information is obtained.

[0071] The working principle and technical effect of the above technical solution are as follows: calculate the shortest relative distance between each dynamic feature. If it is greater than the preset relative distance threshold, the corresponding dynamic feature is judged to be non-associated and each is independently formed into a dynamic feature area; if it is less than or equal to the threshold, it is judged to be associated, and the two areas are combined into an associated feature area.

[0072] For the associated feature areas, the associated shortest relative distance between the associated feature areas is obtained, and compared with a preset associated relative distance threshold to obtain an associated distance comparison result.

[0073] Based on the correlation distance comparison results, closely correlated correlation feature regions are combined into combined feature regions, and then comprehensive analysis is performed to obtain comprehensive feature regions. At the same time, weights are set according to the characteristics of each region.

[0074] Through multi-level distance comparison and judgment, the region is subdivided into single, associated, combined and comprehensive feature areas to accurately reflect the dynamic feature distribution and relationship.

[0075] The preset threshold is used to objectively judge the correlation of dynamic features, avoid subjective errors, and ensure the accuracy of correlation judgment.

[0076] By obtaining associated feature areas, combined feature areas, and comprehensive feature areas, the scope of different areas can be obtained to reflect the gathering of people, which in turn helps set regional weights and consider the impact of personnel distribution on brightness adjustment.

[0077] In one embodiment of the present invention, the step of obtaining the combined feature region and the comprehensive feature region based on the correlation distance comparison result and obtaining weight setting information includes:

[0078] When the shortest relative distance between the two correlated features is greater than a preset threshold value of the shortest relative distance between the two correlated features, the correlated feature information corresponding to the shortest relative distance between the two correlated features is obtained, and the two correlated feature information are marked as non-combined features; the non-combined features include two non-combined correlated feature areas;

[0079] When the relative distance between the associated peers is less than or equal to a preset relative distance threshold, the associated feature information corresponding to the shortest relative distance is obtained, and the two associated feature information are marked as a combined feature to obtain a combined feature area; the combined feature area includes the area after the two associated feature areas are combined;

[0080] The preset association relative distance threshold is 1 / 2 of the preset relative threshold;

[0081] Obtain the combined shortest relative distance between each combination feature and other combination features, compare the combined shortest relative distance with a preset combination relative distance threshold, and obtain a combined distance comparison result for each combination feature;

[0082] The preset combined relative distance threshold is 1 / 2 of the preset associated relative threshold;

[0083] Determine whether to combine the combined features again according to the combined distance comparison result until all associated features are combined to obtain a comprehensive feature area; the largest area formed after all associated combinations is the comprehensive feature area;

[0084] The weights of different types of feature regions are set to obtain weight setting information. The different types of feature regions include comprehensive feature regions, combined feature regions, and dynamic feature regions of associated feature regions.

[0085] The working principle and technical effect of the above technical solution are as follows: First, the shortest relative distance between the associated feature information is calculated and compared with a preset relative distance threshold. If it is greater than the threshold, the corresponding associated features are marked as non-combined features, and each of them forms a non-combined associated feature region. If it is less than or equal to the threshold, it is marked as a combined feature, and the two associated feature regions are combined into a combined feature region.

[0086] For the formed combined feature regions, the combined shortest relative distance between the combined feature regions is calculated and compared with the preset combined relative distance threshold to obtain a combined distance comparison result. Based on the result, it is determined whether these combined features should be combined again.

[0087] Repeat the above combination determination process until all related features are combined, and the largest area finally formed is the comprehensive feature area.

[0088] For different categories of feature areas, such as comprehensive feature areas, combined feature areas, and dynamic feature areas in associated feature areas, weights are set according to factors such as the degree of their influence on brightness adjustment.

[0089] Through step-by-step relative distance comparison and combination judgment, the feature area is subdivided from the associated feature area into the combined feature area, and finally the comprehensive feature area is formed, constructing a clear multi-level feature area structure, which can more accurately reflect the distribution and correlation degree of dynamic features in the area.

[0090] Based on this multi-level feature area division, brightness adjustment can set differentiated weights for areas at different levels, making brightness adjustment more in line with actual needs and improving the rationality and effectiveness of adjustment.

[0091] This dynamic combination judgment method can flexibly respond to changes in dynamic characteristics within the region, enhancing the adaptability and stability of the system.

[0092] By setting weights, the system can reasonably obtain brightness adjustment data based on the importance and influence of different feature areas, avoid waste of resources, and improve the operating efficiency of the system.

[0093] In one embodiment of the present invention, the weight setting information includes:

[0094] The weight of the comprehensive feature area is greater than that of the combined feature area;

[0095] The weight of the combined feature area is greater than the weight of the associated feature area;

[0096] The weight of the associated feature area is greater than that of the dynamic feature area.

[0097] The weight value range is 0-1.

[0098] The working principle and technical effect of the above technical solution are as follows: based on the number of dynamic features covered by the feature area, the degree of correlation, etc., the comprehensive feature area, combined feature area, associated feature area and dynamic feature area are divided into different levels. The comprehensive feature area contains the maximum range after the combination of all associated features, and has the most critical impact on the overall brightness adjustment, so it has the highest weight; the combined feature area is composed of some associated features and is second in importance; the associated feature area has a certain correlation but a smaller range, and is third in importance; the dynamic feature area is only a single dynamic feature, and has the least impact on the overall brightness adjustment, so it has the lowest weight. Through this hierarchical division, different feature areas are given different weight values ​​from high to low.

[0099] The weight value range is limited to 0-1, where 0 indicates that the feature region has no effect on brightness adjustment, and 1 indicates that the feature region has a decisive influence on brightness adjustment. This limitation allows the weight value to intuitively and quantitatively reflect the relative importance of each feature region in brightness adjustment.

[0100] Reasonable weight setting can enable the brightness adjustment system to determine the differentiated impact according to the importance of different feature areas.

[0101] By assigning weights, the system can prioritize data from areas with greater influencing factors and conduct comprehensive analysis and adjustment of brightness across multiple areas. Weight values ​​range from 0 to 1, allowing the system to flexibly adjust the weights of each feature area based on different application scenarios and actual needs. For example, in scenes with dense crowds and high brightness requirements, the weights of the comprehensive and combined feature areas can be appropriately increased; whereas in scenes with sparse crowds and low brightness requirements, the weights of these areas can be reduced, enhancing the system's adaptability to different environments.

[0102] In one embodiment of the present invention, obtaining the preset relative distance threshold includes:

[0103] Obtaining an average value of the brightness attenuation index of the display brightness of the area where the display is located on different target feature information;

[0104] Obtain the relative position of the target feature information and the display screen corresponding to the average value of the brightness attenuation index on different target feature information to obtain the average attenuation relative position;

[0105] The relative distance between the average attenuation and the relative position is the preset relative distance threshold.

[0106] The calculation formula of brightness attenuation index is:

[0107] LS=1-e -αd

[0108] Where LS is the brightness attenuation index, α is the attenuation coefficient, which is related to the characteristics of the propagation medium, such as air density and dust content, and d is the propagation distance;

[0109] Calculation example: If light propagates in air, the attenuation coefficient α = 0.01m-1, and the propagation distance d = 50m, then the brightness attenuation index LS = 1-e-0.01×50 = 1-e-0.5≈1-0.6065=0.3935, that is, the brightness attenuation is about 39.35%;

[0110] The working principle and technical effect of the above technical solution are as follows: Brightness measurement and data analysis are performed for different target features within the display area. Using specialized brightness measurement equipment, the brightness of light emitted by the display is measured at different locations and conditions when it reaches each target feature. Combined with the initial brightness value, the brightness attenuation index for each target feature is calculated. The brightness attenuation index for all target features is then averaged to obtain the average brightness attenuation index for the display brightness across the different target features.

[0111] While calculating the average brightness attenuation index, the relative position of each target feature information and the display screen is recorded. The calculated average brightness attenuation index value is then correlated with the corresponding relative position of the target feature information. The relative position of the target feature information and the display screen corresponding to the average brightness attenuation index is found. This position is the average attenuation relative position.

[0112] The relative distance of the average attenuation relative position is used as the preset relative distance threshold.

[0113] By actually measuring and analyzing the attenuation of display brightness at different target features, the preset relative distance threshold is determined, eliminating subjective assumptions. This threshold accurately reflects the relationship between brightness attenuation and the location of target feature information.

[0114] Based on the preset relative distance threshold determined based on actual brightness attenuation data, the system can more accurately determine the distance relationship between different target feature information and the display screen, thereby adjusting the brightness more precisely.

[0115] By reasonably setting the preset relative distance threshold, the system can adjust the brightness according to actual needs, minimize energy consumption while meeting the user's visual needs, and achieve an optimized balance between user experience and energy utilization.

[0116] In one embodiment of the present invention, S2 includes:

[0117] Obtaining relative position variables of each dynamic feature information in the feature areas of different types of areas, comparing the preset relative distance threshold with the relative position variables, and obtaining position flow determination information of each dynamic feature information;

[0118] When the relative position variable is greater than a preset relative distance threshold, the corresponding dynamic feature information is determined to be in a position flow state; otherwise, it is determined to be in a position non-flow state;

[0119] The flow area determination is performed on the dynamic feature information corresponding to the relative position variable according to the position flow determination information to obtain the flow area determination information.

[0120] When the dynamic feature information corresponding to the phase position variable is marked as an associated feature with the dynamic feature information of other different types of regions, the corresponding dynamic feature information is determined to be in a regional flow state; otherwise, it is determined to be in a regional non-flow state. When the dynamic feature information is in a regional flow state, the flow region is determined to be the region where the associated feature is located.

[0121] The working principle and technical effect of the above technical solution are: obtaining the relative position variable of each dynamic feature information in different types of feature areas, which variable describes the position information of the dynamic feature information in space.

[0122] The preset relative distance threshold is compared with the relative position variable of each dynamic feature information. By comparing the two, if the relative position variable is greater than the preset relative distance threshold, it indicates that the position of the dynamic feature information has changed significantly and is judged to be in a state of positional mobility. Conversely, if the relative position variable is less than or equal to the preset relative distance threshold, it is judged to be in a state of positional immobility, thus obtaining positional mobility determination information for each dynamic feature information.

[0123] After determining location mobility, the dynamic feature information is further considered in relation to dynamic feature information of other different types of regions. If a dynamic feature is marked as a correlation feature with dynamic feature information of other different types of regions, it indicates that the dynamic feature has a tendency to move between different regions and become associated with features of other regions. In this case, it is considered to be in a regional mobility state. If no such correlation is marked, it is considered to be in a regional non-mobility state.

[0124] When the dynamic feature information is determined to be a regional flow state, its flow region is determined to be the region where the associated feature is located, and flow region determination information is obtained.

[0125] By comparing relative position variables with a preset relative distance threshold, we can accurately determine whether the location of dynamic feature information is flowing, avoiding errors caused by subjective judgment or simple observation. Furthermore, combining associated feature annotations for regional flow determination further refines the identification of dynamic feature information flow states, accurately distinguishing between different states such as positional flow, regional flow, and non-flow.

[0126] By determining the location and regional status, the regional status can be updated and the weight can be further adjusted according to the flow of personnel.

[0127] In one embodiment of the present invention, S3 includes:

[0128] Get the average value of brightness attenuation index of different types of areas;

[0129] Calculate the display brightness adjustment coefficient based on the weight setting information of different types of areas and the average value of the brightness attenuation index;

[0130] Adjust the brightness of the display according to the display brightness adjustment coefficient to obtain display brightness adjustment data;

[0131] updating weight setting information of different types of areas according to flow area determination information to obtain weight setting update information;

[0132] Determine whether the weight setting update information is greater than the update threshold. When the weight setting update information is greater than the update threshold, calculate the display brightness update adjustment coefficient based on the weight setting update information of different types of areas, the average value of the brightness attenuation index, etc.;

[0133] The display brightness is adjusted according to the display brightness update adjustment coefficient to obtain display brightness update adjustment data.

[0134] The calculation formula of the display brightness adjustment coefficient is:

[0135]

[0136] Wherein, LT is the display brightness adjustment coefficient, ZT is the total adjustment value of all comprehensive feature areas, QZ is the weight of the comprehensive feature area, UT is the total adjustment value of the combined feature area, QU is the weight of the combined feature area, GT is the total adjustment value of the associated feature area, QG is the weight of the associated feature area, DT is the total adjustment value of the dynamic feature area, and QT is the weight value of the dynamic feature area;

[0137] The calculation formula for the total adjustment value of the comprehensive feature area, combined feature area, associated feature area or dynamic feature area is:

[0138]

[0139] Where OT is the total adjustment value, n is the total number of comprehensive feature areas, combined feature areas, associated feature areas or dynamic feature areas, SP i is the average value of the brightness attenuation index of the i-th region in the total number of regions.

[0140] The working principle and technical effect of the above technical solution are: measuring the brightness of different types of areas (such as comprehensive feature areas, combined feature areas, associated feature areas, etc.), analyzing the attenuation of light emitted by the display in these areas, calculating the brightness attenuation index of each area, and obtaining the average brightness attenuation index of different types of areas to reflect the overall brightness attenuation characteristics of different areas.

[0141] The display brightness adjustment coefficient is obtained by combining the pre-set weight setting information of different types of areas (reflecting the importance of each area in brightness adjustment) and the calculated average value of the brightness attenuation index. This coefficient is used to guide the preliminary adjustment of the display brightness.

[0142] The brightness of the display is adjusted according to the calculated brightness adjustment coefficient of the display to obtain the brightness adjustment data of the display, thereby achieving preliminary optimization of the brightness of the display.

[0143] Based on the flow area determination information obtained previously (determining whether the dynamic feature information is in the regional flow state and the flow area), the weight setting information of different types of areas is updated to obtain weight setting update information to adapt to the changes in regional importance brought about by the flow of dynamic feature information.

[0144] Determine whether the updated weight setting information is greater than the preset update threshold. If it is, it indicates that the region importance has changed significantly, and the display brightness adjustment coefficient needs to be recalculated. At this time, the display brightness update adjustment coefficient is calculated based on the updated weight setting information of different types of regions and the average brightness attenuation index. The display brightness is adjusted again based on this coefficient to obtain the display brightness update adjustment data, completing further optimization of the display brightness.

[0145] By comprehensively considering the average brightness attenuation index and weight setting information of different types of areas to calculate the brightness adjustment coefficient, the display brightness can be dynamically and accurately adjusted according to the actual brightness attenuation and importance of each area, ensuring that appropriate brightness is provided to users in different environments.

[0146] The weight setting information is updated using the flow area determination information, and whether to make a secondary adjustment is determined based on the update threshold, so that the system can quickly adapt to scene changes brought about by the flow of dynamic feature information, adjust the display brightness in time, and improve the system's adaptability to complex environments.

[0147] Through reasonable weight setting and brightness adjustment, unnecessary energy waste is avoided. Under the premise of meeting the user's visual needs, energy consumption is minimized and resource utilization efficiency is improved.

[0148] In one embodiment of the present invention, the system includes:

[0149] A region division module is used to extract and analyze target features of the region where the display is located to obtain a comprehensive first region and a second region;

[0150] The obtaining of the comprehensive first area includes:

[0151] Obtaining the relative distance of the dynamic feature information of the regional target feature information, performing a shortest relative distance analysis on the relative distance, obtaining the associated feature area, the combined feature area and the comprehensive feature area and obtaining the weight setting information;

[0152] A flow determination module is used to obtain relative position variables of dynamic feature information, perform position flow determination and flow area determination, and obtain flow area determination information;

[0153] The brightness adjustment module is used to calculate the display brightness adjustment coefficient according to the weight setting information and the average value of the brightness attenuation index, adjust and update the display brightness, and obtain the display brightness update adjustment data.

[0154] The working principle and technical effect of the above technical solution are as follows: Target feature extraction is performed. Regional information includes various types, such as images and ambient light distribution, while target features include brightness, color, object outline, etc.

[0155] From the extracted target feature information, dynamic feature information is obtained and the relative distance between these dynamic features is calculated. The relative distance is the diameter between two locations.

[0156] Based on the shortest relative distance analysis results, the system further divides the regions into associated feature regions, combined feature regions, and comprehensive feature regions. Associated feature regions are regions where dynamic features are directly associated; combined feature regions are regions with specific significance formed by combining associated features; and comprehensive feature regions are the result of integrating combined feature regions. Furthermore, weighting information is obtained for each region, and the weighting is determined based on factors such as the region's importance.

[0157] Obtain the relative position variables of the dynamic feature information. The variables describe the position changes of the dynamic feature in space, such as the position coordinate changes of the dynamic feature over a period of time.

[0158] The acquired relative position variables are used to perform position flow determination to determine whether the dynamic feature has moved, as well as the direction and speed of the movement. Based on this, flow area determination is performed to determine the area involved in the dynamic feature flow, thereby obtaining flow area determination information.

[0159] The weight setting information and the pre-collected average value of the brightness attenuation index (which reflects the attenuation of display brightness with factors such as vertical distance from the screen) are obtained to calculate the display brightness adjustment coefficient. This coefficient comprehensively considers the influence of different regional characteristics on brightness adjustment and the brightness attenuation.

[0160] The brightness of the display is adjusted using the calculated brightness adjustment coefficient. The adjusted brightness information is updated to obtain the display brightness update adjustment data, ensuring that the display brightness can adapt to changes in the current area information.

[0161] By deeply analyzing and extracting features from the display's area, the system can adjust brightness based on the characteristics and dynamic changes of each area. This brightness adjustment takes into account the number, size, distance, and dynamic changes of the areas, achieving a balance between energy conservation and brightness. For example, comprehensive brightness adjustments ensure that the display brightness is more in line with the user's actual needs and visual experience.

[0162] By acquiring the relative position variables of dynamic feature information and determining the flow area, the system can perceive dynamic changes in the display's environment in real time. When dynamic features change position, the system can promptly adjust the brightness control strategy to ensure that the display brightness always adapts to the changing environment, providing a clear and comfortable viewing experience.

[0163] The brightness adjustment coefficient is calculated by combining weight settings and the average brightness decay index, making brightness adjustment more precise and standardized. The weight settings highlight the importance of different areas to brightness adjustment, while the average brightness decay index takes into account the natural decay of brightness with factors such as distance, thus avoiding blindness and inaccuracy in brightness adjustment.

[0164] Obviously, those skilled in the art may make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if such modifications and variations fall within the scope of the claims and their equivalents, the present invention is intended to include such modifications and variations.

Claims

1. A display brightness adjustment optimization method, characterized in that: The method comprises: S1. Extract and analyze target features of the area where the display is located to obtain a comprehensive first area and a second area; The obtaining of the comprehensive first area includes: Obtaining the relative distance of the dynamic feature information of the regional target feature information, performing a shortest relative distance analysis on the relative distance, obtaining the associated feature area, the combined feature area and the comprehensive feature area and obtaining the weight setting information; S2. Obtain relative position variables of dynamic feature information, perform position flow determination and flow area determination, and obtain flow area determination information; S3. Calculate the display brightness adjustment coefficient according to the weight setting information and the average value of the brightness attenuation index, adjust and update the display brightness, and obtain display brightness update adjustment data.

2. A display brightness adjustment optimization method according to claim 1, characterized in that: Said S1 comprises: Acquire information about the area where the display is located, perform target feature extraction on the information about the area where the display is located, and obtain regional feature information; Preprocessing the regional feature information to obtain preprocessed regional target feature information; Analyze the regional target characteristic information to obtain the comprehensive first region; Extracting light information features from the area where the display is located to obtain regional light information; Preprocessing the regional light information to obtain preprocessed regional light feature information; The regional light characteristic information is analyzed to obtain a second region.

3. The display brightness adjustment optimization method according to claim 2, characterized in that: The analyzing the regional target characteristic information to obtain the comprehensive first region includes: Classifying regional target feature information according to dynamic features and static features to obtain dynamic feature information and static feature information; Obtaining relative positions between multiple pieces of dynamic feature information, and obtaining relative distances between the dynamic feature information based on the relative positions; Obtaining the shortest relative distance between each dynamic feature information and other dynamic feature information, comparing the shortest relative distance with a preset relative distance threshold, and obtaining a feature distance comparison result for each dynamic feature information; The associated feature area is obtained based on the feature distance comparison result.

4. A display brightness adjustment optimization method according to claim 3, characterized in that: The obtaining of the associated feature area according to the feature distance comparison result includes: When the shortest relative distance is greater than a preset relative distance threshold, two dynamic feature information corresponding to the shortest relative distance are obtained, the two dynamic feature information are marked as non-correlated features, and two dynamic feature areas are obtained; When the shortest relative distance is less than or equal to a preset relative distance threshold, two pieces of dynamic feature information corresponding to the shortest relative distance are obtained, the two pieces of dynamic feature information are marked as associated features, and an associated feature area is obtained; Obtaining the shortest relative distance between each correlation feature and other correlation features, comparing the shortest relative distance with a preset correlation relative distance threshold, and obtaining a correlation distance comparison result for each correlation feature; The combined feature region and the comprehensive feature region are obtained according to the correlation distance comparison result, and the weight setting information is obtained.

5. The display brightness adjustment optimization method according to claim 4, characterized in that: The step of obtaining the combined feature region and the comprehensive feature region and obtaining weight setting information according to the correlation distance comparison result includes: When the shortest relative distance is greater than a preset threshold value of the associated relative distance, the associated feature information corresponding to the shortest relative distance is obtained, and the two pieces of associated feature information are marked as non-combined features; When the relative distance between the associated peers is less than or equal to a preset relative distance threshold, the associated feature information corresponding to the shortest relative distance is obtained, and the two associated feature information are marked as a combined feature to obtain a combined feature area; Obtain the combined shortest relative distance between each combination feature and other combination features, compare the combined shortest relative distance with a preset combination relative distance threshold, and obtain a combined distance comparison result for each combination feature; Determining whether to combine the combined features again according to the combined distance comparison result until all associated features are combined to obtain a comprehensive feature area; Weights are set for different types of feature regions to obtain weight setting information.

6. A display brightness adjustment optimization method according to claim 5, characterized in that: The weight setting information includes: The weight of the comprehensive feature area is greater than that of the combined feature area; The weight of the combined feature area is greater than the weight of the associated feature area; The weight of the associated feature area is greater than that of the dynamic feature area.

7. The display brightness adjustment optimization method according to claim 3, characterized in that: The acquisition of the preset relative distance threshold includes: Obtaining an average value of the brightness attenuation index of the display brightness of the area where the display is located on different target feature information; Obtain the relative position of the target feature information and the display screen corresponding to the average value of the brightness attenuation index on different target feature information to obtain the average attenuation relative position; The relative distance between the average attenuation and the relative position is the preset relative distance threshold.

8. The display brightness adjustment optimization method according to claim 1, characterized in that: The S2 includes: Obtaining relative position variables of each dynamic feature information in the feature areas of different types of areas, comparing a preset relative distance threshold with the relative position variables, and obtaining position flow determination information of each dynamic feature information; The flow area determination is performed on the dynamic feature information corresponding to the relative position variable according to the position flow determination information to obtain the flow area determination information.

9. The display brightness adjustment optimization method according to claim 1, characterized in that: The S3 includes: Get the average value of brightness attenuation index of different types of areas; Calculate the display brightness adjustment coefficient based on the weight setting information of different types of areas and the average value of the brightness attenuation index; Adjust the brightness of the display according to the display brightness adjustment coefficient to obtain display brightness adjustment data; updating weight setting information of different types of areas according to flow area determination information to obtain weight setting update information; Determine whether the weight setting update information is greater than an update threshold. If the weight setting update information is greater than the update threshold, calculate the display brightness update adjustment coefficient based on the weight setting update information of different types of areas and the average value of the brightness attenuation index. The display brightness is adjusted according to the display brightness update adjustment coefficient to obtain display brightness update adjustment data.

10. A display brightness adjustment optimization system, characterized in that: The system comprises: A region division module is used to extract and analyze target features of the region where the display is located to obtain a comprehensive first region and a second region; The obtaining of the comprehensive first area includes: Obtaining the relative distance of the dynamic feature information of the regional target feature information, performing a shortest relative distance analysis on the relative distance, obtaining the associated feature area, the combined feature area and the comprehensive feature area and obtaining the weight setting information; A flow determination module is used to obtain relative position variables of dynamic feature information, perform position flow determination and flow area determination, and obtain flow area determination information; The brightness adjustment module is used to calculate the display brightness adjustment coefficient according to the weight setting information and the average value of the brightness attenuation index, adjust and update the display brightness, and obtain the display brightness update adjustment data.

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