Energy-saving method, device and equipment based on commercial liquid crystal display and storage medium

Abstract

The invention relates to an energy-saving method, device and equipment based on a commercial liquid crystal display and a storage medium. The energy-saving method comprises the steps that real-time display content and environment brightness data of the liquid crystal display are collected; performing image processing on the real-time display content to obtain brightness distribution characteristics and color information of the real-time display content; transmitting the brightness distribution characteristics, the color information and the ambient brightness data to a pre-trained display model for analysis, and obtaining a target brightness value of each backlight area of the liquid crystal display through analysis; and adjusting the backlight brightness of the liquid crystal display according to the target brightness value of each backlight area so as to save energy and optimize the viewing experience of a user. The liquid crystal display has the effect of improving the energy utilization efficiency of the liquid crystal display.

Description

Technical Field

[0001] The present application relates to the technical field of liquid crystal display, and in particular to an energy-saving method, device, equipment and storage medium based on a commercial liquid crystal display. Background Art

[0002] At present, as commercial LCDs are widely used in various occasions, their energy consumption issues are increasingly concerned. Commercial LCDs usually use fixed backlight settings and cannot dynamically adjust the backlight brightness according to the display content, resulting in high energy consumption. In the prior art, some high-end LCDs use a simple backlight adjustment function, but the adjustment range is limited and cannot achieve refined dynamic adjustment.

[0003] The above-mentioned prior art solutions have the following defects: the backlight adjustment method of the prior art cannot fully adapt to the diverse display requirements of commercial liquid crystal displays, has poor energy-saving effects, and may affect the user's viewing experience, so there is room for improvement. Summary of the invention

[0004] In order to improve the energy utilization efficiency of liquid crystal displays, the present application provides an energy-saving method, device, equipment and storage medium based on a commercial liquid crystal display.

[0005] The above-mentioned invention objective of the present application is achieved through the following technical solutions: An energy-saving method based on a commercial liquid crystal display, the energy-saving method based on a commercial liquid crystal display comprising: Collect real-time display content and ambient brightness data of LCD monitors; Performing image processing on the real-time display content to obtain brightness distribution characteristics and color information of the real-time display content; The brightness distribution characteristics, the color information and the ambient brightness data are transmitted to a pre-trained display model for analysis, and the target brightness value of each backlight area of ​​the liquid crystal display is obtained by analysis; The backlight brightness of the liquid crystal display is adjusted according to the target brightness values ​​of the respective backlight zones to achieve energy saving and optimize the user viewing experience.

[0006] By adopting the above technical solution, by collecting the real-time display content and ambient brightness data of the LCD display, the brightness and color distribution of the display content, as well as the light intensity of the surrounding environment can be fully and comprehensively grasped in real time. During the operation of the LCD display, the display content and ambient lighting are dynamically changing. Real-time collection of these data ensures that the system can capture the changes at any time. The brightness and color distribution of the display content directly affect the backlight demand, while the ambient brightness determines the perceived brightness of the overall display effect. By simultaneously monitoring these two types of key data, the system can accurately evaluate the current display demand, so that when adjusting the backlight brightness, it can save energy and maintain the best visual effect, ultimately improving energy saving efficiency and optimizing the user viewing experience; according to the target brightness value of each backlight area obtained by model analysis, the system will automatically adjust the backlight brightness of the display. This adjustment is intended to ensure that the display can provide the best viewing experience under different display content and environmental conditions, achieve energy saving and optimize the user viewing experience. By intelligently adjusting the backlight brightness, the system can reduce energy consumption without sacrificing viewing quality and achieve energy saving.

[0007] At the same time, optimizing backlight brightness can improve image visibility and comfort, and improve the user's viewing experience.

[0008] In a preferred example, the present application can be further configured as follows: the acquisition of real-time display content and ambient brightness data of the liquid crystal display includes: Acquire image frames of the content displayed by the liquid crystal display in real time through an image acquisition device; Continuously sampling the image frames of the display content, and statistically analyzing the sampling information to obtain the real-time display content of the liquid crystal display; The brightness data of the environment around the liquid crystal display is collected by an ambient light sensor as the ambient brightness data.

[0009] By adopting the above technical solution, by collecting the real-time display content and ambient brightness data of the LCD display, the brightness and color distribution of the display content, as well as the light intensity of the surrounding environment can be fully and comprehensively grasped in real time. Real-time collection of these data ensures that the system can capture changes at any time. The brightness and color distribution of the display content directly affect the backlight demand, while the ambient brightness determines the perceived brightness of the overall display effect, improves energy saving efficiency and optimizes the user viewing experience; by performing image processing on the real-time display content, the brightness distribution characteristics and color information of the display content can be accurately extracted; by transmitting the brightness distribution characteristics and color information as well as the ambient brightness data to a pre-trained display model for analysis, the display content and environmental factors can be comprehensively considered to accurately calculate the target brightness value of each backlight area of ​​the LCD display.

[0010] In a preferred example, the present application may be further configured as follows: performing image processing on the real-time display content to obtain brightness distribution characteristics and color information of the real-time display content includes: Calculating the brightness distribution of the real-time display content in each image frame by using a brightness histogram analysis technique to obtain brightness distribution characteristics of the real-time display content; By color distribution analysis, the color components and their distribution ratios in the image of the real-time display content are extracted to obtain the color information of the real-time display content.

[0011] By adopting the above technical solution, by performing image processing on the real-time display content, the brightness distribution characteristics and color information of the display content can be accurately extracted. Specifically, the brightness distribution of the display content determines the light intensity that the backlight system needs to provide, and the color information is related to the color saturation and contrast of the display. In the process of image processing, the system can analyze the brightness distribution of the display content in detail through the brightness histogram analysis technology, so as to accurately identify the light and dark changes in the display area; in addition, through color distribution analysis, the system can extract the main color components in the image and determine the distribution ratio of each color, which enables the system to adjust the backlight brightness in a targeted manner to ensure the true restoration of colors and the visual impact of the picture. Finally, this series of processing steps provides accurate data support for subsequent backlight adjustments, thereby improving energy saving effects and picture quality.

[0012] In a preferred example, the present application may be further configured as follows: before the brightness distribution characteristics and the color information are transmitted to a pre-trained display model for analysis to obtain target brightness values ​​of each backlight area of ​​the liquid crystal display, the energy saving method based on a commercial liquid crystal display further includes: Collecting display content data in different environments, and preprocessing the display content data in different environments to obtain a training set; A display model is constructed based on a convolutional neural network and a recurrent neural network, the display model is trained by forward propagation and back propagation using the training set, and the display model after forward propagation and back propagation training is optimized using a model pruning method to obtain the pre-trained display model.

[0013] By adopting the above technical solution, by collecting display content data in different environments and preprocessing these data, a display model with wide adaptability can be constructed. Specifically, in the training process of the model, the display content data in different environments provide a variety of scenarios, which cover various display conditions from high brightness to low brightness, from single color to complex colors. By preprocessing these data, the system can clean up noise, standardize input, and remove redundant information to ensure the accuracy of model training; based on the combination of convolutional neural networks and recurrent neural networks, the model shows extremely high learning ability when processing time series data and spatial features, and through forward propagation and back propagation training, the model is optimized, and finally forms an efficient display model that can accurately analyze display content in multiple environments, which greatly improves the energy saving effect and user experience of the display under different usage conditions.

[0014] In a preferred example, the present application may be further configured as follows: the brightness distribution characteristics and the color information are transmitted to a pre-trained display model for analysis, and the target brightness values ​​of each backlight area of ​​the liquid crystal display obtained by analysis include: Performing multi-level analysis on brightness distribution characteristics and color information using the pre-trained model to generate brightness adjustment coefficients for each backlight area; According to the brightness adjustment coefficients of the respective backlight areas, target brightness values ​​of the respective backlight areas of the liquid crystal display are calculated.

[0015] By adopting the above technical solution, by using a pre-trained model to perform multi-level analysis on the brightness distribution characteristics and color information, the brightness adjustment coefficient of each backlight area can be accurately calculated, and then the target brightness value of each backlight area can be determined. In this process, the display model fully considers the brightness changes and color distribution of the display content. Through multi-level in-depth analysis, the model can identify the specific lighting requirements of different backlight areas and quantify this requirement as a brightness adjustment coefficient. By calculating these coefficients, the system can accurately control the light intensity of each backlight area and realize dynamic adjustment of the backlight of each area. Finally, this precise backlight adjustment method minimizes energy consumption while ensuring the display effect, and significantly improves the overall energy efficiency of the LCD display.

[0016] In a preferred example, the present application can be further configured as follows: the energy saving method based on a commercial liquid crystal display further includes: Acquire and record the user's viewing habits and preference data, input the user's viewing habits and preference data into the pre-trained display model, and adjust the parameters in the pre-trained display model; The energy-saving effect after the backlight brightness is adjusted is recorded in real time, an energy-saving report is generated according to the energy-saving effect, and the energy-saving report is fed back to the user end.

[0017] By adopting the above technical solution, by acquiring and recording the user's viewing habits and preference data and inputting these data into a pre-trained display model, the parameter settings of the display model can be further optimized, so that the backlight adjustment is more in line with the user's personalized needs. In the daily use of the LCD display, the user's viewing habits and preferences will directly affect their perception of brightness and color. By recording these habits and preferences, the system can gradually understand the user's usage patterns and use these data to continuously adjust the parameters of the display model, so that the backlight brightness adjustment is more in line with the user's needs. In addition, by real-time recording the energy-saving effect after the backlight adjustment, the system can evaluate the effect of the adjustment strategy and generate a detailed energy-saving report to feedback to the user, thereby improving the user's recognition of the energy-saving measures and further improving the energy-saving effect of the display.

[0018] The second object of the invention is achieved by the following technical solutions: An energy-saving device based on a commercial liquid crystal display, the energy-saving device based on a commercial liquid crystal display comprising: A data collection module is used to collect real-time display content and ambient brightness data of the LCD display; An image processing module, used to perform image processing on the real-time display content to obtain brightness distribution characteristics and color information of the real-time display content; An analysis module is used to transmit the brightness distribution characteristics, the color information and the ambient brightness data to a pre-trained display model for analysis, and obtain target brightness values ​​of each backlight area of ​​the liquid crystal display through analysis; The adjustment module is used to adjust the backlight brightness of the liquid crystal display according to the target brightness value of each backlight area to achieve energy saving and optimize the user viewing experience.

[0019] By adopting the above technical solution, by collecting the real-time display content and ambient brightness data of the LCD display, it is possible to fully and in real time grasp the brightness and color distribution of the display content, as well as the light intensity of the surrounding environment. During the operation of the LCD display, the display content and ambient lighting are dynamically changing. Real-time collection of these data ensures that the system can capture the changes at any time. The brightness and color distribution of the display content directly affect the backlight demand, while the ambient brightness determines the perceived brightness of the overall display effect. By simultaneously monitoring these two types of key data, the system can accurately evaluate the current display demand, thereby saving energy when adjusting the backlight brightness while maintaining the best visual effect, ultimately improving energy-saving efficiency and optimizing the user viewing experience.

[0020] The third objective of the present application is achieved through the following technical solutions: A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the energy saving method based on a commercial liquid crystal display are implemented.

[0021] The fourth objective of the present application is achieved through the following technical solutions: A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the energy-saving method based on a commercial liquid crystal display are implemented.

[0022] In summary, the present application includes at least one of the following beneficial technical effects: 1. By collecting the real-time display content and ambient brightness data of the LCD, the brightness and color distribution of the display content, as well as the light intensity of the surrounding environment, can be fully understood in real time. During the operation of the LCD, the display content and ambient light are dynamically changing. Real-time collection of these data ensures that the system can capture the changes at any time. The brightness and color distribution of the display content directly affect the backlight demand, while the ambient brightness determines the perceived brightness of the overall display effect. By simultaneously monitoring these two types of key data, the system can accurately evaluate the current display demand, so that when adjusting the backlight brightness, it can save energy while maintaining the best visual effect, ultimately improving energy-saving efficiency and optimizing the user viewing experience; 2. By performing image processing on the real-time display content, the brightness distribution characteristics and color information of the display content can be accurately extracted. Specifically, the brightness distribution of the display content determines the light intensity that the backlight system needs to provide, while the color information is related to the color saturation and contrast of the display. During the image processing process, the system can analyze the brightness distribution of the display content in detail through the brightness histogram analysis technology, so as to accurately identify the light and dark changes in the display area. In addition, through color distribution analysis, the system can extract the main color components in the image and determine the distribution ratio of each color, which enables the system to adjust the backlight brightness in a targeted manner to ensure the true restoration of colors and the visual impact of the picture. Finally, this series of processing steps provides accurate data support for subsequent backlight adjustments, thereby improving energy saving effects and picture quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of an energy saving method based on a commercial liquid crystal display in an embodiment of the present application; Figure 2 is a flowchart for implementing step S10 in the energy saving method based on a commercial liquid crystal display in an embodiment of the present application; Figure 3 is a flowchart for implementing step S20 in the energy saving method based on a commercial liquid crystal display in an embodiment of the present application; Figure 4 is a flowchart for implementing step S30 in an energy saving method based on a commercial liquid crystal display in an embodiment of the present application; Figure 5 is a flowchart for implementing step S30 in the energy saving method based on a commercial liquid crystal display in an embodiment of the present application; Figure 6 is a flow chart of an implementation of an energy-saving method based on a commercial liquid crystal display in an embodiment of the present application; Figure 7 It is a principle block diagram of an energy-saving device based on a commercial liquid crystal display in one embodiment of the present application; Figure 8 It is a schematic diagram of a device in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The present application is further described in detail below in conjunction with the accompanying drawings.

[0025] In one embodiment, if Figure 1 As shown, the present application discloses an energy-saving method based on a commercial liquid crystal display, which specifically includes the following steps: S10: Collect real-time display content and ambient brightness data of the LCD display.

[0026] Specifically, a sensor is used to monitor the image frames of the displayed content of the LCD in real time, and then the acquired image frames are integrated to obtain the real-time display content of the LCD, and the brightness data of the current environment in which the LCD is located is detected and recorded by using an environmental sensor.

[0027] S20: performing image processing on the real-time display content to obtain brightness distribution characteristics and color information of the real-time display content.

[0028] In this embodiment, the brightness distribution feature refers to the brightness level of different regions in the image. The color information refers to the color composition in the image.

[0029] Specifically, the collected display content images are processed, such as denoising, contrast enhancement, etc., to improve image quality, and image segmentation and feature extraction algorithms are applied to identify different areas in the display content, and analyze the brightness distribution characteristics and color information of these areas.

[0030] S30: transmitting the brightness distribution characteristics and color information as well as the ambient brightness data to a pre-trained display model for analysis, and obtaining target brightness values ​​of each backlight area of ​​the liquid crystal display through analysis.

[0031] Specifically, the extracted brightness distribution characteristics, color information and ambient brightness data are transmitted to the central processing unit through the network. On the central processing unit, a pre-trained display model receives these data as input. The pre-trained display model understands the relationship between the display content and the ideal backlight brightness. The model analyzes the input data and predicts the target brightness values ​​of each backlight area of ​​the display under the current display content and environmental conditions.

[0032] S40: adjusting the backlight brightness of the liquid crystal display according to the target brightness value of each backlight zone to achieve energy saving and optimize the user viewing experience.

[0033] Specifically, based on the prediction results of the model, the system automatically adjusts the backlight system of the LCD display. By intelligently adjusting the backlight brightness, the system can reduce unnecessary energy consumption while maintaining image quality, achieving energy saving. Optimizing the backlight brightness can reduce screen reflections and overly bright or dark areas, providing a more comfortable and clearer viewing experience, especially under different ambient brightness and different display content.

[0034] By adopting the above technical solution, by collecting the real-time display content and ambient brightness data of the LCD display, the brightness and color distribution of the display content, as well as the light intensity of the surrounding environment can be fully and comprehensively grasped in real time. During the operation of the LCD display, the display content and ambient lighting are dynamically changing. Real-time collection of these data ensures that the system can capture the changes at any time. The brightness and color distribution of the display content directly affect the backlight demand, while the ambient brightness determines the perceived brightness of the overall display effect. By simultaneously monitoring these two types of key data, the system can accurately evaluate the current display demand, so that when adjusting the backlight brightness, it can save energy and maintain the best visual effect, ultimately improving energy saving efficiency and optimizing the user viewing experience; according to the target brightness value of each backlight area obtained by model analysis, the system will automatically adjust the backlight brightness of the display. This adjustment is intended to ensure that the display can provide the best viewing experience under different display content and environmental conditions, achieve energy saving and optimize the user viewing experience. By intelligently adjusting the backlight brightness, the system can reduce energy consumption without sacrificing viewing quality and achieve energy saving.

[0035] In one embodiment, if Figure 2 As shown, in step S10, the real-time display content and ambient brightness data of the liquid crystal display are collected, which specifically includes: S11: Acquire image frames of the content displayed on the liquid crystal display in real time through an image acquisition device.

[0036] Specifically, an image acquisition device, such as a high frame rate camera, is used to shoot the screen of the LCD display in real time to obtain continuous image frames. These image frames represent the display status of the display at different time points and are the basis for analyzing the display content.

[0037] S12: Continuously sampling the image frames of the display content, and statistically analyzing the sampling information to obtain the real-time display content of the liquid crystal display.

[0038] Specifically, the captured image frames are sampled continuously, that is, image data is collected within a certain time interval. The sampling can be full-frame sampling or local sampling of a specific area in the image frame. The sampled image data are statistically analyzed, which includes calculating the average, median, distribution and other statistical information of the brightness. Through analysis, the brightness changes, color distribution and other characteristics of the displayed content can be understood, and finally the real-time display content of the LCD display can be obtained.

[0039] S13: Collecting brightness data of the environment around the liquid crystal display through the ambient light sensor as ambient brightness data.

[0040] Specifically, the ambient brightness around the LCD display is measured through an ambient light sensor, such as a photoresistor or a photodiode. The ambient light sensor can quantify the light intensity and provide accurate data of the ambient brightness. The collected ambient brightness data will serve as important reference information for subsequent analysis and adjustment.

[0041] In one embodiment, if Figure 3 As shown, in step S20, image processing is performed on the real-time display content to obtain the brightness distribution characteristics and color information of the real-time display content, which specifically includes: S21: using a brightness histogram analysis technique, calculating the brightness distribution of the real-time display content in each image frame, and obtaining a brightness distribution feature of the real-time display content.

[0042] Specifically, the system uses brightness histogram analysis technology to calculate the brightness distribution of real-time display content in each image frame. For continuous image frames acquired in real time, the system will calculate the brightness histogram of each frame separately to identify the concentrated area of ​​brightness in the image frame, as well as the range and mode of brightness change. After analyzing the brightness histogram, the brightness distribution characteristics of the display content can be obtained, such as the peak value, average value, median value, standard deviation, etc. of the brightness. These characteristics reflect the overall brightness level of the display content and the dynamic range of brightness change, and finally the brightness distribution characteristics of the real-time display content are obtained. S22: extracting color components and their distribution ratios in the image of the real-time display content through color distribution analysis to obtain color information of the real-time display content.

[0043] Specifically, through color distribution analysis, the system will identify the main color components in the image and the proportion of each color in the image. Through color distribution analysis, the system obtains the color information of the real-time displayed content, including dominant color, color diversity, color contrast and other characteristics. This information helps to understand the visual characteristics of the displayed content and how to adjust the backlight to optimize color performance.

[0044] In one embodiment, if Figure 4 As shown, before step S30, that is, before the brightness distribution characteristics and color information and the ambient brightness data are transmitted to the pre-trained display model for analysis, and before the target brightness value of each backlight area of ​​the liquid crystal display is obtained by analysis, the energy saving method based on the commercial liquid crystal display further includes: S301: Collect display content data in different environments, and pre-process the display content data in different environments to obtain a training set.

[0045] Specifically, data on display content is collected from a variety of environmental conditions. These data may include images or video frames of different brightness, color, and resolution. The display content data under different environments is preprocessed. The preprocessing step is to make the collected data suitable for training models, including normalizing pixel values, adjusting image size, and data enhancement. For example, rotating, scaling, and cropping images to increase data diversity, etc. The preprocessed data is organized into a training set for training machine learning models.

[0046] S302: construct a display model based on a convolutional neural network and a recurrent neural network, perform forward propagation and back-propagation training on the display model using a training set, and use a model pruning method to optimize the display model after forward propagation and back-propagation training to obtain a pre-trained display model.

[0047] Specifically, a display model is constructed based on convolutional neural networks and recurrent neural networks. The convolutional neural network can capture local features in the image and construct more complex and abstract feature representations layer by layer. The recurrent neural network can remember previously processed data information and is suitable for time series prediction or dynamic image content analysis. The display model is trained by forward propagation and back propagation using the training set, and the display model after forward propagation and back propagation training is optimized using the model pruning method. The model structure is simplified by removing unimportant connections in the neural network, the model complexity is reduced, overfitting is prevented, and the generalization ability of the model is improved, ultimately obtaining a pre-trained display model.

[0048] In one embodiment, if Figure 5As shown, in step S40, the brightness distribution characteristics and color information as well as the ambient brightness data are transmitted to the pre-trained display model for analysis, and the target brightness values ​​of each backlight area of ​​the liquid crystal display are obtained by analysis, specifically including: S31: Perform multi-level analysis on brightness distribution characteristics and color information using a pre-trained model to generate brightness adjustment coefficients for each backlight area.

[0049] Specifically, a trained display model is used, which is able to understand the complex features of the display content, such as brightness distribution and color information. The model processes data at different levels of abstraction, from simple edge and texture features to complex scene understanding. The model analyzes brightness distribution features, including the brightness histogram of the image, the pattern of brightness distribution, etc., to identify the brightness requirements of different areas in the image. At the same time, the model analyzes color information, including color distribution, saturation, and hue, to understand the color requirements of the display content. Based on the multi-level analysis results of the model, a brightness adjustment coefficient is generated for each backlight area of ​​the LCD display, indicating the amount by which the backlight brightness needs to be increased or decreased to achieve an ideal display effect.

[0050] S32: Calculate the target brightness value of each backlight area of ​​the liquid crystal display according to the brightness adjustment coefficient of each backlight area.

[0051] Specifically, the target brightness value of each backlight area is calculated using the brightness adjustment coefficient combined with the actual brightness value of the current backlight area. This calculation process may involve simple multiplication or more complex algorithms to ensure that the target brightness value meets both display requirements and energy efficiency.

[0052] In one embodiment, if Figure 6 As shown, the energy saving method based on commercial liquid crystal display also includes: S50: Acquire and record the user's viewing habits and preference data, input the user's viewing habits and preference data into a pre-trained display model, and adjust parameters in the pre-trained display model.

[0053] Specifically, the system collects data by observing users' usage patterns, such as users' viewing behaviors in different time periods, preferred brightness and contrast settings, and commonly used display content types, and provides the collected user data as input to a pre-trained display model. These data help the model understand users' personalized needs, thereby providing a display effect that is more in line with user preferences. Based on users' viewing habits and preference data, the system automatically adjusts the parameters in the display model. Parameter adjustments may include brightness adjustment coefficients, contrast, color saturation, etc., to ensure that the display settings meet the user's specific preferences.

[0054] S60: Record the energy-saving effect after the backlight brightness is adjusted in real time, generate an energy-saving report according to the energy-saving effect, and feed back the energy-saving report to the user end.

[0055] Specifically, the system will continuously monitor and record the energy consumption after the backlight brightness is adjusted. By comparing the energy consumption data before and after the adjustment, the system can evaluate the effectiveness of the energy-saving measures. Using the collected energy consumption data, the system will generate a detailed energy-saving report. The report may include specific energy-saving values, energy-saving ratios, recommended optimal viewing settings and other information. The energy-saving report will be displayed to the user through the user interface or sent to the user through email, application push, etc. Users can understand how their viewing habits affect energy consumption based on these feedbacks, and make corresponding adjustments to achieve more efficient energy use.

[0056] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0057] In one embodiment, a power-saving device based on a commercial liquid crystal display is provided, and the power-saving device based on a commercial liquid crystal display corresponds one-to-one to the power-saving method based on a commercial liquid crystal display in the above embodiment. Figure 7 As shown, the energy-saving device based on a commercial liquid crystal display includes a data acquisition module, an image processing module, an analysis module and an adjustment module. The detailed description of each functional module is as follows: A data collection module is used to collect real-time display content and ambient brightness data of the LCD display; An image processing module is used to perform image processing on the real-time display content to obtain brightness distribution characteristics and color information of the real-time display content; An analysis module is used to transmit the brightness distribution characteristics and color information as well as the ambient brightness data to a pre-trained display model for analysis, and to obtain the target brightness value of each backlight area of ​​the liquid crystal display; The adjustment module is used to adjust the backlight brightness of the LCD display according to the target brightness value of each backlight zone to achieve energy saving and optimize the user viewing experience.

[0058] Optionally, the energy-saving device based on a commercial liquid crystal display further comprises: A model adjustment module, used to obtain and record the user's viewing habits and preference data, input the user's viewing habits and preference data into a pre-trained display model, and adjust the parameters in the pre-trained display model; The feedback module is used to record the energy-saving effect after the backlight brightness is adjusted in real time, generate an energy-saving report according to the energy-saving effect, and feed back the energy-saving report to the user end.

[0059] A historical data collection module is used to collect display content data in different environments and pre-process the display content data in different environments to obtain a training set; The model training module is used to build a display model based on a convolutional neural network and a recurrent neural network, perform forward and backward propagation training on the display model using a training set, and use a model pruning method to optimize the display model after forward and backward propagation training to obtain a pre-trained display model.

[0060] Optionally, the data collection module includes: An image acquisition submodule, used to acquire image frames of the content displayed on the liquid crystal display in real time through an image acquisition device; The sampling submodule is used to continuously sample the image frames of the display content and perform statistical analysis on the sampling information to obtain the real-time display content of the liquid crystal display; The sensing detection submodule is used to collect brightness data of the environment around the liquid crystal display through an ambient light sensor as ambient brightness data.

[0061] Optionally, the image processing module includes: The brightness distribution submodule is used to calculate the brightness distribution of the real-time display content in each image frame by using the brightness histogram analysis technology to obtain the brightness distribution characteristics of the real-time display content; The color analysis submodule is used to extract the color components and their distribution ratios in the image of the real-time display content through color distribution analysis to obtain the color information of the real-time display content.

[0062] Optional analysis modules include: A hierarchical analysis submodule is used to perform multi-level analysis on brightness distribution characteristics and color information using a pre-trained model to generate brightness adjustment coefficients for each backlight area; The calculation submodule is used to calculate the target brightness value of each backlight area of ​​the liquid crystal display according to the brightness adjustment coefficient of each backlight area.

[0063] For the specific definition of the energy-saving device based on a commercial liquid crystal display, please refer to the definition of the energy-saving method based on a commercial liquid crystal display above, which will not be repeated here. Each module in the above energy-saving device based on a commercial liquid crystal display can be implemented in whole or in part by software, hardware and a combination thereof. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0064] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an energy-saving method based on a commercial liquid crystal display is implemented.

[0065] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: Collect real-time display content and ambient brightness data of LCD monitors; Performing image processing on the real-time display content to obtain brightness distribution characteristics and color information of the real-time display content; The brightness distribution characteristics and color information as well as the ambient brightness data are transmitted to the pre-trained display model for analysis, and the target brightness value of each backlight area of ​​the liquid crystal display is obtained by analysis; Adjust the backlight brightness of the LCD display according to the target brightness value of each backlight zone to achieve energy saving and optimize the user viewing experience.

[0066] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Collect real-time display content and ambient brightness data of LCD monitors; Performing image processing on the real-time display content to obtain brightness distribution characteristics and color information of the real-time display content; The brightness distribution characteristics and color information as well as the ambient brightness data are transmitted to the pre-trained display model for analysis, and the target brightness value of each backlight area of ​​the liquid crystal display is obtained by analysis; Adjust the backlight brightness of the LCD display according to the target brightness value of each backlight zone to achieve energy saving and optimize the user viewing experience.

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

[0068] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

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

Claims

1. An energy saving method based on a commercial liquid crystal display, characterized in that: The energy saving method based on commercial liquid crystal display comprises: Collect real-time display content and ambient brightness data of LCD monitors; Performing image processing on the real-time display content to obtain brightness distribution characteristics and color information of the real-time display content; The brightness distribution characteristics, the color information and the ambient brightness data are transmitted to a pre-trained display model for analysis, and the target brightness value of each backlight area of ​​the liquid crystal display is obtained by analysis; The backlight brightness of the liquid crystal display is adjusted according to the target brightness values ​​of the respective backlight zones to achieve energy saving and optimize the user viewing experience.

2. The energy saving method based on commercial liquid crystal display according to claim 1, characterized in that: The collecting of real-time display content and ambient brightness data of the liquid crystal display comprises: Acquire image frames of the content displayed by the liquid crystal display in real time through an image acquisition device; Continuously sampling the image frames of the display content, and statistically analyzing the sampling information to obtain the real-time display content of the liquid crystal display; The brightness data of the environment around the liquid crystal display is collected by an ambient light sensor as the ambient brightness data.

3. The energy saving method based on commercial liquid crystal display according to claim 1, characterized in that: The performing image processing on the real-time display content to obtain the brightness distribution characteristics and color information of the real-time display content includes: Calculating the brightness distribution of the real-time display content in each image frame by using a brightness histogram analysis technique to obtain brightness distribution characteristics of the real-time display content; By color distribution analysis, the color components and their distribution ratios in the image of the real-time display content are extracted to obtain the color information of the real-time display content.

4. The energy saving method based on commercial liquid crystal display according to claim 1, characterized in that: Before transmitting the brightness distribution characteristics and the color information to a pre-trained display model for analysis to obtain target brightness values ​​of each backlight area of ​​the liquid crystal display, the energy saving method based on a commercial liquid crystal display further includes: Collecting display content data in different environments, and preprocessing the display content data in the different environments to obtain a training set; A display model is constructed based on a convolutional neural network and a recurrent neural network, the display model is trained by forward propagation and back propagation using the training set, and the display model after forward propagation and back propagation training is optimized using a model pruning method to obtain the pre-trained display model.

5. The energy saving method based on commercial liquid crystal display according to claim 1, characterized in that: The step of transmitting the brightness distribution characteristics and the color information to a pre-trained display model for analysis, and obtaining target brightness values ​​of each backlight area of ​​the liquid crystal display through analysis includes: Performing multi-level analysis on brightness distribution characteristics and color information using the pre-trained model to generate brightness adjustment coefficients for each backlight area; According to the brightness adjustment coefficients of the respective backlight areas, target brightness values ​​of the respective backlight areas of the liquid crystal display are calculated.

6. The energy saving method based on commercial liquid crystal display according to claim 1, characterized in that: The energy saving method based on commercial liquid crystal display also includes: Acquire and record the user's viewing habits and preference data, input the user's viewing habits and preference data into the pre-trained display model, and adjust the parameters in the pre-trained display model; The energy-saving effect after the backlight brightness is adjusted is recorded in real time, an energy-saving report is generated according to the energy-saving effect, and the energy-saving report is fed back to the user end.

7. An energy-saving device based on a commercial liquid crystal display, characterized in that: The energy-saving device based on a commercial liquid crystal display comprises: A data collection module is used to collect real-time display content and ambient brightness data of the LCD display; An image processing module, used to perform image processing on the real-time display content to obtain brightness distribution characteristics and color information of the real-time display content; An analysis module is used to transmit the brightness distribution characteristics, the color information and the ambient brightness data to a pre-trained display model for analysis, and obtain target brightness values ​​of each backlight area of ​​the liquid crystal display through analysis; The adjustment module is used to adjust the backlight brightness of the liquid crystal display according to the target brightness value of each backlight area to achieve energy saving and optimize the user viewing experience.

8. The energy-saving device based on a commercial liquid crystal display according to claim 7, characterized in that: The energy-saving device based on a commercial liquid crystal display further comprises: A model adjustment module, used to obtain and record the user's viewing habits and preference data, and input the user's viewing habits and preference data into the pre-trained display model to adjust the parameters in the pre-trained display model; The feedback module is used to record the energy-saving effect after the backlight brightness is adjusted in real time, generate an energy-saving report according to the energy-saving effect, and feed back the energy-saving report to the user end.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the energy saving method based on a commercial liquid crystal display according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the energy saving method based on a commercial liquid crystal display according to any one of claims 1 to 6 are implemented.

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