Display Screen Control Method, Device, Equipment and Storage Medium of Smart Watch

Abstract

The present invention relates to the technical field of data processing, and provides a method, device, equipment and storage medium for controlling the display screen of a smart watch. It includes real-time detection of the current state of the display screen of the smart watch to obtain the brightness parameter, color temperature parameter and display content distribution information of the display screen, and then performing analysis and adjustment to obtain the partition display output and the pre-display interface; analyzing and processing the partition display output and the pre-display interface to generate an optimization parameter group, and controlling the smart watch based on the optimization parameter group. By detecting, analyzing and adjusting the brightness parameter, color temperature parameter and display content distribution information of the display screen to generate an optimization parameter group and then controlling the smart watch, the smart watch can provide the best display effect in different usage scenarios, improving the problem that when the display content on the screen is complex and fine display is required, the traditional brightness and color temperature control methods are difficult to achieve ideal effects and there is an uneven display effect.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and in particular to a display screen control method, device, equipment and storage medium for smart watches. Background Art

[0002] With the rapid development of technology, the smart wearable device market has gradually emerged, and smart watches have become one of the most popular products. Smart watches can not only provide basic functions such as time display and daily activity recording, but also realize various functions such as health monitoring, message reminder, and navigation. Their portability and versatility meet the needs of consumers for a convenient life and promote the rapid development of the smart watch industry.

[0003] In the prior art, the display screen control of smart watches is mainly achieved through brightness sensors and color temperature sensors. The brightness sensor detects changes in ambient light and adjusts the brightness of the display screen according to the light intensity to ensure clear display in different lighting environments. The color temperature sensor can adjust the color temperature of the display screen to make the screen display effect more in line with the comfort of the human vision. This control method realizes the adaptive display of smart watches in different environments and improves the user experience.

[0004] For the above technical solution, although the brightness and color temperature of the display screen can be adjusted through brightness sensors and color temperature sensors to adapt to different ambient lighting conditions, when the display content on the screen is complex and requires fine display, the traditional brightness and color temperature control methods are difficult to achieve ideal effects, and there is a problem of uneven display effects. Summary of the Invention

[0005] In order to improve the problem that when the display content on the screen is complex and requires fine display, the traditional brightness and color temperature control methods are difficult to achieve ideal effects and there is a problem of uneven display effects, this application provides a display screen control method, device, equipment and storage medium for smart watches.

[0006] The present invention provides a method for controlling the display screen of a smart watch, including: real-time detecting the current state of the display screen of the smart watch to obtain the brightness parameter, color temperature parameter and display content distribution information of the display screen; adjusting the backlight module of the display screen based on the brightness parameter and the color temperature parameter to obtain a full-screen brightness control signal and a full-screen color temperature control signal; inputting the full-screen brightness control signal and the full-screen color temperature control signal into a preset display adjustment module to dynamically adjust the pixel partitions of the display screen to obtain partition brightness distribution information, and using the partition brightness distribution information and the display content distribution information to perform refined adjustment on each pixel of the display screen to obtain a pixel driving signal; performing partition driving on the display screen based on the pixel driving signal to obtain a partition display output, and preferentially adjusting the interaction area of the display screen according to the display content distribution information and user interaction data to obtain a pre-display interface; analyzing and processing the partition display output and the pre-display interface to generate an optimization parameter group, and controlling the smart watch based on the optimization parameter group.

[0007] As a preferred solution, the step of real-time detecting the current state of the display screen of the smart watch to obtain the brightness parameter, color temperature parameter and display content distribution information of the display screen includes: collecting the ambient light intensity and color temperature information around the display screen through a photodiode sensor module to obtain an ambient brightness parameter and an ambient color temperature parameter, and applying a Gaussian filtering algorithm to denoise the ambient brightness parameter and the ambient color temperature parameter to obtain an ambient light correction parameter; inputting the ambient light correction parameter, the light emission intensity of the display screen and the RGB color output information into a preset multi-layer perceptron model to obtain the brightness parameter and the color temperature parameter of the display screen; dividing the display content of the display screen into regions to obtain initial display content distribution information and initial partition feature parameters; using a watershed segmentation algorithm based on gray gradient to perform partition refinement processing on the initial display content distribution information to obtain refined brightness distribution information, and performing fitting processing on the refined brightness distribution information and the initial partition feature parameters to obtain brightness distribution information; generating screen state feature parameters and regional display features according to the brightness distribution information, and using principal component analysis to extract the main features of the screen state feature parameters and the regional display features to obtain the display content distribution information.

[0008] As a preferred solution, the step of adjusting the backlight module of the display screen based on the brightness parameter and the color temperature parameter to obtain a full-screen brightness control signal and a full-screen color temperature control signal includes: parsing the brightness parameter and the color temperature parameter through a Kalman filtering algorithm to obtain a target brightness adjustment value and a target color temperature adjustment value, and performing a partition mapping process on the target brightness adjustment value and the target color temperature adjustment value by using a preset linear regression model to obtain a brightness correction parameter and a color temperature correction parameter for each display partition; according to the brightness correction parameter, adjusting the light-emitting units of the backlight module of the display screen region by region through a pulse width modulation technique to obtain a regional brightness control signal; according to the color temperature correction parameter, applying a proportional integral derivative control algorithm to refine the adjustment of the color temperature adjustment unit of the backlight module of the display screen to obtain a regional color temperature control signal; and respectively performing a weighted average process on the regional brightness control signal and the regional color temperature control signal to generate a full-screen brightness control signal and a full-screen color temperature control signal.

[0009] As a preferred solution, the step of parsing the brightness parameter and the color temperature parameter through a Kalman filtering algorithm to obtain a target brightness adjustment value and a target color temperature adjustment value, and performing a partition mapping process on the target brightness adjustment value and the target color temperature adjustment value by using a preset linear regression model to obtain a brightness correction parameter and a color temperature correction parameter for each display partition includes: performing a time series analysis on the brightness parameter by using a Kalman filtering algorithm to obtain a brightness trend prediction value and a brightness residual, performing a moving average filtering process on the brightness trend prediction value to obtain a brightness reference value, and performing a fast Fourier transform on the brightness residual to obtain a brightness frequency domain characteristic parameter; based on the brightness reference value and the brightness frequency domain characteristic parameter, performing a piecewise regression calculation by using a polynomial fitting method of the least squares method to obtain an initial brightness adjustment value and a brightness offset correction value, and performing a weighted synthesis on the initial brightness adjustment value and the brightness offset correction value to obtain a target brightness adjustment value; performing a recursive analysis on the color temperature parameter by using a Kalman filtering algorithm to obtain a color temperature trend prediction value and a color temperature dynamic change parameter, performing a wavelet transform analysis on the color temperature trend prediction value to obtain a multi-resolution color temperature detail parameter, calculating a significance weight of the color temperature dynamic change parameter by using an entropy weight method to generate a color temperature change significance parameter; weighting the multi-resolution color temperature detail parameter and the color temperature change significance parameter based on a locally weighted regression method to generate a target color temperature adjustment value; performing a per-partition fitting process on the target brightness adjustment value by using a weighted linear regression calculation method for regional partitioning to obtain a brightness correction parameter for each display partition; and performing a per-partition refinement process on the target color temperature adjustment value based on a regression model of a support vector machine to generate a color temperature correction parameter for each display partition.

[0010] As a preferred solution, the step of inputting the full-screen brightness control signal and the full-screen color temperature control signal into a preset display adjustment module to dynamically adjust the pixel partitions of the display screen to obtain partition brightness distribution information, and using the partition brightness distribution information and the display content distribution information to perform refined adjustment on each pixel of the display screen to obtain a pixel driving signal includes: resampling the full-screen brightness control signal and the full-screen color temperature control signal by using a bilinear interpolation algorithm to adjust the initial pixel brightness distribution of each display partition to obtain the adjusted partition brightness distribution information; performing cross-analysis on the adjusted partition brightness distribution information and the display content distribution information by using a cosine similarity calculation method to obtain pixel characteristic parameters; performing refined processing on the pixel characteristic parameters based on a bilateral filtering algorithm to obtain a pixel brightness control signal and a pixel color temperature control signal for each pixel; and performing fusion processing on the pixel brightness control signal and the pixel color temperature control signal by using a homography matrix transformation algorithm to obtain a pixel driving signal.

[0011] As a preferred solution, the step of performing partition driving on the display screen based on the pixel driving signal to obtain a partition display output, and preferentially adjusting the interaction area of the display screen according to the display content distribution information and user interaction data to obtain a pre-display interface includes: performing partition mapping on the pixel driving signal by using a Voronoi diagram generation algorithm to generate a partition driving signal, and independently driving each partition of the display screen by using the partition driving signal to obtain a partition display output; classifying the partition display output and the display content distribution information by using a support vector machine to obtain the display priority of each area, calculating the weight value of the display priority and the user interaction data by using an entropy weight method to identify an interaction priority area; wherein the user interaction data includes any one of the following: touch interaction data, gesture interaction data, voice input data; preferentially adjusting the display parameters of the interaction priority area by using a linear interpolation method to obtain an enhanced interaction partition display output; and performing weighted linear fusion processing on the partition display output and the enhanced interaction partition display output to generate a pre-display interface.

[0012] As a preferred solution, the step of analyzing and processing the partitioned display output and the pre-display interface to generate an optimized parameter group and controlling the smart watch based on the optimized parameter group includes: extracting features of the partitioned display output and the pre-display interface by using a convolutional neural network to obtain interface feature parameters and partitioned display output characteristic data, and generating an optimized parameter group by performing fusion processing on the interface feature parameters and the partitioned display output characteristic data by using linear discriminant analysis; parsing the optimized parameter group to generate a screen refresh rate adjustment parameter, a touch response adjustment parameter, and a display content arrangement parameter; dynamically adjusting the display refresh rate according to the screen refresh rate adjustment parameter by applying a servo control algorithm; adjusting the touch module according to the touch response adjustment parameter by applying a generalized predictive control algorithm; and optimizing the layout and arrangement of the display screen content of the smart watch according to the display content arrangement parameter.

[0013] The present application further provides a display screen control device for a smart watch, including: a detection module for detecting the current state of the display screen of the smart watch in real time to obtain the brightness parameter, color temperature parameter, and display content distribution information of the display screen; an adjustment module for adjusting the backlight module of the display screen based on the brightness parameter and the color temperature parameter to obtain a full-screen brightness control signal and a full-screen color temperature control signal; an adjustment module for inputting the full-screen brightness control signal and the full-screen color temperature control signal into a preset display adjustment module to dynamically adjust the pixel partitions of the display screen to obtain partitioned brightness distribution information, and using the partitioned brightness distribution information and the display content distribution information to perform refined adjustment on each pixel of the display screen to obtain a pixel drive signal; a drive module for performing partitioned driving on the display screen based on the pixel drive signal to obtain a partitioned display output, and preferentially adjusting the interaction area of the display screen according to the display content distribution information and user interaction data to obtain a pre-display interface; and a control module for analyzing and processing the partitioned display output and the pre-display interface to generate an optimized parameter group and controlling the smart watch based on the optimized parameter group.

[0014] The present application further provides an electronic device, including a memory and a processor, where the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, it implements the display screen control method of the smart watch described in any one of the above.

[0015] The present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is run by a processor, the processor is caused to execute the display screen control method of the smart watch described in any one of the above.

[0016] Compared with the prior art, the present application has the following beneficial effects: high flexibility and uniform display effect. By detecting the brightness parameter, color temperature parameter and display content distribution information of the display screen in real time, the current state of the display screen can be accurately obtained; based on the brightness parameter and color temperature parameter, the backlight module of the display screen is adjusted to achieve automatic adjustment of the full-screen brightness and color temperature; through the preset display adjustment module, the pixel partition of the display screen is dynamically adjusted to achieve independent and refined adjustment of each pixel, ensuring the uniformity of the display effect; based on the pixel driving signal for partition driving, the display effect of the interaction area can be preferentially adjusted according to the display content distribution information and user interaction data, improving the user experience; by analyzing and processing the partition display output and pre-display interface, an optimization parameter group is generated, and the display effect is optimized based on the optimization parameter group, so that the smart watch can provide the best display effect and user experience in different usage scenarios, improving the problem that the traditional brightness and color temperature control methods are difficult to achieve ideal effects and there is uneven display effect when the display content on the screen is complex and fine display is required. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to these drawings.

[0018] The structures, proportions, sizes, etc. shown in the drawings of this specification are only used to cooperate with the content disclosed in the specification for those who are familiar with this technology to understand and read, and are not used to limit the limited conditions under which the present invention can be implemented. Therefore, they do not have technical essence. Any modification of the structure, change of the proportional relationship or adjustment of the size, without affecting the effects that the present invention can produce and the purposes that can be achieved, should still fall within the scope that the technical content disclosed by the present invention can cover.

[0019] Figure 1 is a schematic flowchart of a display screen control method for a smart watch provided by an embodiment of the present invention;

[0020] Figure 2 is a schematic block diagram of the structure of a display screen control device for a smart watch provided by an embodiment of the present invention;

[0021] Figure 3 is a schematic block diagram of the structure of an electronic device provided by an embodiment of the present invention.

[0022] Description of the reference numerals:

[0023] 10. Display screen control device of smart watch; 11. Detection module; 12. Adjustment module; 13. Regulation module; 14. Driving module; 15. Control module; 20. Electronic device; 21. Memory; 22. Processor. Detailed implementation manners

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0025] The flowcharts shown in the accompanying drawings are only illustrative examples, and do not necessarily include all contents and operations / steps, nor do they necessarily need to be executed in the described order. For example, some operations / steps can also be decomposed, combined or partially merged, so the actual execution order may be changed according to the actual situation.

[0026] It should also be understood that the terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. As used in the specification of this application and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0027] It should be further understood that the term "and / or" used in the specification of this application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0028] The following further illustrates the technical solutions of the present invention with reference to the accompanying drawings and through specific implementation manners.

[0029] Embodiment 1:

[0030] As Figure 1 shown, Embodiment 1:

[0031] This application provides a method for controlling the display screen of a smart watch, including steps S100 to S500.

[0032] Step S100: Real-time detect the current state of the display screen of the smart watch to obtain the brightness parameter, color temperature parameter and display content distribution information of the display screen.

[0033] In this step, the current state of the display screen is detected in real time by a sensor module, which includes a brightness sensor, a color temperature sensor, and an image sensor. Specifically, the brightness sensor is used to detect the brightness of the ambient light, the color temperature sensor is used to detect the color temperature of the ambient light, and the image sensor is used to obtain the distribution information of the display content on the display screen.

[0034] For example, when a user uses a smartwatch in an environment with strong outdoor light, the brightness sensor will detect a higher ambient brightness parameter, the color temperature sensor will detect a change in the color temperature parameter, and at the same time, the image sensor will obtain the distribution information of the current display content.

[0035] Step S200: Based on the brightness parameter and the color temperature parameter, adjust the backlight module of the display screen to obtain a full-screen brightness control signal and a full-screen color temperature control signal.

[0036] In this step, the backlight module of the display screen is adjusted by a control module. The control module generates a full-screen brightness control signal and a full-screen color temperature control signal according to the brightness parameter and the color temperature parameter. Specifically, the control module adjusts the brightness of the backlight module according to the brightness parameter and adjusts the color temperature of the backlight module according to the color temperature parameter, so that the display screen adapts to the current ambient light conditions.

[0037] For example, when the ambient brightness is high, the control module will generate a stronger full-screen brightness control signal to increase the brightness of the display screen, so that the user can still clearly see the screen content in a strong light environment. At the same time, the color temperature control signal will adjust the color temperature of the backlight module to make the display effect more comfortable.

[0038] Step S300: Input the full-screen brightness control signal and the full-screen color temperature control signal into a preset display adjustment module to dynamically adjust the pixel partitions of the display screen to obtain partition brightness distribution information. Use the partition brightness distribution information and the display content distribution information to finely adjust each pixel of the display screen to obtain a pixel drive signal.

[0039] In this step, the pixel partitions of the display screen are dynamically adjusted by a display adjustment module. The display adjustment module finely adjusts the brightness and color temperature of each pixel partition according to the full-screen brightness control signal and the full-screen color temperature control signal. Specifically, the display adjustment module divides the screen into multiple pixel partitions and independently adjusts the brightness and color temperature of each pixel partition according to the partition brightness distribution information and the display content distribution information to generate corresponding pixel drive signals.

[0040] For example, when the display content distribution information shows that the left half of the display screen mainly consists of dark images while the right half mainly consists of light images, the display adjustment module will, based on the partition brightness distribution information, lower the brightness of the pixel partitions in the left half and increase the brightness of the pixel partitions in the right half to ensure the uniformity of the overall display effect.

[0041] Step S400: Perform partition driving on the display screen based on the pixel driving signal to obtain a partition display output, and preferentially adjust the interaction area of the display screen according to the display content distribution information and user interaction data to obtain a pre-display interface.

[0042] In this step, the partition driving module performs partition driving on the display screen. The partition driving module drives each pixel partition according to the pixel driving signal. Specifically, the partition driving module divides the display screen into multiple regions, independently adjusts the brightness and color temperature of each region, and preferentially adjusts the display effect of the user interaction area based on the display content distribution information and user interaction data to generate a pre-display interface.

[0043] For example, when the user interacts with a certain area of the display screen, the partition driving module will preferentially increase the brightness and color temperature of this interaction area to ensure that the user can clearly see the screen content during interaction and improve the user experience.

[0044] Step S500: Analyze and process the partition display output and the pre-display interface to generate an optimization parameter group, and control the smart watch based on the optimization parameter group.

[0045] In this step, the analysis module analyzes and processes the partition display output and the pre-display interface. The analysis module generates an optimization parameter group according to the feedback information of the display effect. Specifically, the analysis module comprehensively analyzes the partition display output of the display screen, combines the user interaction data, evaluates the display effect, and generates an optimization parameter group including brightness adjustment, color temperature adjustment, etc.

[0046] For example, when the user feedbacks that the display effect of a certain area is not ideal, the analysis module will adjust the partition display output according to this feedback information to generate an optimization parameter group to improve the overall display effect of the display screen.

[0047] In this embodiment, by detecting the current state of the display screen of the smart watch in real time, the brightness parameter, color temperature parameter, and display content distribution information of the display screen are obtained. Then, based on the brightness parameter and color temperature parameter, the backlight module of the display screen is adjusted to generate a full-screen brightness control signal and a full-screen color temperature control signal. These signals are input into a preset display adjustment module to dynamically adjust the pixel partitions of the display screen, obtaining partition brightness distribution information. Using the partition brightness distribution information and the display content distribution information, each pixel of the display screen is finely adjusted to generate a pixel drive signal. Finally, based on the pixel drive signal, the display screen is partition-driven to obtain a partition display output, and according to the display content distribution information and user interaction data, the interaction area of the display screen is preferentially adjusted to generate a pre-display interface. Finally, by analyzing and processing the partition display output and the pre-display interface, an optimization parameter group is generated to control the smart watch. The fine adjustment of the display screen of the smart watch is realized, improving the uniformity and clarity of the display effect. This method can not only automatically adjust the brightness and color temperature according to the ambient light conditions, but also perform partition driving according to the display content and user interaction data, so that the display screen can provide the best display effect and user experience in different usage scenarios. In addition, this method can also optimize the display effect of the interaction area, improving the operation convenience and visual comfort of the user.

[0048] Embodiment 2:

[0049] In step S100, the ambient light intensity and color temperature information around the display screen are collected by a photodiode sensor module to obtain an ambient brightness parameter and an ambient color temperature parameter, and the Gaussian filtering algorithm is applied to denoise the ambient brightness parameter and the ambient color temperature parameter to obtain an ambient light correction parameter.

[0050] The ambient light intensity and color temperature information around the display screen are monitored in real time by a photodiode sensor module, and the ambient brightness parameter and the ambient color temperature parameter are collected. Specifically, the photodiodes in the photodiode sensor module detect the intensity and color temperature of the ambient light and transmit the detection data to the signal processing module. The signal processing module applies the Gaussian filtering algorithm to denoise the collected ambient brightness parameter and ambient color temperature parameter to obtain a stable and accurate ambient light correction parameter.

[0051] For example, when the user enters from indoors to outdoors, the photodiode sensor module will detect a significant change in the ambient light intensity, and the Gaussian filtering algorithm is used to remove the noise in the ambient light signal to ensure the accuracy of the ambient light correction parameter.

[0052] The ambient light correction parameter, the luminous intensity of the display screen, and the RGB color output information are input into a preset multi-layer perceptron model to obtain the brightness parameter and color temperature parameter of the display screen.

[0053] Comprehensively process the ambient light correction parameters, the luminous intensity of the display screen, and the RGB color output information through a preset multi-layer perceptron model; specifically, first normalize the ambient light correction parameters, luminous intensity, and RGB color output information, and then input them into the multi-layer perceptron model; the multi-layer perceptron model performs a non-linear mapping on the input information through a training learning algorithm, and outputs the brightness parameters and color temperature parameters of the display screen.

[0054] For example, when the ambient light intensity is high and the luminous intensity of the display screen is low, the multi-layer perceptron model will calculate the result of needing to increase the brightness parameters of the display screen, thereby improving the display effect.

[0055] Divide the display content of the display screen into regions to obtain the initial display content distribution information and initial partition feature parameters, and use the watershed segmentation algorithm based on gray gradient to refine the partition of the initial display content distribution information to obtain the refined brightness distribution information of each display region; perform a fitting process on the refined brightness distribution information and the initial partition feature parameters to obtain the brightness distribution information of each display region.

[0056] Divide the display content into regions through the K-means clustering algorithm; specifically, first perform gray processing on the display content, then apply the K-means clustering algorithm to perform clustering analysis on the processed image to obtain the initial display content distribution information and initial partition feature parameters; then use the watershed segmentation algorithm based on gray gradient to refine the partition of the initial display content distribution information to obtain the refined brightness distribution information of each display region; finally, apply the weighted least squares method to perform a fitting process on the refined brightness distribution information and the initial partition feature parameters to obtain the brightness distribution information of each display region.

[0057] For example, when the display content includes text, images, and videos, cluster similar content in the same region through the K-means clustering algorithm, then use the watershed segmentation algorithm to further refine the region boundaries, and finally calculate the brightness distribution information of each region through the weighted least squares method.

[0058] Generate screen state feature parameters and regional display features according to the brightness distribution information.

[0059] Dynamically detect the brightness and color temperature states of the display screen through the dynamic time warping algorithm; specifically, according to the brightness distribution information, real-time monitor the changes in the brightness and color temperature of the display screen, and input the monitoring data into the dynamic time warping algorithm; the algorithm extracts the screen state feature parameters and regional display features by analyzing the time series change trends of the brightness and color temperature.

[0060] For example, when the display screen switches from the daytime mode to the nighttime mode, the dynamic time warping algorithm can detect the changing trends of brightness and color temperature, and generate corresponding screen state characteristic parameters.

[0061] The principal component analysis method is used to extract the main features from the screen state characteristic parameters and the regional display characteristics, and the display content distribution information is obtained.

[0062] The principal component analysis method is used to extract the main features from the screen state characteristic parameters and the regional display characteristics; specifically, the screen state characteristic parameters and the regional display characteristics are input into the principal component analysis model, and the model performs dimensionality reduction processing on the input data, extracts the main feature variables, and obtains the optimized display content distribution information.

[0063] For example, the principal component analysis method can extract the brightness and color temperature characteristics that have the greatest impact on the display effect from the screen state characteristic parameters, and generate the simplified display content distribution information.

[0064] In step S200, the brightness parameter and the color temperature parameter are analyzed through the Kalman filtering algorithm to obtain the target brightness adjustment value and the target color temperature adjustment value, and the preset linear regression model is used to perform partition mapping processing on the target brightness adjustment value and the target color temperature adjustment value to obtain the brightness correction parameter and the color temperature correction parameter for each display partition.

[0065] The brightness parameter and the color temperature parameter are analyzed through the Kalman filtering algorithm to obtain the target brightness adjustment value and the target color temperature adjustment value; specifically, the Kalman filtering algorithm is used to perform time series analysis on the brightness parameter to obtain the brightness trend prediction value and the brightness residual, perform moving average filtering processing on the brightness trend prediction value to obtain the brightness reference value, and perform fast Fourier transform on the brightness residual to obtain the brightness frequency domain characteristic parameter; then, the Kalman filtering algorithm is used to perform recursive analysis on the color temperature parameter to obtain the color temperature trend prediction value and the color temperature dynamic change parameter, perform wavelet transform analysis on the color temperature trend prediction value to obtain the multi-resolution color temperature detail parameter, and calculate the significance weight of the color temperature dynamic change parameter through the entropy weight method to generate the color temperature change significance parameter.

[0066] For example, for the brightness parameter, the Kalman filtering algorithm can be used to predict the brightness change trend in the future for a period of time, and analyze the periodic characteristics of the brightness change through the frequency domain characteristic parameter; for the color temperature parameter, the multi-scale characteristics of the color temperature change can be analyzed through wavelet transform, and the corresponding color temperature adjustment value can be generated.

[0067] According to the brightness correction parameter, the light-emitting units of the backlight module of the display screen are adjusted region by region through the pulse width modulation technology to obtain the regional brightness control signal.

[0068] The light-emitting units of the backlight module of the display screen are adjusted region by region through pulse-width modulation technology; specifically, according to the brightness correction parameters, the display screen is divided into multiple regions, and the light-emitting units of each region are independently controlled by pulse-width modulation to generate region brightness control signals, so as to achieve precise control of the brightness of different regions.

[0069] For example, when the brightness correction parameter of a certain region is high, the pulse-width modulation technology will increase the drive current of the light-emitting units in that region to increase the region brightness; conversely, it will decrease the drive current to weaken the region brightness.

[0070] According to the color temperature correction parameters, the proportional-integral-derivative control algorithm is applied to refine the adjustment of the color temperature adjustment unit of the backlight module of the display screen to obtain region color temperature control signals.

[0071] The proportional-integral-derivative control algorithm is used to refine the adjustment of the color temperature adjustment unit of the backlight module of the display screen; specifically, according to the color temperature correction parameters, the proportional-integral-derivative control algorithm is used to precisely control the working state of the color temperature adjustment unit to generate region color temperature control signals.

[0072] For example, when it is necessary to increase the color temperature of a certain region, the proportional-integral-derivative control algorithm will adjust the working voltage of the color temperature adjustment unit to increase the color temperature of that region; conversely, it will decrease the color temperature.

[0073] The region brightness control signals and region color temperature control signals are respectively weighted and averaged to generate full-screen brightness control signals and full-screen color temperature control signals.

[0074] The brightness control signals and color temperature control signals of each region are integrated through weighted average processing; specifically, the region brightness control signals and region color temperature control signals are weighted and averaged according to preset weights to generate full-screen brightness control signals and full-screen color temperature control signals, so as to uniformly adjust the overall brightness and color temperature of the display screen.

[0075] For example, when the brightness control signals of most regions are high, the full-screen brightness control signal will also be correspondingly high; if the color temperature control signals of some regions are low, the full-screen color temperature control signal will be adjusted on average.

[0076] Among them, the steps of analyzing the brightness parameter and the color temperature parameter through the Kalman filtering algorithm to obtain the target brightness adjustment value and the target color temperature adjustment value, and performing a partition mapping process on the target brightness adjustment value and the target color temperature adjustment value by using a preset linear regression model to obtain the brightness correction parameter and the color temperature correction parameter for each display partition include: performing a time series analysis on the brightness parameter through the Kalman filtering algorithm to obtain the brightness trend prediction value and the brightness residual, performing a moving average filtering process on the brightness trend prediction value to obtain the brightness reference value, and performing a fast Fourier transform on the brightness residual to obtain the brightness frequency domain characteristic parameter.

[0077] The Kalman filtering algorithm is used to monitor the change of the brightness parameter in real time, and the brightness trend prediction value and the brightness residual are extracted; specifically, by analyzing the time series data of the brightness parameter, the brightness change trend in the future period of time is predicted, and the brightness residual is calculated. The short-term fluctuation is eliminated through the moving average filtering process to obtain a stable brightness reference value, and the fast Fourier transform is performed on the brightness residual to extract the brightness frequency domain characteristic parameter and analyze the frequency characteristics of the brightness change.

[0078] For example, when the brightness of the display screen changes frequently and there are periodic fluctuations, the Kalman filtering algorithm can accurately extract the brightness trend prediction value, and identify the periodic characteristics of the brightness change through the fast Fourier transform, generating the brightness reference value and the frequency domain characteristic parameter.

[0079] Based on the brightness reference value and the brightness frequency domain characteristic parameter, the piecewise regression calculation is performed by using the polynomial fitting method of the least squares method to obtain the initial brightness adjustment value and the brightness offset correction value, and the initial brightness adjustment value and the brightness offset correction value are weighted and synthesized to obtain the target brightness adjustment value.

[0080] The piecewise regression calculation is performed on the brightness reference value and the brightness frequency domain characteristic parameter by using the polynomial fitting method of the least squares method; specifically, according to the brightness reference value and the brightness frequency domain characteristic parameter, the polynomial fitting is applied to the brightness data by using the least squares method to obtain the initial brightness adjustment value and the brightness offset correction value, and the two are weighted and synthesized to obtain the final target brightness adjustment value to achieve the precise control of the brightness of the display screen.

[0081] For example, when the brightness reference value of the display screen is low and the frequency domain characteristic parameter is high, the polynomial fitting by using the least squares method can effectively improve the accuracy of the brightness adjustment and generate an accurate target brightness adjustment value.

[0082] The Kalman filtering algorithm is used to recursively analyze the color temperature parameter to obtain the color temperature trend prediction value and the color temperature dynamic change parameter, perform a wavelet transform analysis on the color temperature trend prediction value to obtain the multi-resolution color temperature detail parameter, and calculate the significance weight of the color temperature dynamic change parameter through the entropy weight method to generate the color temperature change significance parameter.

[0083] Recursively analyze the color temperature parameters through the Kalman filter algorithm; specifically, use the Kalman filter algorithm to analyze the time series data of the color temperature parameters, extract the color temperature trend prediction value and the color temperature dynamic change parameters; apply wavelet transform to the color temperature trend prediction value for multi-resolution analysis, and extract the color temperature detail parameters at different scales; calculate the significance weight of the color temperature dynamic change parameters through the entropy weight method to generate the color temperature change significance parameters for further adjusting the color temperature.

[0084] For example, when there are obvious multi-scale changes in the color temperature parameters, the Kalman filter algorithm and wavelet transform can accurately extract the detail features of the color temperature, and use the entropy weight method to calculate the significance weight to improve the accuracy of color temperature adjustment.

[0085] Weight the multi-resolution color temperature detail parameters and the color temperature change significance parameters based on the locally weighted regression method to generate the target color temperature adjustment value.

[0086] Weight the multi-resolution color temperature detail parameters and the color temperature change significance parameters through the locally weighted regression method; specifically, input the multi-resolution color temperature detail parameters and the color temperature change significance parameters into the locally weighted regression model, perform weighted processing on different parameters, and generate the target color temperature adjustment value to achieve precise control of the color temperature.

[0087] For example, when the color temperature detail parameters are complex and change significantly, the locally weighted regression method can effectively weight different parameters to generate an accurate target color temperature adjustment value.

[0088] Through the weighted linear regression calculation method of regional partitioning, perform per-partition fitting processing on the target brightness adjustment value to obtain the brightness correction parameters for each display partition; perform per-partition refinement processing on the target color temperature adjustment value based on the regression model of the support vector machine to generate the color temperature correction parameters for each display partition.

[0089] Perform per-partition fitting and refinement processing on the target brightness adjustment value and the target color temperature adjustment value through a preset linear regression model; specifically, first input the target brightness adjustment value and the target color temperature adjustment value into the linear regression model, and according to the characteristics of each display partition, apply the weighted linear regression calculation method for fitting processing to obtain the brightness correction parameters for each display partition; at the same time, perform per-partition refinement processing on the target color temperature adjustment value based on the regression model of the support vector machine to generate the color temperature correction parameters for each display partition.

[0090] For example, when the brightness of some partitions of the display screen is high while that of other partitions is low, the linear regression model and the support vector machine regression model can effectively adjust the brightness and color temperature of each partition to make the overall display effect more uniform.

[0091] In step S300, the full-screen brightness control signal and the full-screen color temperature control signal are resampled using the bilinear interpolation algorithm to adjust the initial pixel brightness distribution of each display partition, and the adjusted partition brightness distribution information is obtained.

[0092] The full-screen brightness control signal and the full-screen color temperature control signal are resampled by the bilinear interpolation algorithm; specifically, the full-screen brightness control signal and the full-screen color temperature control signal are input into the bilinear interpolation algorithm, and resampling processing is performed according to the initial brightness distribution of each display partition to adjust the pixel brightness of each partition, and the adjusted partition brightness distribution information is generated.

[0093] For example, when the full-screen brightness control signal is relatively consistent but the initial brightness distribution of each partition is uneven, the bilinear interpolation algorithm can resample the brightness signal to ensure the uniformity of the brightness distribution of each partition.

[0094] The adjusted partition brightness distribution information and the display content distribution information are cross-analyzed by the cosine similarity calculation method to obtain pixel feature parameters; based on the bilateral filtering algorithm, the pixel feature parameters are refined to obtain the pixel brightness control signal and the pixel color temperature control signal of each pixel.

[0095] The partition brightness distribution information and the display content distribution information are cross-analyzed by the cosine similarity calculation method; specifically, the adjusted partition brightness distribution information and the display content distribution information are input into the cosine similarity calculation model, the similarity between the two is calculated to obtain pixel feature parameters; based on the bilateral filtering algorithm, the pixel feature parameters are refined to generate the pixel brightness control signal and the pixel color temperature control signal of each pixel.

[0096] For example, when the display content in a certain area is mainly a dark image and the brightness is low, the cosine similarity calculation method can accurately analyze the characteristics of this area, and the pixel brightness and color temperature control signals are refined through the bilateral filtering algorithm to improve the display effect.

[0097] The homography matrix transformation algorithm is applied to fuse the pixel brightness control signal and the pixel color temperature control signal to obtain the pixel drive signal.

[0098] The pixel brightness control signal and the pixel color temperature control signal are fused by the homography matrix transformation algorithm; specifically, the pixel brightness control signal and the pixel color temperature control signal are input into the homography matrix transformation model, and the two are fused through matrix transformation to generate a comprehensive pixel drive signal to achieve independent and precise control of each pixel.

[0099] For example, when it is necessary to adjust the brightness and color temperature of a certain area simultaneously, the homography matrix transformation algorithm can fuse the control signals of the two to generate a unified pixel driving signal, ensuring the consistency of the display effect.

[0100] In step S400, the pixel driving signal is partitioned and mapped through the Voronoi diagram generation algorithm to generate a partition driving signal, and each partition of the display screen is independently driven by the partition driving signal to obtain a partition display output.

[0101] The pixel driving signal is partitioned and mapped through the Voronoi diagram generation algorithm; specifically, a Voronoi diagram is generated according to the pixel driving signal, the display screen is divided into multiple independent partitions, and a corresponding partition driving signal is generated for each partition; each partition is independently driven by the partition driving signal to obtain a partition display output.

[0102] For example, when the display content is complex and contains multiple different areas, the Voronoi diagram generation algorithm can effectively divide the screen into multiple areas, and each area generates an independent partition driving signal according to the pixel driving signal, ensuring the consistency of the display effect of each area.

[0103] The support vector machine is used to classify the partition display output and the display content distribution information to obtain the display priority of each area, and the entropy weight method is used to calculate the weight of the display priority and the user interaction data to identify the interaction priority area; among them, the user interaction data includes any one of the following: touch interaction data, gesture interaction data, voice input data.

[0104] The support vector machine is used to classify the partition display output and the display content distribution information; specifically, the partition display output and the display content distribution information are input into the support vector machine model, each area is classified to obtain the display priority of each area; the entropy weight method is used to calculate the weight of the display priority and the user interaction data to determine the interaction priority area; the user interaction data can include touch interaction data, gesture interaction data, and voice input data.

[0105] For example, when the user frequently touches and interacts with a certain area, the support vector machine model can identify this area as a high-priority area and calculate its interaction weight through the entropy weight method to ensure the best display effect of this area.

[0106] The linear interpolation method is used to preferentially adjust the display parameters of the interaction priority area to obtain an enhanced interactive partition display output.

[0107] The display parameters of the interactive priority area are preferentially adjusted by the linear interpolation method; specifically, the linear interpolation algorithm is used to precisely adjust the brightness and color temperature parameters of the high-priority area to ensure that the display effect of this area reaches the best state, and an enhanced interactive partition display output is generated.

[0108] For example, when the user performs a gesture interaction in a certain area, the display parameters of this area are preferentially adjusted by the linear interpolation method to increase its brightness and color temperature, making the interaction experience smoother and more comfortable.

[0109] The partition display output and the enhanced interactive partition display output are subjected to weighted linear fusion processing to generate a pre-display interface.

[0110] The partition display output and the enhanced interactive partition display output are comprehensively processed through weighted linear fusion processing; specifically, each partition display output and the enhanced interactive partition display output are weighted and fused according to preset weights to generate a pre-display interface to optimize the overall display effect of the display screen.

[0111] For example, when the display effects of multiple partitions are different, weighted linear fusion processing can synthesize the display characteristics of each area to generate a pre-display interface with higher consistency.

[0112] In step S500, a convolutional neural network is used to extract features from the partition display output and the pre-display interface to obtain interface feature parameters and partition display output characteristic data. By using linear discriminant analysis to fuse the interface feature parameters and the partition display output characteristic data, an optimization parameter group is generated.

[0113] Feature extraction is performed on the partition display output and the pre-display interface through a convolutional neural network; specifically, the partition display output and the pre-display interface are input into the convolutional neural network to extract the interface feature parameters and the partition display output characteristic data; then, linear discriminant analysis is used to fuse the extracted features to generate an optimization parameter group to further optimize the control effect of the display screen.

[0114] For example, when there are problems with uneven brightness and color temperature in the pre-display interface, the convolutional neural network can extract these features and generate an optimization parameter group through linear discriminant analysis to improve the display effect.

[0115] The optimization parameter group is analyzed to generate a screen refresh rate adjustment parameter, a touch response adjustment parameter, and a display content layout parameter.

[0116] Specific control parameters are generated by analyzing the optimization parameter group; specifically, the data in the optimization parameter group is analyzed to generate a screen refresh rate adjustment parameter, a touch response adjustment parameter, and a display content layout parameter to optimize the various performances of the display screen.

[0117] For example, by parsing the screen refresh rate adjustment data in the optimization parameter group, specific refresh rate adjustment parameters can be generated to ensure the smoothness of the display screen in different scenarios.

[0118] According to the screen refresh rate adjustment parameters, apply the servo control algorithm to dynamically adjust the display refresh rate.

[0119] Dynamically adjust the screen refresh rate through the servo control algorithm; specifically, according to the screen refresh rate adjustment parameters, apply the servo control algorithm to adjust the refresh rate of the display screen in real time to ensure the best display effect in different usage scenarios.

[0120] For example, when the user is watching a video, the servo control algorithm can dynamically increase the screen refresh rate to provide a smoother visual experience.

[0121] According to the touch response adjustment parameters, apply the generalized predictive control algorithm to adjust the touch module.

[0122] Adjust the touch module through the generalized predictive control algorithm; specifically, according to the touch response adjustment parameters, apply the generalized predictive control algorithm to optimize the response speed and sensitivity of the touch module to enhance the user's interaction experience.

[0123] For example, when the user makes a quick sliding operation on the screen, the generalized predictive control algorithm can improve the response speed of the touch module to make the operation more sensitive and smooth.

[0124] According to the display content layout parameters, optimize the layout and arrangement of the display screen content of the smart watch.

[0125] Adjust the layout and arrangement of the display screen content by optimizing the display content layout parameters; specifically, according to the display content layout parameters, optimize the content distribution of each display area to improve the readability and visual beauty of the information.

[0126] For example, when multiple applications are displayed on the display screen at the same time, adjusting the content layout parameters can make the layout of each application more reasonable and enhance the user experience.

[0127] In this embodiment, the ambient light intensity and color temperature information are collected by a photodiode sensor module, and denoised by combining with a Gaussian filtering algorithm to obtain ambient light correction parameters. Then, the light emission intensity of the display screen and the RGB color output information are input into a multi-layer perceptron model to generate the brightness parameter and color temperature parameter of the display screen. In addition, the K-means clustering algorithm and the gray gradient watershed segmentation algorithm are used to divide and refine the display content to obtain the brightness distribution information of each display area. Then, through the dynamic time warping algorithm and the principal component analysis method, the brightness and color temperature states of the screen are dynamically detected, and the main features are extracted to obtain the optimized display content distribution information. The Kalman filtering algorithm analyzes the brightness parameter and color temperature parameter to generate the target brightness and color temperature adjustment values, and uses the linear regression model and the support vector machine regression model for zoning processing to obtain the brightness and color temperature correction parameters of each zone. Through the pulse width modulation technology and the proportional integral derivative control algorithm, the light-emitting unit and the color temperature adjustment unit of the backlight module are adjusted region by region to generate the full-screen brightness and color temperature control signals, ensuring uniform distribution of the brightness and color temperature of the display screen. In addition, through the bilinear interpolation algorithm and the cosine similarity calculation method, the adjusted brightness and color temperature distribution information is processed to generate pixel drive signals, and the brightness and color temperature control signals are fused using the homography matrix transformation algorithm. The Voronoi diagram generation algorithm and the support vector machine classification method optimize the zoned drive signals, and the display priority is calculated based on the entropy weight method to generate a pre-display interface. Finally, using convolutional neural networks and linear discriminant analysis, the interface features are extracted and an optimized parameter set is generated. Through the servo control algorithm and the generalized predictive control algorithm, the screen refresh rate and touch response are dynamically adjusted to optimize the display content layout of the display screen, improving the overall display effect and user experience of the smartwatch.

[0128] Embodiment 3:

[0129] As Figure 2 shown, the present application also provides a display screen control device 10 for a smartwatch, including a detection module 11, an adjustment module 12, an adjustment module 13, a drive module 14, and a control module 15.

[0130] The detection module 11 is mainly used to detect the current state of the display screen of the smartwatch in real time to obtain the brightness parameter, color temperature parameter, and display content distribution information of the display screen.

[0131] The adjustment module 12 is mainly used to adjust the backlight module of the display screen based on the brightness parameter and color temperature parameter to obtain the full-screen brightness control signal and the full-screen color temperature control signal.

[0132] The adjustment module 13 is mainly used to input the full-screen brightness control signal and the full-screen color temperature control signal into a preset display adjustment module 12, dynamically adjust the pixel partitions of the display screen to obtain the partition brightness distribution information, and use the partition brightness distribution information and the display content distribution information to refine the adjustment of each pixel of the display screen to obtain the pixel drive signal.

[0133] The driving module 14 is mainly used to perform partition driving on the display screen based on the pixel drive signal to obtain the partition display output, and preferentially adjust the interaction area of the display screen according to the display content distribution information and the user interaction data to obtain the pre-display interface.

[0134] The control module 15 is mainly used to analyze and process the partition display output and the pre-display interface, generate an optimization parameter group, and control the smart watch based on the optimization parameter group.

[0135] In this embodiment, the detection module 11 performs real-time detection on the current state of the display screen to obtain the brightness parameter, the color temperature parameter, and the display content distribution information, so as to ensure that the state of the display screen accurately reflects the current usage environment. The adjustment module 12 adjusts the backlight module based on the brightness parameter and the color temperature parameter to generate the full-screen brightness control signal and the full-screen color temperature control signal, so as to ensure that the display screen can provide the best brightness and color temperature in different environments. The adjustment module 13 inputs these signals into the preset display adjustment module 12, dynamically adjusts the pixel partitions, and performs refined adjustment on each pixel according to the partition brightness distribution information and the display content distribution information to generate the pixel drive signal. The driving module 14 performs partition driving on the display screen based on the pixel drive signal to obtain the partition display output, and preferentially adjusts the interaction area of the display screen according to the display content distribution information and the user interaction data to generate the pre-display interface, improving the user experience. The control module 15 analyzes and processes the partition display output and the pre-display interface, generates an optimization parameter group, and performs fine control on the smart watch based on the optimization parameter group to ensure the optimization of the display effect and the user experience.

[0136] It should be noted that those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described device and each module can refer to the corresponding processes in the embodiment of the display screen control method of the smart watch described above, and will not be repeated here.

[0137] Embodiment 4:

[0138] As Figure 3 shown, the present application also provides an electronic device 20, including a memory 21 and a processor 22. The memory 21 stores a computer program that can run on the processor 22, and when the processor 22 executes the computer program, it implements the display screen control method of the smart watch in Embodiment 1.

[0139] In this embodiment, through the memory 21 and the processor 22 of the electronic device 20, a computer program stored in the memory 21 is run to execute the display screen control method of the smart watch. The processor 22 detects the current state of the display screen in real time through the computer program, obtains the brightness parameter, the color temperature parameter and the display content distribution information, and adjusts the backlight module of the display screen based on these parameters to generate a full-screen brightness control signal and a full-screen color temperature control signal. The processor 22 inputs the control signals into the preset display adjustment module 12 to dynamically adjust the pixel partitions of the display screen, generating a partition brightness distribution information and a pixel driving signal. Through the partition driving of the pixel driving signal, the processor 22 realizes the partition display output, and preferentially adjusts the interaction area according to the display content distribution information and the user interaction data to generate a pre-display interface. Finally, the processor 22 analyzes and processes the partition display output and the pre-display interface to generate an optimized parameter set, and improves the display effect and the user experience through the fine control of the smart watch.

[0140] Embodiment 5:

[0141] The present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, the processor is caused to execute the display screen control method of the smart watch as in Embodiment 1.

[0142] In this embodiment, through the computer program stored in the computer-readable storage medium, when the processor runs the computer program, it executes the display screen control method of the smart watch. Specifically, the processor detects the current state of the display screen in real time through the computer program, obtains the brightness parameter, the color temperature parameter and the display content distribution information, adjusts the backlight module of the display screen based on these parameters to generate a full-screen brightness control signal and a full-screen color temperature control signal. The processor inputs the control signals into the display adjustment module to dynamically adjust the pixel partitions of the display screen, obtaining a partition brightness distribution information and a pixel driving signal. The processor performs partition driving on the display screen based on the pixel driving signal to generate a partition display output, and preferentially adjusts the interaction area according to the display content distribution information and the user interaction data to generate a pre-display interface. Finally, the processor analyzes and processes the partition display output and the pre-display interface to generate an optimized parameter set, and ensures the improvement of the display effect and the user experience through the optimized control of the smart watch.

[0143] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than limiting it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for controlling a display screen of a smart watch, characterized in that: include: Perform real-time detection on the current state of the display screen of the smart watch to obtain the brightness parameters, color temperature parameters and display content distribution information of the display screen; Based on the brightness parameter and the color temperature parameter, a backlight module of the display screen is adjusted to obtain a full-screen brightness control signal and a full-screen color temperature control signal; The full-screen brightness control signal and the full-screen color temperature control signal are resampled by using a bilinear interpolation algorithm, and the initial brightness distribution of pixels in each display partition is adjusted to obtain adjusted partition brightness distribution information; the adjusted partition brightness distribution information and the display content distribution information are cross-analyzed by a cosine similarity calculation method to obtain pixel feature parameters; the pixel feature parameters are refined based on a bilateral filtering algorithm to obtain a pixel brightness control signal and a pixel color temperature control signal for each pixel; the pixel brightness control signal and the pixel color temperature control signal are fused by using a homography matrix transformation algorithm to obtain a pixel drive signal; The display screen is driven by partitions based on the pixel driving signal to obtain a partition display output, and the interactive area of ​​the display screen is preferentially adjusted according to the display content distribution information and the user interaction data to obtain a pre-display interface; The partition display output and the pre-display interface are analyzed and processed to generate an optimization parameter group, and the smart watch is controlled based on the optimization parameter group.

2. The display screen control method of a smart watch according to claim 1, characterized in that: The step of detecting the current state of the display screen of the smart watch in real time to obtain the brightness parameters, color temperature parameters and display content distribution information of the display screen includes: The photodiode sensor module is used to collect ambient light intensity and color temperature information around the display screen to obtain ambient brightness parameters and ambient color temperature parameters, and a Gaussian filter algorithm is used to perform denoising on the ambient brightness parameters and the ambient color temperature parameters to obtain ambient light correction parameters; Inputting the ambient light correction parameter and the luminous intensity and RGB color output information of the display screen into a preset multi-layer perceptron model to obtain the brightness parameter and color temperature parameter of the display screen; Dividing the display content of the display screen into regions to obtain initial display content distribution information and initial partition characteristic parameters; Using a grayscale gradient-based watershed segmentation algorithm to partition and refine the initial display content distribution information to obtain refined brightness distribution information, and fitting the refined brightness distribution information with the initial partition feature parameters to obtain brightness distribution information; Screen state characteristic parameters and regional display characteristics are generated according to the brightness distribution information, and main characteristics of the screen state characteristic parameters and the regional display characteristics are extracted using a principal component analysis method to obtain display content distribution information.

3. The display screen control method of a smart watch according to claim 1, characterized in that: The step of adjusting the backlight module of the display screen based on the brightness parameter and the color temperature parameter to obtain a full-screen brightness control signal and a full-screen color temperature control signal comprises: The brightness parameter and the color temperature parameter are parsed by a Kalman filter algorithm to obtain a target brightness adjustment value and a target color temperature adjustment value, and a preset linear regression model is used to perform partition mapping processing on the target brightness adjustment value and the target color temperature adjustment value to obtain a brightness correction parameter and a color temperature correction parameter of each display partition; According to the brightness correction parameter, the light-emitting unit of the backlight module of the display screen is adjusted region by region through pulse width modulation technology to obtain a regional brightness control signal; According to the color temperature correction parameter, a proportional-integral-differential control algorithm is applied to fine-tune the color temperature adjustment unit of the backlight module of the display screen to obtain a regional color temperature control signal; The regional brightness control signal and the regional color temperature control signal are respectively subjected to weighted average processing to generate a full-screen brightness control signal and a full-screen color temperature control signal.

4. The display screen control method of a smart watch according to claim 3, characterized in that: The step of parsing the brightness parameter and the color temperature parameter by using a Kalman filter algorithm to obtain a target brightness adjustment value and a target color temperature adjustment value, and performing partition mapping processing on the target brightness adjustment value and the target color temperature adjustment value by using a preset linear regression model to obtain a brightness correction parameter and a color temperature correction parameter of each display partition includes: Using the Kalman filter algorithm to perform time series analysis on the brightness parameter to obtain a brightness trend prediction value and a brightness residual, performing moving average filtering on the brightness trend prediction value to obtain a brightness reference value, and performing fast Fourier transform on the brightness residual to obtain a brightness frequency domain characteristic parameter; Based on the brightness reference value and the brightness frequency domain characteristic parameter, a piecewise regression calculation is performed using a least squares polynomial fitting method to obtain an initial brightness adjustment value and a brightness offset correction value, and the initial brightness adjustment value and the brightness offset correction value are weighted and synthesized to obtain a target brightness adjustment value; The color temperature parameters are recursively analyzed by using a Kalman filter algorithm to obtain a color temperature trend prediction value and a color temperature dynamic change parameter, the color temperature trend prediction value is subjected to a wavelet transform analysis to obtain a multi-resolution color temperature detail parameter, and the significance weight of the color temperature dynamic change parameter is calculated by an entropy weight method to generate a color temperature change significance parameter; weighting the multi-resolution color temperature detail parameter and the color temperature change significance parameter based on a local weighted regression method to generate a target color temperature adjustment value; By using a weighted linear regression calculation method for regional partitions, the target brightness adjustment value is subjected to a partition-by-partition fitting process to obtain a brightness correction parameter for each display partition; The target color temperature adjustment value is refined partition by partition based on a regression model of a support vector machine to generate a color temperature correction parameter for each display partition.

5. The display screen control method of a smart watch according to claim 1, characterized in that: The step of driving the display screen by partitions based on the pixel driving signal to obtain a partition display output, and preferentially adjusting the interactive area of ​​the display screen according to the display content distribution information and the user interaction data to obtain a pre-display interface includes: Performing partition mapping on the pixel drive signal by using a Voronoi diagram generation algorithm to generate a partition drive signal, and using the partition drive signal to independently drive each partition of the display screen to obtain a partition display output; A support vector machine is used to classify the partition display output and the display content distribution information to obtain the display priority of each area, and the display priority and user interaction data are weighted by an entropy weight method to identify the interaction priority area; wherein the user interaction data includes any one of the following: touch interaction data, gesture interaction data, and voice input data; Using a linear interpolation method to preferentially adjust the display parameters of the interactive priority area to obtain an enhanced interactive partition display output; The partition display output and the enhanced interactive partition display output are subjected to weighted linear fusion processing to generate a preview display interface.

6. The display screen control method of a smart watch according to claim 1, characterized in that: The step of analyzing and processing the partition display output and the pre-display interface to generate an optimization parameter group, and controlling the smart watch based on the optimization parameter group includes: Using a convolutional neural network to extract features from the partition display output and the pre-display interface to obtain interface feature parameters and partition display output characteristic data, and using linear discriminant analysis to fuse the interface feature parameters and the partition display output characteristic data to generate an optimization parameter group; Parsing the optimization parameter group to generate screen refresh rate adjustment parameters, touch response adjustment parameters, and display content arrangement parameters; According to the screen refresh rate adjustment parameter, a servo control algorithm is applied to dynamically adjust the display refresh rate; According to the touch response adjustment parameter, a generalized predictive control algorithm is applied to adjust the touch module; According to the display content arrangement parameters, the layout and arrangement of the display screen content of the smart watch are optimized.

7. A display screen control device for a smart watch, characterized in that: include: A detection module is used to detect the current state of the display screen of the smart watch in real time to obtain the brightness parameters, color temperature parameters and display content distribution information of the display screen; An adjustment module, used to adjust the backlight module of the display screen based on the brightness parameter and the color temperature parameter to obtain a full-screen brightness control signal and a full-screen color temperature control signal; The adjustment module is used to resample the full-screen brightness control signal and the full-screen color temperature control signal by using a bilinear interpolation algorithm, adjust the initial brightness distribution of pixels in each display partition, and obtain adjusted partition brightness distribution information; cross-analyze the adjusted partition brightness distribution information and the display content distribution information by using a cosine similarity calculation method to obtain pixel feature parameters; refine the pixel feature parameters based on a bilateral filtering algorithm to obtain a pixel brightness control signal and a pixel color temperature control signal for each pixel; and fuse the pixel brightness control signal and the pixel color temperature control signal by using a homography matrix transformation algorithm to obtain a pixel drive signal; A driving module, configured to drive the display screen in partitions based on the pixel driving signal to obtain a partition display output, and to preferentially adjust the interactive area of ​​the display screen according to the display content distribution information and the user interaction data to obtain a pre-display interface; The control module is used to analyze and process the partition display output and the pre-display interface, generate an optimization parameter group, and control the smart watch based on the optimization parameter group.

8. An electronic device, characterized in that: The invention comprises a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, the display screen control method of the smart watch according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the processor executes the display screen control method of a smart watch as claimed in any one of claims 1 to 6.

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