Display device color self-adjustment system and method for matchless color analyzers

Abstract

The application discloses a display device color self-adjusting system and method for a matching-free color analyzer, a measurement data picture on a panel of the color analyzer is acquired through a camera of an intelligent display device, and the intelligent display device parses measurement values from the panel picture through deep learning according to the picture; then, the recognized display parameter data is compared with standard color data, and the intelligent display device is controlled to modulate standard color data that does not meet the standard, and the production adjustment data is saved in the intelligent display device. The application is not affected by whether the color analyzer and the display device can be matched and connected, application scenarios are expanded, stability is improved, and research and development investment is saved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of display device, and particularly relates to a display device color self-adjusting system and method for a non-matching color analyzer. BACKGROUND

[0002] With the wide popularity of display devices, the color function requirements of display devices are also increasingly high. For example, current display devices basically have color temperature, gamma and other functions, and high-end display devices have delta E, brightness uniformity and other functions. Since the optical properties of each panel are not consistent, in order to meet the color function parameters of each display device in accordance with the corresponding specifications, each display device needs to be adjusted in the production link, and corresponding color adjustment data is generated and saved in the display device. Therefore, the color adjustment scheme needs to consider and evaluate the time required for the adjustment process, the stability of the adjustment process, and the human cost invested in the research and development stage. At present, the common adjustment method is to use additional software on a PC, the PC is interconnected with the display device through UART and the like to issue control instructions and complete the transmission of color data, the PC receives the data of the optical device (color analyzer) such as CA210 through the usb line to obtain the color characteristics of the display panel, the color adjustment program of the PC generates adjustment data, and then the adjustment data is transmitted to the display device to be adjusted through the UART line for saving. When the color adjustment mode is multiple, the PC transmits multiple control instructions and adjustment data through the UART, and the low transmission rate of the UART causes the stability to be reduced and the time for adjusting and saving data to be too long, which will increase the manufacturing cost of a single display device.

[0003] The PC in the existing scheme usually uses the OS of windows, and the optical device such as CA310 has the driver package of the manufacturer of windows, and the PC can obtain the data of the CA310 through the usb line based on the sdk development application of the manufacturer of windows.

[0004] Unlike the PC in the existing scheme, the OS of the current smart display is Android or Linux, and the CA310 manufacturer does not provide the driver and sdk development package on Linux / Android, so the data of the CA310 cannot be obtained through the usb line. SUMMARY

[0005] The present application relates to the technical field of display device, and particularly relates to a display device color self-adjusting system and method for a non-matching color analyzer.

[0006] The technical scheme adopted by the present application is:

[0007] A color self-adjustment system for display devices without a matching color analyzer includes a color analyzer, a display device, and a screen data acquisition device electrically connected to the display device. The color analyzer's probe is aligned with the display screen of the display device. The color analyzer includes a color capture device and a color processing device. The color capture device senses and captures changes in brightness from low to high and across different color gamuts on the intelligent display device's screen, and transmits the detected data to the color processing device. The color processing device accurately determines the display parameters of the display device based on the color data from the color capture device and presents the display parameters visually on the analyzer's display panel. The screen data acquisition device captures images of the display screen on the color analyzer's display panel and displays the data. The displayed image is transmitted to the display device in real time. The display device is equipped with a color self-adjustment program, which includes a color verification module, a digital classification module, and a color adjustment module. The color verification module controls the intelligent display device to switch between different colors on the screen at a certain frequency and sequence, and is used to wait for the color capture device to collect colors. The digital classification module is an optimized model that has been trained based on a deep learning network structure. The digital classification module is used to classify and recognize the numbers on the color analyzer panel using the model and transmit the recognized data to the color adjustment module. The color adjustment module is used to compare the data from the digital classification module with the built-in standard color data and control the display device to adjust any color data that does not meet the standard to the standard.

[0008] Furthermore, display parameters include color temperature, hue, brightness, contrast, flicker level, uniformity, and Gamma parameter.

[0009] Furthermore, the display device's color self-adjustment program is embedded within the operating system.

[0010] Furthermore, display devices include IPS panels, TN panels, and VA panels.

[0011] Furthermore, the display device is equipped with an operating system running Windows / Linux / Android / iOS and has computing power.

[0012] Furthermore, the screen data acquisition device includes an adapter-type external camera, an image-collecting sensor, or a built-in camera of the display device.

[0013] Furthermore, deep learning network structures include DNN and CNN network structures.

[0014] A color self-adjustment system and method for a display device without a matching color analyzer, comprising the following steps:

[0015] Step 1: The calibration test screen is displayed on the device;

[0016] Step 2: The color analyzer collects data from the screen of the display device in real time, and displays the collected display parameters in a visual form on the display screen of the analyzer in real time.

[0017] Step 3: The screen data acquisition device captures the display panel image of the color analyzer and transmits it to the display device in real time;

[0018] Step 4: The color self-adjustment program of the display device uses a deep learning network to perform ORC classification and recognition on the display panel image to obtain the recognized display parameter data;

[0019] Step 5: The color self-adjustment program of the display device compares the identified display parameter data with the standard color data, and controls the intelligent display device to modulate the color data that does not meet the standard, and saves the adjusted data produced on the intelligent display device itself.

[0020] Furthermore, the display device grants the color self-adjustment program permission to call camera functions and control the system's color and brightness systems.

[0021] This invention employs the above technical solution to address situations where color data cannot be obtained from a color analyzer (CA310) via USB cable. Instead, it uses a camera on a smart display device to capture measurement data from the CA310's panel. The display device then uses deep learning to parse the measurement values ​​from the panel image. The identified display parameter data is compared with standard color data, and the smart display device modulates any non-standard color data to a standard, storing the adjusted data locally. This invention completes the logic for screen switching control, optical data acquisition, and the generation and storage of adjustment data all within the smart display device. By using a camera to collect panel data and leveraging the deep learning program on the display device to extract color measurement data from the panel image, this invention is unaffected by compatibility issues between the color analyzer and the display device, expanding application scenarios, improving stability, and saving on R&D investment. Attached Figure Description

[0022] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments;

[0023] Figure 1 This is a schematic diagram of the color self-adjustment system for a display device without a matching color analyzer, as per the present invention.

[0024] Figure 2 This is a flowchart illustrating the color self-adjustment method for a display device using a color analyzer without a matching color analyzer, as per the present invention. Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0026] Currently, many smart displays possess strong computing power and are equipped with operating systems. This invention utilizes a camera and artificial intelligence to acquire data from optical devices, achieving a general framework for smart displays to self-adjust color data using only optical instruments. This reduces investment in adjustment time, stability, and adjustment schemes.

[0027] like Figure 1 As shown in Figure 2, this invention discloses a color self-adjustment system for display devices without a matching color analyzer, including a color analyzer, a display device, and a screen data acquisition device electrically connected to the display device. The probe of the color analyzer is aligned with the display screen of the display device. The color analyzer includes a color capture device and a color processing device. The color capture device senses and captures changes in brightness from low to high and different color gamuts of the smart display device screen, and transmits the detected data to the color processing device. The color processing device accurately determines the display parameter data of the display device based on the color data from the color capture device, and presents the display parameter data in a visual manner on the display panel of the analyzer. The screen data acquisition device captures images of the display on the display panel of the color analyzer. The system transmits the displayed image to the display device in real time. The display device is equipped with a color self-adjustment program, which includes a color verification module, a digital classification module, and a color adjustment module. The color verification module controls the intelligent display device to switch between different colors on the screen at a certain frequency and sequence, and waits for the color capture device to collect colors. The digital classification module is an optimized model that has been trained based on a deep learning network structure. The digital classification module is used to classify and recognize the numbers on the color analyzer panel using the model and transmit the recognized data to the color adjustment module. The color adjustment module is used to compare the data from the digital classification module with the built-in standard color data and control the display device to adjust any color data that does not meet the standard to the standard.

[0028] Furthermore, display parameters include color temperature, hue, brightness, contrast, flicker level, uniformity, and Gamma parameter.

[0029] Furthermore, the display device's color self-adjustment program is embedded within the operating system.

[0030] Furthermore, display devices include IPS panels, TN panels, and VA panels.

[0031] Furthermore, the display device is equipped with an operating system running Windows / Linux / Android / iOS and has computing power.

[0032] Furthermore, the screen data acquisition device includes an adapter-type external camera, an image-collecting sensor, or a built-in camera of the display device.

[0033] Furthermore, deep learning network structures include DNN and CNN network structures.

[0034] A color self-adjustment system and method for a display device without a matching color analyzer, comprising the following steps:

[0035] Step 1: The calibration test screen is displayed on the device;

[0036] Step 2: The color analyzer collects data from the screen of the display device in real time, and displays the collected display parameters in a visual form on the display screen of the analyzer in real time.

[0037] Step 3: The screen data acquisition device captures the display panel image of the color analyzer and transmits it to the display device in real time;

[0038] Step 4: The color self-adjustment program of the display device uses a deep learning network to perform ORC classification and recognition on the display panel image to obtain the recognized display parameter data;

[0039] Step 5: The color self-adjustment program of the display device compares the identified display parameter data with the standard color data, and controls the intelligent display device to modulate the color data that does not meet the standard, and saves the adjusted data produced on the intelligent display device itself.

[0040] Furthermore, the display device grants the color self-adjustment program permission to call camera functions and control the system's color and brightness systems.

[0041] This invention employs the above technical solution to address situations where color acquisition data cannot be obtained from a color analyzer (CA310) via USB cable. Instead, it uses a camera on a smart display device to capture measurement data from the CA310 color analyzer panel. The display device then uses deep learning to parse the measurement values ​​from the panel image. The identified display parameter data is compared with standard color data, and the smart display device modulates any non-standard color data to the correct standard, storing the adjusted data on its own. This invention completes the logic for screen switching control, optical data acquisition, and the generation and storage of adjustment data all within the smart display device. By using a camera to acquire panel data and leveraging the deep learning program on the display device to extract color measurement data from the panel image, this invention is unaffected by compatibility issues between the color analyzer and the display device, expanding application scenarios, improving stability, optimizing the adjustment control process, shortening adjustment data storage time, and saving R&D investment and manufacturing costs.

[0042] Obviously, the described embodiments are only a part of the embodiments of this application, not all of them. Without conflict, the embodiments and features in the embodiments of this application can be combined with each other. The components of the embodiments of this application described and illustrated herein can generally be arranged and designed in various different configurations. Therefore, the detailed description of the embodiments of this application is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

Claims

1. A color self-adjustment system for display devices without a matching color analyzer, characterized in that: It includes a color analyzer, a display device, and a screen data acquisition device electrically connected to the display device; The probe of the color analyzer is aligned with the display screen of the display device. The color analyzer includes a color capture device and a color processing device. The color capture device senses and captures the changes in brightness from low to high and different color gamuts of the display screen, and transmits the detected data to the color processing device. The color processing device accurately measures the display parameters of the display device based on the color data from the color capture device, and presents the display parameters in a visual manner on the display panel of the color analyzer. The screen data acquisition device captures the display image on the display panel of the color analyzer and transmits the image to the display device in real time. The display device is equipped with a color self-adjustment program, which includes a color calibration module, a digit classification module, and a color adjustment module. The color calibration module controls the display device to switch between different colors on the screen at a certain frequency and sequence, and waits for the color capture device to acquire colors. The digit classification module is an optimized model that has been trained based on a deep learning network structure. The digit classification module is used to optimize the model to classify and recognize the digits on the color analyzer panel and transmit the recognized data to the color adjustment module. The color adjustment module is used to compare the data from the digital classification module with the built-in standard color data and control the display device to adjust any color data that does not meet the standard to the standard.

2. The color self-adjustment system for a display device without a matching color analyzer according to claim 1, characterized in that: Display parameters include color temperature, hue, brightness, contrast, flicker level, uniformity, and Gamma parameter.

3. The color self-adjustment system for a display device without a matching color analyzer according to claim 1, characterized in that: The display device's color self-adjustment program is embedded in the operating system.

4. The color self-adjustment system for a display device without a matching color analyzer according to claim 1, characterized in that: Display devices include IPS panels, TN panels, and VA panels.

5. The color self-adjustment system for a display device without a matching color analyzer according to claim 1, characterized in that: The display device is equipped with an operating system that runs Windows / Linux / Android / iOS and has computing power.

6. The color self-adjustment system for a display device without a matching color analyzer according to claim 1, characterized in that: Screen data acquisition devices include adapter-type external cameras, sensors that can collect images, or built-in cameras in display devices.

7. The color self-adjustment system for a display device without a matching color analyzer according to claim 1, characterized in that: Deep learning network structures include DNN and CNN network structures.

8. A color self-adjustment method for a display device without a matching color analyzer, applied to the color self-adjustment system for a display device without a matching color analyzer as described in any one of claims 1 to 7, characterized in that: The method includes the following steps: Step 1: The calibration test screen is displayed on the device; Step 2: The color analyzer collects data from the screen of the display device in real time, and displays the collected display parameters in a visual form on the display screen of the color analyzer in real time. Step 3: The screen data acquisition device captures the display panel image of the color analyzer and transmits it to the display device in real time; Step 4: The color self-adjustment program of the display device uses a deep learning network to classify and recognize the digital data of the display panel to obtain the recognized display parameter data. Step 5: The display device's color self-adjustment program compares the identified display parameter data with the standard color data, and controls the display device to modulate the color data that does not meet the standard, and saves the adjusted data produced on the display device itself.

9. The color self-adjustment method for a display device without a matching color analyzer according to claim 8, characterized in that: The display device is granted permissions to the color self-adjustment program to access camera functions and control the system's color and brightness.

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