Automatic focusing method and system based on TFT liquid crystal panel

Abstract

The invention discloses an automatic focusing method and system based on a TFT liquid crystal panel, and particularly relates to the technical field of TFT liquid crystal panels. By acquiring image data of a shooting scene, calculating an optimal focal length adjustment parameter and applying a control voltage to dynamically adjust the refractive index of a liquid crystal panel, focus adjustment of an optical system is realized, an adjusted image is acquired, image quality is compared by using a definition evaluation algorithm, if the definition does not reach a preset threshold value, voltage control is iteratively optimized, and the image quality is improved. And after the focus is determined, the system maintains the current voltage state, and the focusing process is automatically optimized in combination with a scene change detection mechanism. The problems of optical distortion, halo, aberration and the like caused by the uniformity and response characteristics of liquid crystal molecules in the optical adjustment process of an existing liquid crystal panel are solved; the automatic focusing method and the automatic focusing device are particularly suitable for high-resolution and large-aperture application scenes, and stability and adaptability of automatic focusing are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of TFT liquid crystal panels, and in particular to an automatic focusing method and system based on a TFT liquid crystal panel. Background Art

[0002] TFT liquid crystal panel-based autofocus is an autofocus method that uses thin-film transistor (TFT) liquid crystal technology to dynamically adjust the focal length of the optical system. The basic principle is to control the voltage of the liquid crystal panel and change the arrangement state of the liquid crystal molecules, thereby adjusting the refractive index or transmittance of the liquid crystal panel, affecting the propagation path of light, and realizing automatic adjustment of the focus position. Compared with the traditional mechanical focusing method, this technology does not require moving the lens, but relies on the electric field to quickly adjust the focal length of the optical system. It has the advantages of small size, no mechanical wear, and fast response speed. Therefore, it is widely used in smart phones, micro projectors, AR / VR equipment, and high-end optical instruments.

[0003] This autofocus technology is usually combined with an image clarity analysis algorithm to detect image clarity in real time through an imaging sensor (such as CMOS / CCD), and adjust the control voltage of the LCD panel according to changes in clarity to optimize the focal position. In the specific implementation process, the system will continuously collect the current image, calculate clarity indicators (such as gradient contrast, Laplace transform value), and iteratively optimize the control voltage until the image clarity is optimal. Compared with traditional mechanical focus, this method not only reduces power consumption and structural complexity, but also responds to focal changes faster in dynamic scenes and improves image quality. It is particularly suitable for application scenarios with high requirements for focusing speed and accuracy.

[0004] The prior art has the following deficiencies: The optical adjustment of the liquid crystal panel relies on an external electric field to control the arrangement direction of the liquid crystal molecules to change their refractive index or transmittance, thereby adjusting the focal position of the optical system. However, due to the uniformity error, response speed limitation and nonlinear characteristics of the liquid crystal material itself, the liquid crystal molecules may not be able to achieve completely consistent orientation under the action of the electric field, which will cause deviations in the optical performance of the local area. Specifically, this non-uniformity will cause the scattering and diffraction effects of light, causing additional bending or interference of the light passing through the liquid crystal panel, thereby reducing the image quality. In addition, since the response speed of the liquid crystal molecules is affected by the change of the electric field, its phase adjustment may have nonlinear deviations, resulting in unstable focal length adjustment or difficulty in precise control. These problems are particularly obvious in optical systems with high resolution or large aperture, manifested as imaging defects such as blurred edges of the picture, halo effect (halo) and aberration (aberration), which reduce the overall image quality, especially in low light environments or complex lighting conditions. The impact is more significant, thereby limiting the application effect of liquid crystal autofocus technology. Summary of the invention

[0005] The purpose of the present invention is to provide an automatic focusing method and system based on a TFT liquid crystal panel to solve the deficiencies in the background technology.

[0006] In order to achieve the above object, the present invention provides the following technical solution: an automatic focusing method based on a TFT liquid crystal panel, comprising the following steps: S1: acquiring image data of a current shooting scene, analyzing image clarity information through an imaging sensor, and calculating optimal focal length adjustment parameters according to the image clarity information; S2: applying a control voltage to the TFT liquid crystal panel to change the arrangement state of the liquid crystal molecules, thereby dynamically adjusting the refractive index of the liquid crystal panel and determining the change in the focus position of the optical system; S3: collecting the adjusted image, and comparing the image quality before and after the adjustment based on the clarity evaluation algorithm. If the image clarity does not reach the preset threshold, iteratively adjusting the control voltage until the optimal focus position is obtained; S4: After determining the optimal focus position, the current voltage state is maintained to maintain the stable focus of the optical system, and the focus process is automatically optimized according to the changes in the detection scene to ensure the stability of the focus state.

[0007] Preferably, S1 acquires image data through an imaging sensor and calculates image clarity information using a Laplace transform method to determine whether the current focal length needs to be adjusted, including calculating an image clarity evaluation value S through Laplace transform, which is expressed as: ; In the formula, is the Laplace transform, P is the number of rows of the image, and Q is the number of columns of the image.

[0008] Preferably, the control voltage applied by S2 is calculated based on the focus adjustment parameter, and the refractive index of the liquid crystal panel is The relationship expression with voltage V is: ;in: is the initial refractive index when there is no voltage, and β is the voltage response coefficient of the liquid crystal material, which determines the amplitude of the refractive index change.

[0009] Preferably, the focal length Determined by the refractive index n of the liquid crystal panel, the calculation formula is: ; Wherein, d is the equivalent optical thickness of the liquid crystal layer.

[0010] Preferably, S3 optimizes the focal length by iteratively adjusting the control voltage, and the calculation formula of the adjustment voltage V is: ; Where: γ is the adaptive step size, It represents the gradient of calculating image clarity as voltage changes.

[0011] Preferably, the current resolution is calculated The resolution of the previous frame Changes between: ; If ΔS>0, it means the image becomes clearer and the adjustment direction is correct; if ΔS<0, it means the image becomes blurred and the voltage direction or step size needs to be adjusted; set the preset clarity threshold , if satisfied ≥ , the focusing is completed, and the control voltage is adjusted iteratively to optimize the focal position. If the optimal focal length is not reached, the voltage V is continuously optimized.

[0012] Preferably, in S4, if the current resolution Below the set threshold , indicating that the focus has shifted, and the optical flow algorithm is used to detect whether the position of the photographed object has changed. Specifically: Use the imaging sensor to obtain two adjacent frames of images, and set the grayscale image of the current frame to be , assuming the previous grayscale image is ; Convert the two frames of images into grayscale images; Calculate the gradient of the image in the x and y directions to obtain spatial variation information: ; Use the Sobel operator to calculate the gradient: ;in: ; Calculate the time gradient: ; Since a single pixel cannot solve the two unknowns u and v, the Lucas-Kanade method finds the optimal solution within an n×n window: ;make: ; Solve for the optical flow vector: ; Determine whether the position of the photographed object has changed and calculate the mean optical flow vector of all feature points: ; Calculate the total amount of exercise: ; Where: M represents the overall motion of the object, N is the number of feature points, and the motion detection threshold MT is set. If M>MtT, it is determined that the photographed object has moved significantly and autofocus is triggered.

[0013] The present invention also provides an automatic focusing system based on a TFT liquid crystal panel, comprising an image acquisition module, an optical adjustment module, an automatic focusing control module and an adaptive optimization module; Image acquisition module: acquires image data of the current shooting scene, analyzes image clarity information through an imaging sensor, and calculates optimal focal length adjustment parameters based on the image clarity information; Optical adjustment module: applies control voltage to the TFT liquid crystal panel to change the arrangement state of the liquid crystal molecules, thereby dynamically adjusting the refractive index of the liquid crystal panel and determining the change in the focus position of the optical system; Autofocus control module: collects the adjusted image and compares the image quality before and after adjustment based on the clarity evaluation algorithm. If the image clarity does not reach the preset threshold, the control voltage is iteratively adjusted until the optimal focus position is obtained; Adaptive optimization module: After determining the optimal focus position, maintain the current voltage state to maintain the stable focus of the optical system, and automatically optimize the focus process according to the changes in the detection scene to ensure the stability of the focus state.

[0014] In the above technical solution, the technical effects and advantages provided by the present invention are: 1. The present invention provides an autofocus method and system based on a TFT liquid crystal panel, which realizes dynamic focusing without a mechanical structure by applying a control voltage to adjust the refractive index of the liquid crystal panel, thus overcoming the wear and response hysteresis problems of the traditional mechanical focusing system. The method uses an imaging sensor to obtain image data, and uses a clarity evaluation algorithm such as Laplace transform to calculate the optimal focal length adjustment parameter to accurately control the refractive index change of the liquid crystal panel, so as to make the focus adjustment more accurate. In addition, an iterative optimization mechanism is adopted to continuously optimize the control voltage by comparing the image clarity before and after adjustment in real time, so as to ensure that the system can quickly and stably realize autofocus, which is particularly suitable for high-resolution and large-aperture optical systems, significantly improving the imaging quality, and reducing problems such as edge blur, halo effect and aberration.

[0015] 2. The present invention also combines the optical flow detection algorithm to intelligently perceive the movement of the subject, ensuring that it can quickly refocus when the scene changes, thereby improving the intelligence level of autofocus. By calculating the optical flow vector, the system can accurately determine the overall movement trend of the subject, and trigger autofocus adjustment when significant movement is detected to ensure that the picture remains clear. At the same time, a temperature compensation mechanism is used to overcome the sensitivity of liquid crystal materials to ambient temperature and ensure the stability of focal length under long-term use. The present invention not only improves the accuracy and response speed of autofocus, but also enhances the adaptability to complex environments, making it have a wide range of application value in smart phones, micro projectors, high-end optical instruments and other fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0017] Figure 1 The figure is a flow chart of the method of the present invention.

[0018] Figure 2 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Example 1, please refer to Figure 1 As shown, the automatic focusing method based on the TFT liquid crystal panel described in this embodiment includes the following steps: S1: acquiring image data of a current shooting scene, analyzing image clarity information through an imaging sensor, and calculating optimal focal length adjustment parameters according to the image clarity information; S2: applying a control voltage to the TFT liquid crystal panel to change the arrangement state of the liquid crystal molecules, thereby dynamically adjusting the refractive index of the liquid crystal panel and determining the change in the focus position of the optical system; S3: collecting the adjusted image, and comparing the image quality before and after the adjustment based on the clarity evaluation algorithm. If the image clarity does not reach the preset threshold, iteratively adjusting the control voltage until the optimal focus position is obtained; S4: After determining the optimal focus position, the current voltage state is maintained to maintain the stable focus of the optical system, and the focus process is automatically optimized according to the changes in the detection scene to ensure the stability of the focus state.

[0021] In S1, a CMOS or CCD sensor is used to capture an image I(x,y) of the current scene. The image data is stored as a grayscale image. , used for subsequent clarity calculation, the formula is as follows: ; Represents the red, green, and blue channel values ​​at the pixel point (x, y) respectively.

[0022] The image clarity evaluation value S is calculated by Laplace transform, and the expression is: ; The Laplacian transform uses a 3×3 filter kernel, P is the number of rows of the image (the number of pixels in the vertical direction), and Q is the number of columns of the image (the number of pixels in the horizontal direction). The larger the S value, the clearer the image.

[0023] Define the current focus state as , the refractive index of the liquid crystal panel is , target clarity threshold , then the steps to adjust the focal length are: Calculate the new focal length, set is the current definition value, if , the focal length f needs to be adjusted to improve clarity; adjust the focal length by gradient ascent method: ; Where: α is the step size parameter (adaptive adjustment); Calculated by the change in image clarity: ; Calculate the voltage adjustment value of the LCD panel, assuming that the focal length f of the LCD panel is controlled by the refractive index n, and n is determined by the driving voltage V: ; Wherein, d is the thickness of the liquid crystal layer.

[0024] Adjusting the refractive index by voltage: ;in: is the initial refractive index, and β is the response coefficient of the liquid crystal refractive index to voltage.

[0025] Calculate the required voltage adjustment: ; Where: γ is the adaptive step size, Calculate the gradient of image sharpness as the voltage changes.

[0026] Iteratively optimize f and V until the clarity reaches the preset threshold .

[0027] In S2, step 1: applying an initial control voltage: applying an initial control voltage to the TFT liquid crystal panel according to the calculated optimal focal length adjustment parameters , driving the liquid crystal molecules to change their orientation.

[0028] Step 2: Liquid crystal molecule alignment adjustment: voltage After acting on the liquid crystal layer, the liquid crystal molecules rearrange, changing the equivalent refractive index of the liquid crystal layer. , refractive index The calculation formula is: ;in: is the initial refractive index when there is no voltage, and β is the voltage response coefficient of the liquid crystal material, which determines the amplitude of the refractive index change.

[0029] Step 3: Adjust the focal length of the optical system: The change in the refractive index of the liquid crystal layer affects the light propagation path, making the equivalent focal length of the optical system Changes occur, and the calculation formula is: ; Wherein, d is the equivalent optical thickness of the liquid crystal layer.

[0030] Step 4: Get the adjusted image data: After adjusting the focal length, get a new image through the imaging sensor , and compare the imaging effects before and after adjustment.

[0031] Step 5: Determine the change in focus position: Use image clarity evaluation algorithms (such as gradient contrast, Laplace transform) to calculate the current clarity value and the previous clarity value For comparison: If > , indicating that the focus has moved to the optimal position, and the voltage can be further fine-tuned to optimize the focus. < , indicating that the focus is off the optimal position and the voltage direction or step size needs to be adjusted. Reaching the preset threshold , the focus is considered complete and the current voltage value is locked .

[0032] In S3, calculate the current clarity The resolution of the previous frame Changes between: ; If ΔS>0, it means the image becomes clearer and the adjustment direction is correct; if ΔS<0, it means the image becomes blurred and the voltage direction or step size needs to be adjusted. Set the preset clarity threshold , if satisfied ≥ , the focusing is completed, and the control voltage is adjusted iteratively to optimize the focal position. If the optimal focal length is not reached, the voltage V is continuously optimized.

[0033] To ensure focus accuracy, the system sets a preset clarity threshold When the current resolution Meet or exceed When , it indicates that the optimal focus has been obtained, the system locks the current voltage, and the focus adjustment process ends. If the threshold value is still not reached, the system will continue to iteratively adjust the control voltage V, and by finely optimizing the refractive index, the focus of the optical system is further brought closer to the optimal imaging position. This method ensures the accuracy and stability of autofocus and avoids focus failure caused by insufficient or excessive adjustment.

[0034] The advantage of this method is that it can quickly determine the focus direction and adaptively adjust the voltage step size through dynamic feedback adjustment of the clarity change ΔS to improve the focus efficiency. At the same time, the preset clarity threshold ensures that the system can quickly and stably lock after reaching the optimal focus, preventing excessive adjustment from causing focal length oscillation. Compared with traditional fixed step size or blind scanning methods, the iterative optimization strategy of the present invention can reduce the amount of calculation, improve the response speed, and enable the system to obtain higher quality imaging effects in various shooting environments, especially suitable for dynamic scenes or high-resolution imaging applications.

[0035] In S4, if the image clarity ≥ , it is considered that the best focus position has been obtained. At this time, the current voltage Vopt is maintained to stabilize the refractive index of the liquid crystal panel to maintain the best focus state of the optical system.

[0036] Continuously monitor the input image of the imaging sensor, analyze the dynamic changes of the scene content, and determine whether the focus needs to be readjusted. The scene change detection method includes: if the current clarity Below the set threshold , indicating that the focus may be shifted, and the optical flow algorithm is used to detect whether the position of the photographed object has changed. Specifically: Use imaging sensor (CMOS / CCD) to obtain two adjacent frames of images: Let the grayscale image of the current frame be , assuming the previous grayscale image is ; Convert the two frames of images into grayscale images to reduce computational complexity; Calculate the gradient of the image in the x and y directions to obtain spatial variation information: ; Use the Sobel operator to calculate the gradient: ;in: ; Calculate the time gradient, that is, calculate the pixel difference between two frames of images. The expression is: .

[0037] Optical flow assumes that the gray value of the pixel remains unchanged during motion and satisfies the optical flow constraint equation: ; Where: u, v are the movement speed of the pixel in the x and y directions respectively (optical flow vector) is the image gradient, is the time gradient; Since a single pixel cannot solve the two unknowns (u, v), the Lucas-Kanade method finds the optimal solution within an n×n window: ;make: ; Solve for the optical flow vector: ; Determine whether the position of the photographed object has changed and calculate the mean optical flow vector of all feature points: ; Calculate the total amount of exercise: ; Where: M represents the overall motion of the object, N is the number of feature points, and the motion detection threshold MT is set. If M>MtT, it is determined that the photographed object has moved significantly and autofocus is triggered.

[0038] In this embodiment, by acquiring the image data of the current shooting scene, analyzing the image clarity information, and calculating the optimal focal length adjustment parameters. Subsequently, a control voltage is applied to the TFT liquid crystal panel to change the arrangement state of the liquid crystal molecules, dynamically adjust the refractive index of the liquid crystal panel, and determine the change in the focus position of the optical system. On this basis, the adjusted image is collected, and the image quality before and after the adjustment is compared based on the clarity evaluation algorithm. If the clarity does not reach the preset threshold, the control voltage is iteratively adjusted until the optimal focus position is obtained. After determining the optimal focus, the current voltage state is maintained to maintain the stable focus of the optical system, and the focusing process is automatically optimized according to the changes in the detection scene to ensure the continuous stability of the focus state.

[0039] Example 2, please refer to Figure 2 As shown, the automatic focusing system based on the TFT liquid crystal panel described in this embodiment includes an image acquisition module, an optical adjustment module, an automatic focusing control module and an adaptive optimization module; Image acquisition module: acquires image data of the current shooting scene, analyzes image clarity information through an imaging sensor, and calculates optimal focal length adjustment parameters based on the image clarity information; Optical adjustment module: applies control voltage to the TFT liquid crystal panel to change the arrangement state of the liquid crystal molecules, thereby dynamically adjusting the refractive index of the liquid crystal panel and determining the change in the focus position of the optical system; Autofocus control module: collects the adjusted image and compares the image quality before and after adjustment based on the clarity evaluation algorithm. If the image clarity does not reach the preset threshold, the control voltage is iteratively adjusted until the optimal focus position is obtained; Adaptive optimization module: After determining the optimal focus position, maintain the current voltage state to maintain the stable focus of the optical system, and automatically optimize the focus process according to the changes in the detection scene to ensure the stability of the focus state.

[0040] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0041] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0042] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0043] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0044] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0045] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. An automatic focusing method based on a TFT liquid crystal panel, characterized in that: The following steps are involved: S1: acquiring image data of a current shooting scene, analyzing image clarity information through an imaging sensor, and calculating optimal focal length adjustment parameters according to the image clarity information; S2: applying a control voltage to the TFT liquid crystal panel to change the arrangement state of the liquid crystal molecules, thereby dynamically adjusting the refractive index of the liquid crystal panel and determining the change in the focus position of the optical system; S3: collecting the adjusted image, and comparing the image quality before and after the adjustment based on the clarity evaluation algorithm. If the image clarity does not reach the preset threshold, iteratively adjusting the control voltage until the optimal focus position is obtained; S4: After determining the optimal focus position, the current voltage state is maintained to maintain the stable focus of the optical system, and the focus process is automatically optimized according to the changes in the detection scene to ensure the stability of the focus state.

2. The automatic focusing method based on a TFT liquid crystal panel according to claim 1, characterized in that: The S1 acquires image data through an imaging sensor and calculates image clarity information using the Laplace transform method to determine whether the current focal length needs to be adjusted, including calculating the image clarity evaluation value S through the Laplace transform, which is expressed as: ; In the formula, is the Laplace transform, P is the number of rows of the image, and Q is the number of columns of the image.

3. The automatic focusing method based on a TFT liquid crystal panel according to claim 2, characterized in that: The control voltage applied by S2 is calculated based on the focus adjustment parameter, the refractive index of the liquid crystal panel The relationship expression with voltage V is: ;in: is the initial refractive index when there is no voltage, and β is the voltage response coefficient of the liquid crystal material, which determines the amplitude of the refractive index change.

4. The automatic focusing method based on a TFT liquid crystal panel according to claim 3, characterized in that: The focal length Determined by the refractive index n of the liquid crystal panel, the calculation formula is: ; Wherein, d is the equivalent optical thickness of the liquid crystal layer.

5. The automatic focusing method based on a TFT liquid crystal panel according to claim 4, characterized in that: The S3 optimizes the focal length by iteratively adjusting the control voltage, and the voltage V is calculated as: ; Where: γ is the adaptive step size, It represents the gradient of calculating image clarity as voltage changes.

6. The automatic focusing method based on a TFT liquid crystal panel according to claim 5, characterized in that: Calculate current resolution The resolution of the previous frame Changes between: ; If ΔS>0, it means the image becomes clearer and the adjustment direction is correct; if ΔS<0, it means the image becomes blurred and the voltage direction or step size needs to be adjusted; set the preset clarity threshold , if satisfied ≥ , the focusing is completed, and the control voltage is adjusted iteratively to optimize the focal position. If the optimal focal length is not reached, the voltage V is continuously optimized.

7. The automatic focusing method based on a TFT liquid crystal panel according to claim 6, characterized in that: In S4, if the current resolution is Below the set threshold , indicating that the focus has shifted, and the optical flow algorithm is used to detect whether the position of the photographed object has changed. Specifically: Use the imaging sensor to obtain two adjacent frames of images, and set the grayscale image of the current frame to be , let the previous grayscale image be ; Convert the two frames of images into grayscale images; Calculate the gradient of the image in the x and y directions to obtain spatial variation information: ; Use the Sobel operator to calculate the gradient: ;in: ; Calculate time gradient , the expression is: ; Since a single pixel cannot solve the two unknowns u and v, the Lucas-Kanade method is used to find the optimal solution in an n×n window: ;make: ; Solve for the optical flow vector: ; Determine whether the position of the photographed object has changed and calculate the mean optical flow vector of all feature points: ; Calculate the total amount of exercise: ; Where: M represents the overall motion of the object, N is the number of feature points, and the motion detection threshold MT is set. If M>MtT, it is determined that the photographed object has moved significantly and autofocus is triggered.

8. An auto-focusing system based on a TFT liquid crystal panel, used to implement the auto-focusing method based on a TFT liquid crystal panel according to any one of claims 1 to 7, characterized in that: It includes image acquisition module, optical adjustment module, autofocus control module and adaptive optimization module; Image acquisition module: acquires image data of the current shooting scene, analyzes image clarity information through an imaging sensor, and calculates optimal focal length adjustment parameters based on the image clarity information; Optical adjustment module: applies control voltage to the TFT liquid crystal panel to change the arrangement state of the liquid crystal molecules, thereby dynamically adjusting the refractive index of the liquid crystal panel and determining the change in the focus position of the optical system; Autofocus control module: collects the adjusted image and compares the image quality before and after adjustment based on the clarity evaluation algorithm. If the image clarity does not reach the preset threshold, the control voltage is iteratively adjusted until the optimal focus position is obtained; Adaptive optimization module: After determining the optimal focus position, maintain the current voltage state to maintain the stable focus of the optical system, and automatically optimize the focus process according to the changes in the detection scene to ensure the stability of the focus state.

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