Projection picture dynamic transformation method and system based on optical zooming

Abstract

The invention relates to the technical field of intelligent projection equipment, in particular to a projection picture dynamic conversion method and system based on optical zooming and a storage medium. The method comprises the following steps: determining an initial projection ratio R1, an initial projection picture coordinate CO1 and a target transformation coordinate CT1 of a projector; calculating a minimum enclosing rectangle according to CT1 to obtain a second projection picture coordinate CO2; dynamically calculating a target projection ratio R2 according to the bottom edge widths W1 and W2 of CO1 and CO2; controlling the optical zoom module to perform physical zooming according to the R2; a perspective transformation matrix is established according to the transformation relation between CO1 and CO2, perspective transformation is conducted on CT1 again, and a final display coordinate CT2 is obtained. According to the invention, optical zooming and digital conversion are cooperated, the problems of low pixel utilization rate, resolution loss, obvious gray edge and the like caused by pure digital processing are solved, and the definition and the display quality of a projection picture are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent projection equipment, in particular to a projection picture dynamic transformation method and system based on optical zoom and a storage medium. BACKGROUND

[0002] Projection equipment is increasingly popular in modern audio-visual applications, especially in home entertainment, business demonstration and education scenarios. In order to ensure that the projection picture can still present a regular rectangle at different projection angles and distances, it is usually necessary to perform trapezoidal correction. The traditional trapezoidal correction method mainly relies on digital image processing technology to achieve picture shape adjustment through geometric transformation of the image. However, this method has obvious limitations: the correction process often leads to a decrease in pixel utilization, a loss of resolution, and may introduce obvious gray edges, affecting the clarity and viewing experience of the final picture.

[0003] In the prior art, some solutions have tried to combine optical zoom to improve the above problems. However, they usually perform digital image processing (such as trapezoidal correction, obstacle avoidance, and curtain entry) based on a fixed projection ratio, do not fully utilize the characteristics of the optical zoom system to dynamically adjust the projection ratio, and result in low pixel utilization, decreased picture clarity, and obvious gray edges. For example, the comparative document CN115150595A proposes a method of displaying area transformation by optical zoom combined with camera-captured corner point coordinates, which reduces the resolution loss caused by trapezoidal correction to some extent, but it relies on multiple camera shots and coordinate transformation, which is computationally complex and has poor real-time performance, and does not disclose how to dynamically calculate the optimal projection ratio and its specific mapping relationship with motor control.

[0004] Therefore, there is an urgent need for a method that can dynamically adjust the optical zoom parameters and cooperatively realize picture scaling and shape correction, in order to effectively reduce resolution loss and gray edges while maintaining high pixel utilization, and to improve the overall quality of the projection picture and user experience. SUMMARY

[0005] The present application aims to solve the problems of low pixel utilization, complex transformation process, poor real-time performance, etc. in the prior art, and provides a dynamic projection ratio optimization method based on optical zoom, which cooperatively works through optical zoom and digital processing to achieve high-precision and high-efficiency projection picture transformation.

[0006] An embodiment of the present application provides a projection picture transformation method based on optical zoom, comprising the following steps:

[0007] determining the initial projection ratio R1 of the projector, the initial projection picture coordinates CO1 and the target transformation coordinates CT1;

[0008] calculating the minimum circumscribed rectangle of CT1 to obtain the second projection picture coordinates CO2;

[0009] The target projection ratio W2 is calculated according to the bottom edge widths W1 and W2 of CO1 and CO2, and the calculation formula is R2=R1*(W1 / W2);

[0010] The optical zoom module is controlled according to the R2 to perform picture scaling;

[0011] A perspective transformation matrix is established according to the transformation relationship between CO1 and CO2, CT1 is transformed to obtain the final display coordinates CT2.

[0012] In some embodiments, the initial projection picture coordinates CO1 is a rectangular region under the maximum resolution of the projector, and is represented as:

[0013] CO1=[[0,0],[Width-1,0],[Width-1,Height-1],[0,Height-1]],

[0014] Wherein, Width and Height are the horizontal and vertical resolutions of the projector, respectively.

[0015] In some embodiments, the target transformation coordinates CT1 is a quadrilateral coordinate set calculated by a trapezoidal correction, an obstacle avoidance or a curtain entering algorithm.

[0016] In some embodiments, the calculation method of the minimum circumscribed rectangle is to take the circumscribed rectangle after center reduction of CT1 with the center of the bottom edge of CO1 as the reference.

[0017] In some embodiments, the control of the optical zoom module is realized by a stepping motor, including the following calibration steps:

[0018] Project a feature map to a calibration board at a specified position;

[0019] Obtain the real distance of the corner points in the feature map by image processing method;

[0020] Calculate the current projection ratio according to the fixed distance between the projector and the calibration board;

[0021] Record the corresponding relationship between the motor step number and the projection ratio, and fit a linear formula.

[0022] In some embodiments, the real distance of the corner points in the feature map is obtained by an image processing method, including:

[0023] Identify and extract the corner point coordinates of the checkerboard pattern in the feature map;

[0024] Identify and extract the corner point and / or center coordinates of the ArUco marker in the feature map.

[0025] In some embodiments, the calculation formula of the projection ratio R is:

[0026]

[0027] wherein D is the distance between the projector and the calibration board, w is the real distance between two corner points of the chessboard bottom edge in the feature map, and λ is the ratio of the projector's maximum picture W to w.

[0028] In some embodiments, the formula for calculating the motor target step number is:

[0029]

[0030] wherein Rmin and Rmax are the minimum and maximum projection ratios, respectively, Step is the total step number, and Rtarget is the target projection ratio. min and R max are the minimum and maximum projection ratios, respectively, Step total is the total step number, and R target is the target projection ratio.

[0031] In some embodiments, the perspective transformation matrix M is:

[0032]

[0033] wherein the element m22 = 1 is used to maintain the normalization of the homogeneous coordinates.

[0034] In another aspect, an optical zoom-based projection picture transformation system is provided, comprising:

[0035] an optical zoom lens group;

[0036] a stepping motor for driving the optical zoom lens group to zoom;

[0037] an image processing unit for executing the above-mentioned optical zoom-based projection picture transformation method;

[0038] a control unit for coordinating the optical zoom and image processing processes.

[0039] In yet another aspect, a computer readable storage medium is provided, having stored thereon a computer program which, when executed by a processor, implements the above-mentioned optical zoom-based projection picture transformation method.

[0040] In some embodiments, the computer program further comprises instructions for implementing automatic calibration of the distance between the projector and the calibration board.

[0041] The above technical solutions have the following technical effects:

[0042] The application overcomes the problem of low pixel utilization caused by traditional pure digital picture transformation, significantly reduces resolution loss and projection gray edge phenomenon, and greatly improves the clarity, brightness and overall display quality of the projection picture, thereby greatly improving the user's viewing experience. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 A flowchart of a projection picture transformation method based on optical zoom of an embodiment of the application is shown in FIG. 1.

[0044] Figure 2 A schematic diagram of the principle of the projection picture transformation method based on optical zoom of the application is shown in FIG. 2.

[0045] Figure 3 A schematic diagram of the calibration board and feature map in an embodiment of the application is shown in FIG. 3. DETAILED DESCRIPTION

[0046] To further illustrate the embodiments, the application provides accompanying drawings. These drawings are part of the disclosure of the application and mainly serve to illustrate the embodiments and can be used to explain the operating principle of the embodiments in conjunction with the related description of the specification. Those of ordinary skill in the art should be able to understand other possible implementations and advantages of the application in conjunction with these contents. The components in the drawings are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0047] The various steps of the method of the application will be described in detail below in conjunction with the flowchart of FIG. 4. Figure 1

[0048] Step S101: Determine the initial projection ratio R1, the initial projection picture coordinates CO1 and the target transformation coordinates CT1 of the projector.

[0049] This step is the initialization stage of the method, which aims to obtain the reference parameters for calculation. Specifically as follows:

[0050] Determine the initial projection ratio R1: The projection ratio R is defined as the ratio of the projection distance D to the picture width W (R=D / W). The initial projection ratio R1 can be a factory preset value, a user manually set value, or a value stored through the last calibration record.

[0051] ​Determine the initial projection screen coordinates CO1: CO1 represents the largest rectangular image that the projector can project without any digital correction at the current initial throw ratio R1. In some embodiments, for ease of subsequent calculations, this coordinate is defined based on the projector's original physical resolution (Width*Height). Its coordinate values ​​are typically set as: CO1 = [[0,0],[Width-1,0],[Width-1,Height-1],[0,Height-1]], where Width and Height are the projector's horizontal and vertical resolutions, respectively. This rectangle defines the physical boundaries of the pixel mapping.

[0052] Determine the target transformation coordinates CT1: CT1 is the target coordinate obtained after digital preprocessing of the geometry of the desired final displayed image. In some embodiments, it is typically a quadrilateral, the shape of which is determined by specific application requirements.

[0053] Keystone correction: When the projector projects from the side, in order to obtain a square image, the digital processing algorithm will calculate a trapezoidal twisted grid, and the coordinates of the four corner points of the grid are CT1.

[0054] Intelligent obstacle avoidance: When there are obstacles (such as picture frames or switches) in the projection area, the algorithm will calculate an irregular quadrilateral area that avoids the obstacles, and the coordinates of its corner points are CT1.

[0055] Automatic screen alignment: When the projection area is smaller than the screen, the algorithm will calculate a rectangle that is aligned with the screen border, and the coordinates of its corner point are CT1.

[0056] The mathematical expression for CT1 is: [[x0,y0],[x1,y1],[x2,y2],[x3,y3]].

[0057] Step S102: Calculate the minimum bounding rectangle of CT1 to obtain the coordinates CO2 of the second projection screen.

[0058] The core idea of ​​this step is to find a minimum rectangular bounding box (CO2) that will be achieved through optical zoom in order to fully accommodate the desired display area (CT1) and maximize the use of optical zoom to reduce the digital processing area.

[0059] In some embodiments, such as Figure 2 As shown, calculate the minimum bounding rectangle of CT1, scaled down with the center of the bottom edge of CO1 as the reference. A specific algorithm could be:

[0060] Calculate the distance Lx of each x coordinate of CT1 to CO1, and the distance Ly of the y coordinate of the top edge of CT1 to CO1, and take the minimum value of Lx / W1 and Ly / H1 as the scaling ratio, where the length of the left or right side of CO1 is H1, and calculate CO2. The width of the bottom of this rectangle CO2 is W2 required for subsequent calculation.

[0061] Step S103: Calculate the target projection ratio R2 according to the bottom widths W1 and W2 of CO1 and CO2.

[0062] This step realizes the dynamic optimization calculation of the projection ratio, which is the key to the cooperation of optics and digital. It contains formula derivation: the projection ratio formula is R=D / W. Since the projection distance D is fixed in a short time, the projection ratio R is inversely proportional to the picture width W. That is, R1 / R2=W2 / W1. From this, the calculation formula of the target projection ratio is derived as follows:

[0063] R2=R1*W1 / W2

[0064] Where W1 is the bottom width of CO1, and W2 is the bottom width of CO2. R2 calculated by this formula is the optimal optical projection ratio required to display CO2 perfectly.

[0065] Step S104: Control the optical zoom module to scale the picture according to R2.

[0066] After calculating the target projection ratio R2, it needs to be converted into control instructions for the stepping motor to drive the optical lens to move to the precise position. Therefore, it is necessary to establish a mapping relationship between the projection ratio R and the number of steps Step of the stepping motor in advance, that is, to carry out the calibration process, which is crucial for accurate control of the movement of the optical lens. The specific calibration process at least includes the following contents:

[0067] Build environment: Fix the projector at a fixed distance D from the calibration board, and make sure that the lens optical axis is perpendicular to the calibration board.

[0068] Project feature map: The projector projects a pre-defined feature pattern onto the calibration board, such as Figure 3 As shown in the figure, there is an ArUco code on the calibration board, and the calibration board image should contain a checkerboard and an ArUco code. The checkerboard is used for high-precision corner detection, and the ArUco code is used to provide absolute scale and orientation reference.

[0069] Image capture and processing: Capture the calibration board image through the camera built-in or external to the projector. Then, the image processing unit uses algorithms in the vision library (such as OpenCV, Halcon, VisionPro, Dlib, MATLAB Computer Vision Toolbox, etc.) for processing:

[0070] For example, in some embodiments, the OpenCV vision library is employed and the findChessboardCorners() function is called to accurately identify all the internal corner points of the checkerboard pattern and obtain their pixel coordinates in the camera image. In addition, the detectMarkers() function is called to detect ArUco markers and obtain the pixel coordinates of their four corner points and center point as well as the marker ID.

[0071] Establish a mapping relationship: control the stepper motor to move uniformly from the minimum mechanical limit to the maximum value, and pause every certain number of steps. Since continuous data cannot be obtained, sampling is used to obtain discrete data. For example, the minimum projection ratio of the projector is R min , and the maximum projection ratio is R max ; during the movement of the motor from the minimum limit to the maximum limit, the motor step number Step total from R min to R max is recorded. Finally, linear fitting is performed on these data points, and the number of steps of the stepper motor is calculated according to the projection ratio, realizing the scaling of the projection picture.

[0072] Real-time control: according to the calculated target projection ratio R2, the inverse of the target stepper value is obtained using the formula obtained from the calibration: Subsequently, instructions are sent to the motor driver to drive the stepper motor to move accurately to the Step target position. At this point, the projection picture has completed physical scaling through optical zoom.

[0073] Step S105: According to the transformation relationship between CO1 and CO2, a perspective transformation matrix is established to transform CT1 to obtain the final display coordinates CT2.

[0074] After optical scaling is completed, the original coordinate system has changed (from CO1 to CO2), so it is necessary to recalculate the position of the desired display area CT1 in the new coordinate system. According to the transformation relationship between CO1 and CO2, a perspective transformation matrix M is established to perform perspective transformation on CT1 to obtain the final display coordinates CT2.

[0075] In some embodiments, the process of establishing the perspective transformation matrix M is as follows:

[0076]

[0077] where the perspective transformation matrix M is:

[0078]

[0079] where: Control linear transformation operations such as scaling, rotation, and shearing; Control the panning operation;[m 20 m 21 ]Affect the perspective effect and change the sense of distance;m 22 Usually fixed as 1, indicating "homogeneous coordinates", which is an important feature of the perspective transformation matrix, so that the matrix can represent all affine transformations including translation, rotation and perspective, as well as perspective transformations.

[0080] In this way, a 3x3 perspective transformation matrix is obtained, which can map the points in CO2 to the points in CO1 (or vice versa). Of course, in some embodiments, the getPerspectiveTransform() or findHomography() functions in the vision library such as OpenCV can also be used, and the four corner coordinates of CO2 and CO1 are input to calculate the perspective transformation matrix M. Transform CT1 to get CT2: After obtaining the perspective transformation matrix M, the original digital transformation target CT1 can be perspective transformed to obtain the final display coordinates CT2.

[0081] Through the above steps, the input original image is real-time geometrically corrected (texture mapping) according to the finally determined display coordinates CT2. The corrected image signal is projected out through the optical lens which has been in the R2 state. Finally, the user sees a high-definition picture that has been first optically zoomed to the best size and then finely digitally corrected, thereby achieving the best balance between clarity and form. The present application does not rely on multiple camera shots, but realizes optical control through single calibration + formula calculation; and realizes dynamic optimization through external rectangle calculation + projection ratio formula, rather than relying on image coordinate transformation. By converting the complex and uncontrollable "real-time visual perception" problem into a simple and controllable "offline calibration + online calculation" problem, the present application realizes overall optimization in speed, cost, stability, accuracy and consistency, etc. in multiple dimensions.

[0082] In some embodiments, the control of the optical zoom module is realized through a stepper motor, including the following calibration steps:

[0083] Project the feature map to the calibration board at the specified position;

[0084] Obtain the real distance of the corner points in the feature map through image processing method;

[0085] Calculate the current projection ratio according to the fixed distance between the projector and the calibration board;

[0086] Record the corresponding relationship between the motor step number and the projection ratio, and fit the linear formula.

[0087] In the above embodiment, the "image processing method" includes corner detection and perspective transformation. Since the feature map contains a chessboard pattern with known physical size, and the ArUco (or AprilTag) markers are provided on the calibration board, after capturing the image of the calibration board by the camera, the pixel coordinates of the corners in the chessboard are first identified with high precision using the findChessboardCorners() function in the image vision processing library (such as OpenCV); at the same time, the detectMarkers() function is used to identify the ArUco markers, and the pixel coordinates of the four corners and the center and their unique IDs are obtained. Since the physical size of the ArUco marker is known in advance, it can be used as a scale reference of the world coordinate system. Through the perspective transformation algorithm, the rotation and translation vectors from the camera image plane to the world coordinate system of the calibration board are solved, and a complete perspective transformation model is constructed. Using this model, the pixel coordinates of the corners of the chessboard can be accurately converted to the world coordinate system, and the real physical distance w between any two corners on the bottom side of the chessboard can be calculated.

[0088] Through the above embodiment, high-precision chessboard corner detection and ArUco markers based on absolute scale are used to convert the optical projection ratio measurement into accurate physical distance measurement, greatly improving the accuracy of the calibration data. The linear model established has high certainty and repeatability. After one-time calibration, all real-time image transformation operations do not require the participation of the camera. The system is downgraded from a complex "visual feedback control system" to a simple "formula lookup-motor driven" open-loop control system. In actual use, the algorithm only needs to perform millisecond-level mathematical calculations (calculate the circumscribed rectangle, substitute the formula to calculate the number of steps), and then directly drive the motor. This completely avoids the time-consuming "projection-shooting-image processing" cycle of hundreds of milliseconds or even seconds, making the response speed of functions such as trapezoidal correction and obstacle avoidance extremely fast, and the user experience smooth and unnoticeable.

[0089] In addition, the calibration method using the above embodiment greatly reduces the requirement for real-time image processing computing power; at the same time, it allows the use of lower-cost or does not require the use of a special high-performance camera, because the camera is only used once in the factory before calibration. Since it is no longer disturbed by variables such as ambient light, camera focusing status, and calibration board surface color, its accuracy is only determined by the high-precision calibration environment at the time of factory shipment, ensuring the high consistency of performance among all products. Based on this accurate pre-calibration model, the cooperative mechanism of the present application "first optically zooming the physical image, and then digitally perspective transforming for fine correction" can be efficiently and reliably implemented, thereby fundamentally solving the defects of pure digital transformation.

[0090] In some embodiments, the real distance of the corner points in the feature map is obtained by the image processing method, comprising:

[0091] identifying and extracting the corner point coordinates of the checkerboard pattern in the feature map;

[0092] identifying and extracting the corner point and / or center coordinates of the ArUco marker in the feature map.

[0093] The above embodiment realizes complementary advantages by fusing the mixed feature map of the checkerboard pattern and the ArUco marker, and brings significant beneficial effects: the checkerboard pattern provides a large number of high-distribution-density corner points, laying a high-precision data foundation for camera calibration and perspective transformation calculation; and the ArUco marker provides indispensable scale reference and coordinate origin for the entire calculation by virtue of its pre-set, absolutely known physical size. This combination successfully converts the pixel coordinates in the image to the real-world coordinate system, thereby calculating the real physical distance between the corner points. The ultimate effect is to greatly improve the absolute accuracy and reliability of the projection ratio calibration data, and to convert the complex, easily disturbed real-time visual measurement into a one-time, controllable, high-precision calibration process, thereby creating conditions for subsequent real-time, high-precision optical control without the participation of the camera.

[0094] In some embodiments, the current projection ratio is calculated according to the fixed distance between the projector and the calibration board. Since the physical size of the ArUco marker is known, the pixel coordinates of the checkerboard corner points can be converted to the real-world coordinate system by combining the perspective transformation and the proportional relationship between the pixel size and the physical size, thereby calculating the real physical distance w between the two corner points of the checkerboard bottom edge. Since the distance w between the two corner points of the checkerboard bottom edge in the feature map is 1 / λ of the maximum projection picture, W is λ times w, i.e. W = λw. Substituting the formula, the current projection ratio can be obtained:

[0095] The above embodiment uses a known, fixed physical reference (ArUco marker) and a pre-set, determined proportional relationship to convert the calculation of the difficult-to-directly-measure physical width (W) of the projection picture into the measurement of a small-size, high-precision feature (checkerboard bottom edge w). By providing an absolute scale through the ArUco marker, the algorithm can accurately calculate the physical value of w, and then indirectly and accurately deduce the real width W of the entire projection picture according to the fixed proportional relationship of W = λw. This method greatly reduces the errors that may be caused by directly measuring the size of a large picture, and ultimately makes the calculation result of the projection ratio R = D / (λw) have very high accuracy and reliability. This not only provides a reliable data basis for establishing an accurate linear model between the motor step number and the projection ratio, but also enables the present application to shift from "relying on real-time visual feedback" to "relying on pre-calibration mathematical model" to achieve efficient and stable open-loop control.

[0096] In the above embodiment, the calculation formula of the motor target step number is:

[0097]

[0098] wherein R min and R max are the minimum and maximum projection ratios respectively, Step total is the step number, R target is the target projection ratio.

[0099] The linear calculation formula provided by the embodiment simplifies the complex and nonlinear physical zooming process in the optical system into an extremely simple and efficient linear mathematical model. After obtaining the three key parameters R min , R max and Step total through pre-calibration, there is no need for complex real-time calculation or sensor feedback in the specific implementation. Only the target projection ratio R target calculated dynamically needs to be substituted into the formula, and the required Step target can be solved instantaneously. This realizes open-loop control of the optical lens, brings millisecond-level response speed, extremely low calculation resource consumption and extremely high execution reliability. The control strategy of “substituting formula for perception” is conducive to the application to get rid of real-time dependence on the camera and realizes high-speed dynamic optimization of the optical lens control, providing users with seamless, smooth and waiting-free picture experience.

[0100] On the other hand, the application also provides a projection picture transformation system based on optical zooming, comprising:

[0101] an optical zoom lens group;

[0102] a stepping motor for driving the optical zoom lens group to zoom;

[0103] an image processing unit for executing the projection picture transformation method based on optical zooming described above;

[0104] a control unit for coordinating the optical zooming and image processing processes.

[0105] In the optical zoom-based projection picture transformation system of the above embodiments, the image processing unit is responsible for performing all the computationally intensive tasks (such as dynamically calculating the target projection ratio and the perspective transformation matrix), while the control unit serves as the central nerve, accurately coordinating the timing and interaction of the two processes of optical zoom (physical scaling) and image processing (digital correction). This division of labor ensures that the system can first instruct the stepper motor to drive the optical zoom lens group to complete the physical picture scaling, and then perform digital transformation, thereby strictly implementing the cooperative optimization logic of "optical first, digital second". Through this hardware and software cooperation, optical and digital step-by-step collaboration system structure setting, the efficient execution of the method of the present application is fundamentally ensured, and finally the fast and high-precision picture form transformation is completed under the premise of maximum retention of original pixels and elimination of gray edges, thereby guaranteeing the overall improvement of the clarity, brightness and user experience of the final projection picture at the system level.

[0106] Further, as an executable solution, the image processing unit can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The processor is the control center of the computer unit, and connects various parts of the computer unit through various interfaces and lines.

[0107] In some embodiments, the present application also provides a computer readable storage medium storing a computer program, wherein the computer program is executed by a processor to implement the steps of the above-mentioned method of the embodiments of the present application.

[0108] The modules / cells integrated by the computer units, if realized in the form of software function units and sold or used as independent products, can be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. The computer program can implement the steps of each method embodiment when executed by a processor. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM) and software distribution medium, etc. It should be noted that the content included in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction.

[0109] In some embodiments, the above computer program further includes instructions for implementing automatic calibration of the distance between the projector and the calibration board.

[0110] Although the present application is specifically shown and described in connection with the preferred embodiments, those skilled in the art will appreciate that various modifications in form and detail can be made without departing from the spirit and scope of the application as defined by the appended claims.

Claims

1. An optical zoom-based projection picture transformation method, characterized by, The method comprises the following steps: determining an initial projection ratio R1 of the projector, an initial projection picture coordinate CO1 and a target transformation coordinate CT1; calculating a minimum circumscribed rectangle of the CT1 to obtain a second projection picture coordinate CO2; calculating a target projection ratio R2 according to the bottom width W1 and W2 of the CO1 and CO2, and the calculation formula is R2=R1*(W1 / W2); controlling the optical zoom module to perform picture scaling according to the R2; establishing a perspective transformation matrix according to the transformation relationship between the CO1 and CO2, and transforming the CT1 to obtain a final display coordinate CT2.

2. The method of claim 1, wherein, The initial projection picture coordinate CO1 is a rectangular area under the maximum resolution of the projector, and is expressed as: CO1=[[0,0],[Width-1,0],[Width-1,Height-1],[0,Height-1]], wherein Width and Height are the horizontal and vertical resolutions of the projector respectively.

3. The method of claim 1, wherein, The target transformation coordinate CT1 is a quadrilateral coordinate set calculated by a trapezoidal correction, obstacle avoidance or curtain entering algorithm.

4. The method of claim 1, wherein, The calculation method of the minimum circumscribed rectangle is to take the circumscribed rectangle after center reduction of the CT1 with the center of the bottom edge of CO1 as the reference.

5. The method of claim 1, wherein, The control of the optical zoom module is realized by a stepping motor, and the following calibration steps are included: projecting a feature map to a calibration board at a specified position; obtaining the real distance of the corner points in the feature map by an image processing method; calculating the current projection ratio according to the fixed distance between the projector and the calibration board; recording the corresponding relationship between the motor step number and the projection ratio, and fitting a linear formula.

6. The method of claim 5, wherein, The method for obtaining the real distance of the corner points in the feature map by the image processing method comprises: identifying and extracting the corner point coordinates of the checkerboard pattern in the feature map; identifying and extracting the corner point and / or center coordinates of the ArUco marker in the feature map.

7. The method of claim 5, wherein, The calculation formula of the projection ratio R is: wherein D is the distance between the projector and the calibration board, w is the real distance of the two corner points of the checkerboard bottom edge in the feature map, and λ is the ratio of the maximum picture W of the projector to w.

8. The method of claim 5, wherein, The calculation formula of the motor target step number is: where R min and R max are the minimum and maximum projection ratios, respectively, Step total is the number of steps, and R target is the target projection ratio.

9. The method of claim 1, wherein, The perspective transformation matrix M is: wherein the element m22=1 is used to maintain the normalization of the homogeneous coordinates.

10. An optical zoom-based projection picture transformation system, characterized by It comprises: an optical zoom lens group; a stepping motor for driving the optical zoom lens group to zoom; an image processing unit for executing the method according to any one of claims 1 to 9; a control unit for coordinating the optical zoom and image processing processes.

11. A computer readable storage medium having stored thereon a computer program, characterized in that, The program is executed by a processor to realize the method according to any one of claims 1 to 9.

12. The computer-readable storage medium of claim 11, wherein, The computer program further comprises instructions for realizing automatic calibration of the distance between the projector and the calibration board.

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