Deformation monitoring method, device and equipment based on circular target correction and medium

Abstract

The application discloses a deformation monitoring method and device based on circular target correction, equipment and medium, comprising: acquiring a template frame image and a real-time frame image corresponding to a circular target, and determining the center coordinates and the long-short axis parameters corresponding to the template frame image and the real-time frame image; constructing a mask image according to the center coordinates and the long-short axis parameters of the real-time frame image, and correcting the edge image of the real-time frame image based on the mask image to obtain a circular target contour image; determining a target center coordinate based on the circular target contour image, determining a target pixel displacement according to the target center coordinate and the center coordinates of the template frame image, and performing deformation monitoring based on the target pixel displacement. By constructing the mask image of the real-time target image, correcting the contour of the real-time collected target image according to the mask image, determining the target center coordinate according to the corrected contour, and realizing the deformation monitoring based on the corrected center coordinate, the precision of the deformation monitoring is improved.

Description

Technical Field

[0001] This invention relates to the field of deformation monitoring technology, and in particular to a deformation monitoring method, device, equipment and medium based on circular target calibration. Background Technology

[0002] To detect the degree of deformation of buildings, a method for visual deformation monitoring is to use a camera to monitor circular targets placed on the building in real time, extract the outline of the circular target, calculate the center of the ellipse by fitting the outline to the ellipse, and monitor the target based on the position change of the ellipse center in real time frames.

[0003] Existing deformation detection methods analyze the acquired target images to obtain the center position of the target. However, when the target is affected by changes in illumination, uneven brightness in the circular target area, or slight occlusion, the extracted circular target outline will affect the accuracy of ellipse fitting, resulting in errors in deformation monitoring. Summary of the Invention

[0004] This invention provides a deformation monitoring method, device, equipment, and medium based on circular target correction. By constructing a mask image of a target image acquired in real time, and correcting the contour of the target image based on the mask image, the center coordinates of the target circle are determined based on the corrected contour, and deformation monitoring is achieved based on the corrected center coordinates, thereby improving the accuracy of deformation monitoring.

[0005] According to one aspect of the present invention, a deformation monitoring method based on circular target correction is provided, comprising:

[0006] Obtain the template frame image and real-time frame image corresponding to the circular target, and determine the center coordinates and major and minor axis parameters corresponding to the template frame image and real-time frame image;

[0007] A mask image is constructed based on the center coordinates and major and minor axis parameters of the real-time frame image. The edge image of the real-time frame image is then pixel-corrected based on the mask image to obtain the circular target contour image.

[0008] The target center coordinates are determined based on the circular target contour image. The target pixel displacement is determined based on the target center coordinates and the center coordinates of the template frame image. Deformation monitoring is then performed based on the target pixel displacement.

[0009] According to another aspect of the present invention, a deformation monitoring device based on circular target correction is provided, comprising:

[0010] The data extraction module is used to acquire the template frame image and real-time frame image corresponding to the circular target, and to determine the center coordinates and major and minor axis parameters corresponding to the template frame image and real-time frame image.

[0011] The image correction module is used to construct a mask image based on the center coordinates and major and minor axis parameters of the real-time frame image, and to perform pixel correction on the edge image of the real-time frame image based on the mask image to obtain a circular target contour image;

[0012] The deformation monitoring module determines the target center coordinates based on the circular target outline image, determines the target pixel displacement based on the target center coordinates and the center coordinates of the template frame image, and performs deformation monitoring based on the target pixel displacement.

[0013] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0014] At least one processor; and

[0015] A memory that is communicatively connected to at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to execute the deformation monitoring method based on circular target correction according to any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to execute and implement the deformation monitoring method based on circular target correction according to any embodiment of the present invention.

[0018] The technical solution of this invention involves acquiring a template frame image and a real-time frame image corresponding to a circular target, and determining the center coordinates and major and minor axis parameters corresponding to the template frame image and the real-time frame image. A mask image is constructed based on the center coordinates and major and minor axis parameters of the real-time frame image. Pixel correction is performed on the edge image of the real-time frame image based on the mask image to obtain a circular target contour image. The target center coordinates are determined based on the circular target contour image. The target pixel displacement is determined based on the target center coordinates and the center coordinates of the template frame image, and deformation monitoring is performed based on the target pixel displacement. Based on the above technical solution, by constructing a mask image of the real-time acquired target image, correcting the contour of the real-time acquired target image based on the mask image, determining the target center coordinates based on the corrected contour, and then realizing deformation monitoring based on the corrected center coordinates, the accuracy of deformation monitoring is improved.

[0019] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of a deformation monitoring method based on circular target correction provided by an embodiment of the present invention;

[0022] Figure 2 This is a flowchart of a deformation monitoring method based on circular target correction provided by an embodiment of the present invention;

[0023] Figure 3 This is a schematic diagram of target template frame image processing provided in an embodiment of the present invention;

[0024] Figure 4 This is a schematic diagram of real-time frame image processing for a target provided in an embodiment of the present invention;

[0025] Figure 5 This is a schematic diagram of the basic mask image provided in an embodiment of the present invention;

[0026] Figure 6 This is a schematic diagram illustrating the generation of a mask image based on a sub-mask image, provided in an embodiment of the present invention.

[0027] Figure 7 This is a schematic diagram of the determination of the circular target contour image and the ellipse fitting result provided in the embodiment of the present invention;

[0028] Figure 8 This is a schematic diagram of the structure of a deformation monitoring device based on circular target correction provided in an embodiment of the present invention;

[0029] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] Figure 1 This is a flowchart illustrating a deformation monitoring method based on circular target correction, provided by an embodiment of the present invention. This embodiment is applicable to situations where the contour of a real-time image is corrected during building deformation monitoring, and deformation monitoring is performed based on the corrected contour. This method can be executed by a deformation monitoring device based on circular target correction, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method specifically includes the following steps:

[0033] S110. Obtain the template frame image and real-time frame image corresponding to the circular target, and determine the center coordinates and major and minor axis parameters corresponding to the template frame image and real-time frame image.

[0034] In this system, the circular target can serve as a reference marker for visual deformation monitoring. The template frame image can be understood as a reference image captured when the circular target is in a deformation-free state. The real-time frame image can be a monitoring image captured at different times to reflect the real-time deformation state of the target. The center coordinates can be understood as the position parameter of the center pixel of the circular target obtained through ellipse fitting. The major and minor axis parameters can be the pixel size parameters of the major and minor axes of the elliptical contour of the target obtained through ellipse fitting.

[0035] Specifically, the template frame image and real-time frame image corresponding to the circular target are acquired, and the center coordinates and major and minor axis parameters corresponding to the template frame image and real-time frame image are determined. For example, a reference image of the circular target without deformation and real-time images at different monitoring times can be acquired by a visual acquisition device. The two types of images are input into an edge fitting algorithm for processing. After contour extraction and ellipse fitting, the center coordinates and major and minor axis parameters corresponding to the template frame image and real-time frame image are output respectively, thus completing the acquisition of basic parameters.

[0036] Based on the above technical solution, the center coordinates and major and minor axis parameters corresponding to the template frame image and the real-time frame image are determined, including: inputting the template frame image into the edge fitting algorithm, and after contour extraction and ellipse fitting processing, obtaining the center coordinates and major and minor axis parameters of the template frame; inputting the real-time frame image into the edge fitting algorithm, and after contour extraction and ellipse fitting processing, obtaining the center coordinates and major and minor axis parameters of the real-time frame.

[0037] The edge fitting algorithm is an edge extraction ellipse fitting method, which uses a sub-pixel precision fitting approach. The template frame image is a baseline image acquired from a circular target in a deformation-free state. The edge fitting algorithm can be an edge extraction ellipse fitting method, which is an image algorithm that combines contour extraction and ellipse fitting. It is used to extract the elliptical contour from the target image and calculate its parameters.

[0038] Specifically, the template frame image can be input into the edge fitting algorithm. First, the edge contour of the target image is extracted by the algorithm. Then, the contour is fitted with an ellipse with sub-pixel precision to calculate the center coordinates and major and minor axis parameters of the template frame. Then, the real-time frame image is input into the edge fitting algorithm using the same algorithm processing flow to complete the extraction of the center coordinates and major and minor axis parameters of the real-time frame.

[0039] The technical solution of this invention processes two types of images through an edge fitting algorithm, ensuring the consistency of parameter extraction. The sub-pixel precision ellipse fitting effectively improves the extraction accuracy of the center coordinates and major and minor axis parameters, avoids the impact of basic parameter errors on subsequent deformation monitoring, and improves the accuracy of parameter extraction.

[0040] S120. Construct a mask image based on the center coordinates and major and minor axis parameters of the real-time frame image. Perform pixel correction on the edge image of the real-time frame image based on the mask image to obtain a circular target contour image.

[0041] The mask image can be an image mask constructed based on real-time frame parameters, used to filter out invalid edge pixels. The edge image can be understood as an image obtained by extracting target edge features from the real-time frame image, containing both valid and invalid edge pixels. Pixel correction can be an image processing procedure that filters out invalid pixels and retains valid target contour pixels through the mask. The circular target contour image can be understood as an image containing only the valid target contour after pixel correction, used for subsequent accurate fitting of the circle center.

[0042] Specifically, a mask image is constructed based on the center coordinates and major and minor axis parameters of the real-time frame image. The edge image of the real-time frame image is then pixel-corrected based on the mask image to obtain the circular target contour image. For example, the mask image can be constructed according to preset rules based on the center coordinates and major and minor axis parameters of the real-time frame image. Then, the edge image of the real-time frame image is extracted, and pixel operations are performed on the mask image and the edge image to filter out invalid edge pixels caused by lighting and occlusion, retaining only the valid contour pixels of the circular target to obtain the corrected circular target contour image.

[0043] Based on the above technical solution, a circular target contour image is obtained by pixel correction of the edge image of the real-time frame image based on the mask image, including: extracting the edge features of the real-time frame image using an edge fitting algorithm to generate a real-time frame edge image; performing a pixel AND operation between the mask image and the real-time frame edge image to filter out invalid edge pixels in the real-time frame edge image to obtain a circular target contour image.

[0044] Specifically, an edge fitting algorithm can be used to extract edge features from the real-time frame image, identify all edge pixels in the image and generate a real-time frame edge image, and then perform a pixel-by-pixel AND operation between the mask image and the edge image, retaining only the valid edge pixels within the mask's defined range and filtering out the invalid edge pixels outside the range, finally obtaining a circular target contour image that only contains the valid contour of the circular target.

[0045] The technical solution of this invention uses an edge fitting algorithm to accurately extract edge features of real-time frames, and then uses pixel AND operation to accurately filter invalid pixels, so that the corrected target contour image retains only valid features, eliminating the interference of factors such as lighting and occlusion on the target contour, and improving the realism and integrity of the target contour.

[0046] S130. Determine the target center coordinates based on the circular target contour image, determine the target pixel displacement based on the target center coordinates and the center coordinates of the template frame image, and perform deformation monitoring based on the target pixel displacement.

[0047] The target center coordinates can be precise coordinates obtained by fitting the corrected circular target contour image. Target pixel displacement can be understood as the pixel position difference between the target center coordinates and the template frame center coordinates, used to quantify the target's positional change. Deformation monitoring is the process of determining the deformation state of the monitored object through target pixel displacement analysis.

[0048] Specifically, the target center coordinates are determined based on the circular target outline image. The target pixel displacement is determined based on the target center coordinates and the center coordinates of the template frame image. Deformation monitoring is then performed based on the target pixel displacement. For example, the corrected circular target outline image can be input into an edge fitting algorithm for ellipse fitting to obtain accurate target center coordinates. Then, the pixel difference between these coordinates and the center coordinates of the template frame is calculated to obtain the target pixel displacement. Finally, the deformation of the monitored object is analyzed and judged based on the magnitude and direction of the pixel displacement to complete the deformation monitoring.

[0049] Based on the above technical solution, the target pixel displacement is determined according to the target center coordinates and the center coordinates of the template frame image, including: extracting the horizontal and vertical coordinates of the center coordinates of the template frame image and the target center coordinates; subtracting the horizontal coordinates of the target center coordinates from the horizontal coordinates of the template frame image to obtain the horizontal pixel displacement; and subtracting the vertical coordinates of the target center coordinates from the vertical coordinates of the template frame image to obtain the vertical pixel displacement.

[0050] Specifically, the horizontal and vertical pixel coordinates can be extracted from the center coordinates of the template frame and the center coordinates of the target circle, respectively. The horizontal pixel displacement is obtained by subtracting the horizontal coordinate value of the template frame from the horizontal coordinate value of the target circle. The vertical pixel displacement is obtained by subtracting the vertical coordinate value of the template frame from the vertical coordinate value of the target circle. This allows for the complete acquisition of pixel displacement data of the target in both directions.

[0051] The technical solution of this invention involves acquiring a template frame image and a real-time frame image corresponding to a circular target, and determining the center coordinates and major and minor axis parameters corresponding to the template frame image and the real-time frame image. A mask image is constructed based on the center coordinates and major and minor axis parameters of the real-time frame image. Pixel correction is performed on the edge image of the real-time frame image based on the mask image to obtain a circular target contour image. The target center coordinates are determined based on the circular target contour image. The target pixel displacement is determined based on the target center coordinates and the center coordinates of the template frame image, and deformation monitoring is performed based on the target pixel displacement. Based on the above technical solution, by constructing a mask image of the real-time acquired target image, correcting the contour of the real-time acquired target image based on the mask image, determining the target center coordinates based on the corrected contour, and then realizing deformation monitoring based on the corrected center coordinates, the accuracy of deformation monitoring is improved.

[0052] In one possible implementation of the present invention Figure 2 This invention provides a flowchart of a deformation monitoring method based on circular target correction. The invention further describes a technical solution for constructing a mask image based on the center coordinates and major and minor axis parameters of a real-time frame image. Figure 2 As shown, the method includes:

[0053] S210. Based on the size parameters of the real-time frame image, create a first base mask image and a second base mask image.

[0054] The first and second base mask images differ in their grayscale values. The size parameters can be the width and height in pixels of the real-time frame image, used to determine the size of the mask image. The first base mask image can be understood as a base mask image created based on the real-time frame size. The second base mask image is a base mask image with the same size as the first base mask image but different grayscale values.

[0055] Specifically, based on the size parameters of the real-time frame image, a first base mask image and a second base mask image are created. For example, the width and height pixel size parameters of the real-time frame image can be extracted, and two base mask images with exactly the same size can be created using these parameters as a standard. Different fixed grayscale values ​​are set for the two base mask images to obtain the first base mask image and the second base mask image.

[0056] S220. Construct a mask image based on the center coordinates and major and minor axis parameters of the real-time frame image, the first basic mask image, and the second basic mask image.

[0057] Specifically, a mask image is constructed based on the center coordinates and major and minor axis parameters of the real-time frame image, as well as a first base mask image and a second base mask image. For example, the center coordinates of the real-time frame image can be used as a reference, combined with the major and minor axis parameters, to draw mask regions of a specific range on the first base mask image and the second base mask image according to preset rules, resulting in two sub-mask images. Then, pixel-level operations are performed on the two sub-mask images, and they are fused to form the final mask image, thus completing the mask construction.

[0058] Based on the above technical solution, a mask image is constructed based on the center coordinates and major and minor axis parameters of the real-time frame image, a first base mask image, and a second base mask image. This includes: determining a first drawing radius based on the major axis parameter of the real-time frame image and a first preset coefficient, and drawing a first sub-mask image on the first base mask image according to the first drawing radius and the center coordinates of the real-time frame image; determining a second drawing radius based on the minor axis parameter of the real-time frame image and a second preset coefficient, and drawing a second sub-mask image on the second base mask image according to the second drawing radius and the center coordinates of the real-time frame image; and performing a pixel-wise AND operation on the first sub-mask image and the second sub-mask image to obtain the mask image.

[0059] The first preset coefficient can be a constant used to adjust the drawing range of the major axis, for example, it can be 2 pixels. The first drawing radius is a drawing radius calculated based on the major axis parameter and the first preset coefficient, used to draw the mask area on the first base mask. The second preset coefficient is a constant used to adjust the drawing range of the minor axis, which can be set according to actual monitoring needs. The second drawing radius can be a drawing radius calculated based on the minor axis parameter and the second preset coefficient, used to draw the mask area on the second base mask. The first sub-mask image can be understood as a mask image drawn on the first base mask, used to define the outer boundary of the target contour. The second sub-mask image can be a mask image drawn on the second base mask, used to define the inner boundary of the target contour.

[0060] Specifically, the major axis parameter of the real-time frame is multiplied by a first preset coefficient to obtain a first drawing radius. A circular region is drawn on the first base mask image with the center coordinates of the real-time frame as the center and filled with the corresponding gray value to obtain a first sub-mask image. In the same way, the minor axis parameter is multiplied by a second preset coefficient to obtain a second drawing radius. A circular region is drawn on the second base mask image and filled with the corresponding gray value to obtain a second sub-mask image. A pixel-by-pixel AND operation is performed on the two sub-mask images to obtain the final mask image.

[0061] The technical solution of this invention adjusts the drawing radius by preset coefficients, so that the mask range can adapt to the needs of different monitoring scenarios. The method of drawing and fusing dual radii accurately defines the upper and lower boundaries of the effective contour of the target, realizing accurate masking of the target contour. Subsequently, invalid edge pixels can be filtered more efficiently, improving the accuracy of pixel correction.

[0062] It should be noted that the technical solution of this invention adopts an ellipse fitting correction method for a circular target, ensuring the accuracy of the ellipse fitting despite uneven illumination and slight target occlusion. Time template frame target image , Real-time frame target image The specific technical solutions include:

[0063] calculate The initial frame center coordinates of the time template are as follows: Figure 3 As shown, the EdgeDrawing algorithm is used to... Initial frame image of time template The center of the target ellipse is obtained by ellipse fitting. and major and minor axes , .

[0064] Calculate the center coordinates of the real-time frame at time tn: (e.g.) Figure 4As shown, the EdgeDrawing algorithm is used to process the real-time frame target image at time tn. Obtain the center of the target ellipse by performing ellipse fitting. The major and minor axes are respectively , .

[0065] Constructing a mask: such as Figure 5 As shown in the image The width and height are respectively and ,by For leniency and Create a black image with a grayscale value of 0 for high definition. and For leniency and Create a white image with a grayscale value of 255. .like Figure 6 As shown in the image The center of the ellipse is above Centered on, major axis Draw a circle with radius , where (Set according to actual situation) as a constant, fill the inside of the circle with white to obtain the image. In the image Draw a circle with the center of the ellipse on top. Centered on, minor axis For radius, This is a constant, set according to the actual situation. The circle is filled with black to obtain the image. For mask images and Perform a bitwise AND operation on the pixels to obtain the mask image. .

[0066] Obtain the corrected profile: such as Figure 7 As shown, using a mask image and edge images Perform a pixel-wise AND operation to obtain the corrected target circle outline edge image. For images The coordinates of the circle center are calculated using EdgeDrawing for circle fitting, denoted as . .

[0067] Target pixel displacement calculation: using the real-time frame center coordinates at time tn and Initial frame center coordinates of the time template Subtraction yields the horizontal and vertical pixel displacements of the target.

[0068] The technical solution of this invention involves acquiring a template frame image and a real-time frame image corresponding to a circular target, and determining the center coordinates and major and minor axis parameters corresponding to the template frame image and the real-time frame image. A mask image is constructed based on the center coordinates and major and minor axis parameters of the real-time frame image. Pixel correction is performed on the edge image of the real-time frame image based on the mask image to obtain a circular target contour image. The target center coordinates are determined based on the circular target contour image. The target pixel displacement is determined based on the target center coordinates and the center coordinates of the template frame image, and deformation monitoring is performed based on the target pixel displacement. Based on the above technical solution, by constructing a mask image of the real-time acquired target image, correcting the contour of the real-time acquired target image based on the mask image, determining the target center coordinates based on the corrected contour, and then realizing deformation monitoring based on the corrected center coordinates, the accuracy of deformation monitoring is improved.

[0069] Figure 8 This is a schematic diagram of a deformation monitoring device based on circular target correction, provided as an embodiment of the present invention. Figure 8 As shown, the device includes: a data extraction module 810, an image correction module 820, and a deformation monitoring module 830.

[0070] The data extraction module 810 is used to acquire the template frame image and the real-time frame image corresponding to the circular target, and to determine the center coordinates and major and minor axis parameters corresponding to the template frame image and the real-time frame image.

[0071] The image correction module 820 is used to construct a mask image based on the center coordinates and major and minor axis parameters of the real-time frame image, and to perform pixel correction on the edge image of the real-time frame image based on the mask image to obtain a circular target contour image.

[0072] The deformation monitoring module 830 determines the target center coordinates based on the circular target outline image, determines the target pixel displacement based on the target center coordinates and the center coordinates of the template frame image, and performs deformation monitoring based on the target pixel displacement.

[0073] Based on the above technical solution, the data extraction module is used to input the template frame image into the edge fitting algorithm, and after contour extraction and ellipse fitting processing, obtain the center coordinates of the template frame and the major and minor axis parameters of the template frame; and input the real-time frame image into the edge fitting algorithm, and after contour extraction and ellipse fitting processing, obtain the center coordinates of the real-time frame and the major and minor axis parameters of the real-time frame.

[0074] Based on the above technical solution, the image correction module is used to create a first base mask image and a second base mask image according to the size parameters of the real-time frame image, wherein the grayscale values ​​of the first base mask image and the second base mask image are different; the mask image is constructed based on the center coordinates and major and minor axis parameters of the real-time frame image, the first base mask image and the second base mask image.

[0075] Based on the above technical solution, the image correction module is used to determine a first drawing radius based on the major axis parameter of the real-time frame image and a first preset coefficient, and draw a first sub-mask image on a first base mask image according to the first drawing radius and the center coordinates of the real-time frame image; determine a second drawing radius based on the minor axis parameter of the real-time frame image and a second preset coefficient, and draw a second sub-mask image on a second base mask image according to the second drawing radius and the center coordinates of the real-time frame image; and perform pixel bitwise AND operation on the first sub-mask image and the second sub-mask image to obtain the mask image.

[0076] Based on the above technical solution, the image correction module is used to extract the edge features of the real-time frame image using an edge fitting algorithm to generate a real-time frame edge image; and to perform a pixel-wise AND operation between the mask image and the real-time frame edge image to filter out invalid edge pixels in the real-time frame edge image to obtain the circular target contour image.

[0077] Based on the above technical solution, the deformation monitoring module is used to extract the horizontal and vertical coordinates of the center coordinates of the template frame image and the center coordinates of the target circle; to obtain the horizontal pixel displacement by subtracting the horizontal coordinates of the center coordinates of the target circle from the horizontal coordinates of the center coordinates of the template frame image; and to obtain the vertical pixel displacement by subtracting the vertical coordinates of the center coordinates of the target circle from the vertical coordinates of the template frame image.

[0078] Based on the above technical solution, the edge fitting algorithm is an edge extraction ellipse fitting method, the ellipse fitting adopts a sub-pixel precision fitting method, and the template frame image is a reference image collected from a circular target in a deformation state.

[0079] The technical solution of this invention involves acquiring a template frame image and a real-time frame image corresponding to a circular target, and determining the center coordinates and major and minor axis parameters corresponding to the template frame image and the real-time frame image. A mask image is constructed based on the center coordinates and major and minor axis parameters of the real-time frame image. Pixel correction is performed on the edge image of the real-time frame image based on the mask image to obtain a circular target contour image. The target center coordinates are determined based on the circular target contour image. The target pixel displacement is determined based on the target center coordinates and the center coordinates of the template frame image, and deformation monitoring is performed based on the target pixel displacement. Based on the above technical solution, by constructing a mask image of the real-time acquired target image, correcting the contour of the real-time acquired target image based on the mask image, determining the target center coordinates based on the corrected contour, and then realizing deformation monitoring based on the corrected center coordinates, the accuracy of deformation monitoring is improved.

[0080] The deformation monitoring device based on circular target correction provided in this embodiment of the invention can execute the deformation monitoring method based on circular target correction provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0081] Figure 9 A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0082] like Figure 9 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0083] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0084] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as deformation monitoring methods based on circular target correction.

[0085] In some embodiments, the deformation monitoring method based on circular target correction can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the deformation monitoring method based on circular target correction described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the deformation monitoring method based on circular target correction by any other suitable means (e.g., by means of firmware).

[0086] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0087] Computer programs used to implement the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0088] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0089] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0090] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0091] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0092] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0093] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A deformation monitoring method based on circular target correction, characterized in that, include: Obtain the template frame image and real-time frame image corresponding to the circular target, and determine the center coordinates and major and minor axis parameters corresponding to the template frame image and real-time frame image; A mask image is constructed based on the center coordinates and major and minor axis parameters of the real-time frame image. The edge image of the real-time frame image is then pixel-corrected based on the mask image to obtain a circular target outline image. The target center coordinates are determined based on the circular target outline image. The target pixel displacement is determined based on the target center coordinates and the center coordinates of the template frame image. Deformation monitoring is performed based on the target pixel displacement.

2. The method according to claim 1, characterized in that, The determination of the center coordinates and major and minor axis parameters corresponding to the template frame image and the real-time frame image includes: The template frame image is input into an edge fitting algorithm, and after contour extraction and ellipse fitting, the center coordinates of the template frame and the major and minor axis parameters of the template frame are obtained. The real-time frame image is input into the edge fitting algorithm, and after contour extraction and ellipse fitting, the center coordinates of the real-time frame and the major and minor axis parameters of the real-time frame are obtained.

3. The method according to claim 1, characterized in that, The process of constructing a mask image based on the center coordinates and major and minor axis parameters of the real-time frame image includes: Based on the size parameters of the real-time frame image, a first base mask image and a second base mask image are created, wherein the grayscale values ​​of the first base mask image and the second base mask image are different; The mask image is constructed based on the center coordinates and major and minor axis parameters of the real-time frame image, the first base mask image, and the second base mask image.

4. The method according to claim 3, characterized in that, The construction of the mask image based on the center coordinates and major and minor axis parameters of the real-time frame image, the first base mask image, and the second base mask image includes: The first drawing radius is determined based on the major axis parameter of the real-time frame image and the first preset coefficient, and the first sub-mask image is drawn on the first base mask image according to the first drawing radius and the center coordinates of the real-time frame image. The second drawing radius is determined based on the minor axis parameter of the real-time frame image and the second preset coefficient, and the second sub-mask image is drawn on the second base mask image according to the second drawing radius and the center coordinates of the real-time frame image. Perform a pixel-wise AND operation on the first sub-mask image and the second sub-mask image to obtain the mask image.

5. The method according to claim 1, characterized in that, The step of performing pixel correction on the edge image of the real-time frame image based on the mask image to obtain a circular target contour image includes: An edge fitting algorithm is used to extract the edge features of the real-time frame image to generate a real-time frame edge image. The mask image and the real-time frame edge image are subjected to a pixel-wise AND operation to filter out invalid edge pixels in the real-time frame edge image, thereby obtaining the circular target contour image.

6. The method according to claim 1, characterized in that, Determining the target pixel displacement based on the target center coordinates and the center coordinates of the template frame image includes: Extract the horizontal and vertical coordinates of the center of the target circle from the template frame image; The horizontal pixel displacement is obtained by subtracting the horizontal coordinate value of the target circle center coordinate from the horizontal coordinate value of the template frame image center coordinate; The vertical pixel displacement is obtained by subtracting the vertical coordinate value of the target circle center from the vertical coordinate value of the template frame image.

7. The method according to claim 2, characterized in that, The edge fitting algorithm is an edge extraction ellipse fitting method. The ellipse fitting adopts a sub-pixel precision fitting method. The template frame image is a reference image collected from a circular target in a deformation state.

8. A deformation monitoring device based on circular target correction, characterized in that, include: The data extraction module is used to acquire template frame images and real-time frame images corresponding to the circular target, and to determine the center coordinates and major and minor axis parameters corresponding to the template frame images and real-time frame images. The image correction module is used to construct a mask image based on the center coordinates and major and minor axis parameters of the real-time frame image, and to perform pixel correction on the edge image of the real-time frame image based on the mask image to obtain a circular target contour image; The deformation monitoring module determines the target center coordinates based on the circular target outline image, determines the target pixel displacement based on the target center coordinates and the center coordinates of the template frame image, and performs deformation monitoring based on the target pixel displacement.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the deformation monitoring method based on circular target correction as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the deformation monitoring method based on circular target correction as described in any one of claims 1-7.

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