Base station antenna surface detection method, terminal device, and storage medium

Abstract

A base station antenna surface detection method, a terminal device, and a storage medium. The base station antenna surface detection method comprises: acquiring an image of a base station antenna surface, wherein auxiliary points are marked in the image (S10); detecting a key feature point of the base station antenna surface on the basis of the auxiliary points, and obtaining a pixel position of the key feature point (S20); and performing calculation according to the pixel position of the key feature point, so as to obtain a three-dimensional spatial position of the key feature point (S30).

Description

Base station antenna surface detection method, terminal device and storage medium

[0001] Related applications

[0002] This application claims priority to Chinese patent application No. 202310756585.9 filed on June 25, 2023, the entire contents of which are incorporated by reference into this application. Technical Field

[0003] The present application relates to the field of communication technology, and in particular to a base station antenna surface detection method, terminal equipment, and storage medium. Background Art

[0004] With the continuous development of wireless communication technology, the number of communication base stations has become enormous. Communication base stations are usually installed outdoors. Due to factors such as climate and topography, the engineering parameters of the base station antennas may change at any time. Therefore, to ensure the normal operation of the communication base stations, the engineering parameters of the base station antennas need to be tested and calibrated.

[0005] At present, there is a photo-based base station antenna surface detection method, which mainly uses a drone to photograph the base station antenna surface to obtain photos, and then identifies the antenna surface or feature points of the antenna surface in the photos to obtain identification results. Finally, engineering parameter measurements are performed based on the identification results to obtain the engineering parameters of the antenna surface.

[0006] However, in the existing method, the identification of the antenna surface or antenna surface feature points is easily affected by the complex background, resulting in low accuracy of antenna surface detection.

[0007] Summary of the Invention

[0008] The main purpose of this application is to provide a base station antenna surface detection method, terminal equipment and storage medium, aiming to improve the accuracy of antenna surface detection.

[0009] To achieve the above objectives, the present application provides a base station antenna surface detection method, the method comprising:

[0010] Acquire an image of the base station antenna surface, wherein the image has auxiliary points marked therein;

[0011] Detecting key feature points of the antenna surface in the image based on the auxiliary points, and obtaining pixel positions of the key feature points;

[0012] The three-dimensional spatial position of the key feature point is obtained by calculating the pixel position of the key feature point.

[0013] The present application also provides a base station antenna surface detection device, the device comprising:

[0014] An image acquisition module, configured to acquire an image of the base station antenna surface, wherein the image is marked with auxiliary points;

[0015] a feature point detection module, configured to detect key feature points of the antenna surface in the image based on the auxiliary points, and obtain pixel positions of the key feature points;

[0016] The three-dimensional space solving module is used to solve the three-dimensional space position of the key feature point according to the pixel position of the key feature point.

[0017] An embodiment of the present application also proposes a terminal device, which includes a memory, a processor, and a base station antenna surface detection program stored in the memory and runnable on the processor. When the base station antenna surface detection program is executed by the processor, the base station antenna surface detection method described above is implemented.

[0018] An embodiment of the present application further provides a computer-readable storage medium, on which a base station antenna surface detection program is stored. When the base station antenna surface detection program is executed by a processor, the base station antenna surface detection method described above is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] FIG1 is a schematic diagram of the functional modules of a terminal device to which the base station antenna surface detection device of the present application belongs;

[0020] FIG2 is a flow chart of a first embodiment of a base station antenna surface detection method according to the present application;

[0021] FIG3 is a schematic diagram of pixel point traversal observation and spatial projection based on the auxiliary points and in combination with the first reference interval length in an embodiment of the base station antenna surface detection method of the present application;

[0022] FIG4 is a schematic diagram of pixel point traversal observation and spatial projection based on the auxiliary points and in combination with the second reference interval length in an embodiment of the base station antenna surface detection method of the present application;

[0023] FIG5 is a flow chart of a fourth embodiment of a base station antenna surface detection method according to the present application;

[0024] FIG6 is a schematic diagram of a detailed process of performing real-time base station antenna surface detection according to an embodiment of the present application.

[0025] The realization of the objectives, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0026] It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application.

[0027] The main solution of the embodiment of the present application is: obtain an image of the base station antenna surface, in which auxiliary points are marked; detect key feature points of the antenna surface in the image based on the auxiliary points, and obtain the pixel positions of the key feature points; calculate the three-dimensional spatial positions of the key feature points based on the pixel positions of the key feature points; and subsequently calculate the engineering parameters of the antenna surface based on the three-dimensional spatial positions of the key feature points. Through the embodiment of the present application, auxiliary points can be marked on the antenna surface, and the auxiliary points can be used to assist in the detection of key feature points on the antenna surface, thereby avoiding interference from irrelevant points in a complex background and improving the accuracy of antenna surface detection.

[0028] Technical terms involved in the embodiments of this application:

[0029] Hough space: The term Hough space comes from the Hough line detection algorithm. The Hough line detection algorithm is an edge detection algorithm based on parameter space, which is often used to extract straight line features in images. The basic idea is to calculate the gradient and direction of each point in the image to obtain the parameter space expression of the straight line, and convert it into the polar angle and polar diameter coordinates of the straight line in the polar coordinate system, and then store the polar angle and polar diameter values ​​of each pixel point in the two-dimensional Hough space. In the Hough space, each straight line corresponds to a peak point, and these peak points will be regarded as models of the straight line. By setting a threshold to determine the peak point in the Hough space, the adjacent peak points are connected into a straight line, and finally the straight line feature in the image is obtained. In the present application scheme, the Hough line detection algorithm is improved, and the edge straight line of the antenna surface is detected in combination with the position of the auxiliary point, so as to avoid the interference of the complex background.

[0030] Mask: In computer vision, a mask is a binary image created by processing an image to extract the target area. The target pixel values ​​are set to 1, while the remaining pixels are set to 0. This binary image can be used for subsequent computer vision processing tasks, such as target recognition, target location, and shape detection. In this solution, the mask is an image obtained by processing the image of the antenna surface, setting the positive antenna surface to 1 and the non-positive antenna surface to 0, to facilitate the subsequent detection of key feature points on the antenna surface.

[0031] The present application takes into account the existing photo-based base station antenna surface detection methods currently available on the market. These methods primarily utilize drones to photograph the base station antenna surface, obtain photographs, then identify the antenna surface or its feature points in the photographs to obtain recognition results. Finally, engineering parameter measurements are performed based on the recognition results to obtain the engineering parameters of the antenna surface. However, this method's identification of the antenna surface or its feature points is easily affected by complex backgrounds, resulting in low antenna surface detection accuracy.

[0032] Therefore, the embodiment of the present application proposes a solution that can mark auxiliary points on the antenna surface, and use the auxiliary points to assist in the detection of line segments on the antenna surface, thereby avoiding the interference of irrelevant line segments in a complex background, and further improving the accuracy of antenna surface detection.

[0033] Referring to Figure 1, Figure 1 is a schematic diagram of the functional modules of the device to which the base station antenna surface detection device of the present application belongs. The base station antenna surface detection device can be a device independent of the device and capable of data processing, and can be hosted on the device in the form of hardware or software. The device can be a smart mobile terminal with data processing capabilities, such as a mobile phone or tablet computer, or a fixed device or server with data processing capabilities.

[0034] In this embodiment, the equipment to which the base station antenna surface detection device belongs includes at least an output module 110 , a processor 120 , a memory 130 and a communication module 140 .

[0035] The memory 130 stores an operating system and a base station antenna surface detection program. The output module 110 may be a display screen, etc. The communication module 140 may include a WIFI module and a Bluetooth module, etc., and communicates with an external device or server through the communication module 140.

[0036] When the base station antenna surface detection program in the memory 130 is executed by the processor, the following steps are implemented:

[0037] Acquire an image of the base station antenna surface, wherein the image has auxiliary points marked therein;

[0038] Detecting key feature points of the antenna surface in the image based on the auxiliary points, and obtaining pixel positions of the key feature points;

[0039] The three-dimensional spatial position of the key feature point is obtained by solving the pixel position of the key feature point;

[0040] In one embodiment, when the base station antenna plane detection program in the memory 130 is executed by the processor, the following steps are further implemented:

[0041] The images of the antenna surface at different angles are acquired, and corresponding auxiliary points are marked and saved on the images according to a click instruction of a user near the center of the antenna surface.

[0042] In one embodiment, when the base station antenna plane detection program in the memory 130 is executed by the processor, the following steps are further implemented:

[0043] According to the pixel positions of the key feature points on the images at different angles, the corresponding shooting positions and inclinations of the cameras, and the intrinsic parameter matrix of the camera obtained by pre-calibrating the camera, the three-dimensional spatial positions of the key feature points are obtained by using a three-dimensional spatial positioning algorithm.

[0044] In one embodiment, when the base station antenna plane detection program in the memory 130 is executed by the processor, the following steps are further implemented:

[0045] determining at least two opposite boundaries of the antenna surface in the image based on the auxiliary points;

[0046] The pixel positions of the key feature points of the antenna surface are determined according to at least two opposite boundaries of the antenna surface.

[0047] In one embodiment, when the base station antenna plane detection program in the memory 130 is executed by the processor, the following steps are further implemented:

[0048] At least two opposite boundaries of the antenna surface are determined based on the auxiliary points and in combination with a predetermined reference interval length.

[0049] In one embodiment, when the base station antenna plane detection program in the memory 130 is executed by the processor, the following steps are further implemented:

[0050] Identifying one or more first-type auxiliary points corresponding to a click instruction of a user on the front surface of the antenna surface, and identifying one or more second-type auxiliary points corresponding to a click instruction of a user on the side surface of the antenna surface;

[0051] The step of determining at least two opposite boundaries of the antenna surface in the image based on the auxiliary points comprises:

[0052] At least two opposite boundaries of the antenna surface in the image are determined based on the first type of auxiliary points and the second type of auxiliary points.

[0053] In one embodiment, when the base station antenna plane detection program in the memory 130 is executed by the processor, the following steps are further implemented:

[0054] converting the image into a grayscale image;

[0055] The edges in the grayscale image are extracted using an edge detection algorithm, and the image after edge extraction is binarized to obtain a binarized image.

[0056] In one embodiment, when the base station antenna plane detection program in the memory 130 is executed by the processor, the following steps are further implemented:

[0057] The image is subjected to distortion correction using the distortion coefficient of the camera obtained by pre-calibrating the camera.

[0058] In one embodiment, when the base station antenna plane detection program in the memory 130 is executed by the processor, the following steps are further implemented:

[0059] Taking the auxiliary point as the center, determining the number of pixel points of the reference interval in the height and width directions of the image, and obtaining the length of a first reference interval in the height direction and the length of a second reference interval in the width direction;

[0060] Determine a first reference interval based on the auxiliary point and in combination with the length of the first reference interval, and determine a second reference interval based on the auxiliary point and in combination with the length of the second reference interval;

[0061] Performing pixel traversal observation and spatial projection on the binary image of the image within the first reference interval to determine a left boundary or a right boundary of the antenna surface in the image;

[0062] In the second reference interval, pixel traversal observation and spatial projection are performed on the binary image of the image based on the auxiliary points and in combination with the length of the second reference interval to determine the upper boundary or the lower boundary of the antenna surface in the image.

[0063] In one embodiment, when the base station antenna plane detection program in the memory 130 is executed by the processor, the following steps are further implemented:

[0064] Taking the auxiliary point as the center, determining the number of pixel points in a reference interval in the height direction of the image to obtain a third reference interval length in the height direction;

[0065] The step of determining at least two opposite boundaries of the antenna surface based on the auxiliary points and in combination with a predetermined reference interval length includes:

[0066] determining a third reference interval based on the auxiliary point and in combination with the length of the third reference interval;

[0067] In the third reference interval, pixel point traversal observation and spatial projection are performed on the binary image of the image to determine the left boundary or the right boundary of the antenna surface in the image.

[0068] In one embodiment, when the base station antenna plane detection program in the memory 130 is executed by the processor, the following steps are further implemented:

[0069] Based on the first type of auxiliary points and the second type of auxiliary points, and using an AI algorithm to extract the antenna surface area from the image, a mask of the antenna surface is obtained;

[0070] At least two opposing boundaries of the antenna face in the image are determined based on the mask.

[0071] In one embodiment, when the base station antenna plane detection program in the memory 130 is executed by the processor, the following steps are further implemented:

[0072] The engineering parameters of the antenna surface are calculated according to the three-dimensional spatial positions of the key feature points.

[0073] This embodiment, through the above-mentioned scheme, specifically obtains an image of the base station antenna surface, wherein auxiliary points are marked in the image; detects key feature points of the antenna surface in the image based on the auxiliary points, and obtains the pixel positions of the key feature points; and calculates the three-dimensional spatial positions of the key feature points based on the pixel positions of the key feature points. Through the scheme of the embodiment of the present application, auxiliary points can be marked on the antenna surface, and the auxiliary points can be used to assist in the detection of key feature points on the antenna surface, thereby avoiding interference from irrelevant points in a complex background and improving the accuracy of antenna surface detection.

[0074] Based on the above device architecture but not limited to the above architecture, an embodiment of the method of the present application is proposed.

[0075] The execution subject of the method of this embodiment may be a base station antenna surface detection device.

[0076] 2, which is a flow chart of a first embodiment of a method for detecting a base station antenna surface. The method comprises:

[0077] Step S10: Acquire an image of the base station antenna surface, wherein auxiliary points are marked in the image.

[0078] The solution of this embodiment can be applied to scenarios of planning, designing, constructing, optimizing and maintaining wireless communication networks, and can also be applied to scenarios of engineering parameter measurement, data collection and analysis of communication base stations. This embodiment takes the scenario of engineering parameter measurement of communication base stations as an example.

[0079] Among them, images of the base station antenna surface can be obtained from various channels.

[0080] As an implementation method, for example, a picture of the base station antenna surface can be pre-taken and stored in a library. From this library, the picture of the antenna surface can be obtained to obtain an image of the antenna surface. The library can be a camera library or a library of another storage device. Alternatively, a previously taken picture of the antenna surface can be downloaded from an external website or server to obtain an image of the antenna surface. The image of the antenna surface can be an image of the antenna surface area identified from the picture of the antenna surface.

[0081] As another implementation, the image of the base station antenna surface may be captured in real time according to a user's shooting instruction.

[0082] As an implementation manner, images of the antenna surface at different angles may be acquired, and each image at a different angle corresponds to a record of a shooting position and an inclination angle of a camera that shoots the image.

[0083] To obtain an image of the base station antenna surface, a device with a camera or a device capable of carrying a camera, which can also have positioning and tilt recording capabilities, can be used. For example, the device can be a smartphone or a drone.

[0084] When capturing images, the camera can be controlled to move, and the camera can be moved to capture the base station antenna surface from two or more different angles, and then multiple images of the base station antenna surface can be obtained from the camera.

[0085] In this embodiment, auxiliary points are marked in the image of the antenna surface, and the auxiliary points are used to detect key feature points of the antenna surface in the image.

[0086] The auxiliary points can be marked on the image in real time after the user obtains the image of the antenna surface, or can be marked on the image in advance before obtaining the image of the antenna surface.

[0087] As an implementation manner, the auxiliary point may be located near the center of the antenna surface.

[0088] The vicinity of the center of the antenna surface may be at the center of the antenna surface, or at a position deviated from the center of the antenna surface by a certain range, such as within the antenna surface area and at a certain distance from the edge of the antenna surface, for example, above, below, to the left, or to the right of the center of the antenna surface.

[0089] As an implementation method, after photographing the base station antenna surface using a camera, multiple images of the base station antenna surface may be operated on the camera to mark auxiliary points.

[0090] In addition, as an implementation method, a base station antenna surface detection device can be used to obtain multiple base station antenna surface images from a camera, and the multiple base station antenna surface images can be operated in the base station antenna surface detection device to identify auxiliary points.

[0091] As an implementation manner, when operating the image of the base station antenna surface, the user may mark auxiliary points on the acquired image of the base station antenna surface by clicking.

[0092] As an implementation manner, corresponding auxiliary points may be identified and saved on the image according to a click instruction by the user near the center of the antenna surface.

[0093] As a specific implementation method, the following solution can also be adopted:

[0094] In response to a shooting instruction for the base station antenna surface, the camera is controlled to shoot the front of the antenna surface from different angles to obtain images of the antenna surface at different angles. Each image at a different angle corresponds to the camera's shooting position and tilt angle. In each shot, the corresponding auxiliary point is identified and saved based on the user's click instruction near the center of the antenna surface. The camera's shooting position refers to the position of the camera in three-dimensional space during the shooting process, which can be expressed in the form of (longitude, latitude, altitude) or in the ECEF coordinate system in the form of (X, Y, Z).

[0095] The camera's tilt angle refers to the azimuth, horizontal, and downtilt angles of the camera lens. In drones, these three angles are usually expressed as pitch, yaw, and roll.

[0096] Step S20: detecting key feature points of the antenna surface in the image based on the auxiliary points, and obtaining pixel positions of the key feature points.

[0097] In one embodiment, at least two opposite boundaries of the antenna surface in the image may be determined based on the auxiliary points.

[0098] For example, for a rectangular antenna surface, the upper, lower, left, and right boundaries of the antenna surface can be determined; for an arc-shaped antenna surface with a raised arch in the middle, for example, when the upper and lower sides of the antenna surface are arcs and the left and right sides are straight lines, the left and right boundaries of the antenna surface can be determined.

[0099] Then, pixel positions of key feature points of the antenna surface are determined according to at least two opposite boundaries of the antenna surface.

[0100] The key feature points of the antenna surface can be determined by the intersection of the boundaries or by the pixel change threshold.

[0101] As an implementation mode, taking an example where an antenna surface has four sides, the intersection points formed by adjacent sides of the antenna surface are used as key feature points of the antenna surface.

[0102] The pixel position of the key feature point refers to the position of the key feature point in the image in the image coordinate system.

[0103] The key feature points of the antenna surface in the image are detected based on the auxiliary points. After the pixel positions of the key feature points are obtained, the three-dimensional spatial positions of the key feature points can be obtained through the pixel positions of the key feature points.

[0104] The method of this embodiment can not only detect the key feature points of the base station antenna surface, but also detect the key feature points of similar blocks to obtain the pixel positions of the key feature points of the similar blocks.

[0105] Step S30 , obtaining the three-dimensional spatial position of the key feature point according to the pixel position of the key feature point.

[0106] After obtaining multiple base station antenna surface images at different angles, auxiliary points are marked for each base station antenna surface image, and key feature points of the antenna surface in each image are detected based on the auxiliary points in each image, and the pixel positions of the key feature points in each image are obtained.

[0107] Because the three-dimensional spatial positions of the key feature points of the antenna surface in multiple images are the same, but the pixel positions are different, the three-dimensional spatial positions of the key feature points of the antenna surface can be calculated based on the different pixel positions of the key feature points of the antenna surface in multiple images.

[0108] As an implementation method, the following solution may be adopted:

[0109] The three-dimensional spatial position of the key feature points is calculated using a three-dimensional spatial positioning algorithm based on the pixel positions of the key feature points on the images at different angles, the corresponding shooting positions and inclinations of the cameras, and the intrinsic parameter matrix of the camera obtained by pre-calibrating the camera.

[0110] Taking the i-th photo as an example, the following equation (1) can be listed: M i =I·R i (1)

[0111] Among them, I is the intrinsic parameter matrix of the camera obtained by pre-calibrating the camera, R i is the external parameter matrix of the camera corresponding to the photo, including translation and rotation, that is, the camera's own position and inclination, M i The matrix constructed from the camera's intrinsic and extrinsic parameter matrices.

[0112] In this embodiment, let M i Set it as the matrix shown in (2), that is:

[0113] The position of a key feature point on the i-th photo is set to (u i ,v i ), then the three-dimensional spatial position (x, y, z) of the key feature point satisfies equation (3):

[0114] For multiple photos, a linear equation system can be constructed based on equation (3), and the linear equation system can be solved by the least squares method to obtain the three-dimensional spatial position (x, y, z) of the key feature point.

[0115] This embodiment uses the above-mentioned scheme to obtain an image of the base station antenna surface, in which auxiliary points are marked; based on the auxiliary points, key feature points of the antenna surface in the image are detected to obtain the pixel positions of the key feature points; and the three-dimensional spatial positions of the key feature points are calculated based on the pixel positions of the key feature points. Through the embodiment scheme of the present application, auxiliary points can be identified on the antenna surface, and the auxiliary points can be used to assist in the detection of key feature points on the antenna surface, thereby avoiding the interference of irrelevant feature points in a complex background, thereby improving the accuracy of antenna surface detection. Auxiliary points are identified near the center of each antenna surface, and the boundary of the antenna surface is detected by the auxiliary points within the antenna surface, thereby avoiding the identification of irrelevant points outside the antenna surface, thereby improving the accuracy of antenna surface detection.

[0116] In one embodiment, the determining of at least two opposite boundaries of the antenna surface in the image based on the auxiliary points may include the following solutions:

[0117] At least two opposite boundaries of the antenna surface are determined based on the auxiliary points and in combination with a predetermined reference interval length.

[0118] As an implementation method, first, the number of pixel points of the reference interval in the height and / or width direction of the image is determined with the auxiliary point as the center, and the length of the reference interval in the height and / or width direction is obtained.

[0119] Then, a reference interval is determined based on the auxiliary points and in combination with a predetermined reference interval length. Within the reference interval, pixel point traversal observation and spatial projection are performed on the binary image of the image to determine the left and right boundaries or the upper and lower boundaries of the antenna surface in the image.

[0120] The above-mentioned determination of at least two relative boundaries of the antenna surface in the image based on the auxiliary points may adopt at least the following three schemes:

[0121] As a first solution, the step of determining at least two opposite boundaries of the antenna surface in the image based on the auxiliary points may include:

[0122] At least two opposite boundaries of the antenna surface are determined based on the auxiliary points and in combination with a predetermined reference interval length.

[0123] The reference interval length refers to an area of ​​a certain length considered in the height or width direction of the antenna surface image with the auxiliary point as the center in the antenna surface image.

[0124] The length of the reference interval may be an empirical value, for example, set according to the user's usage, or may be determined in real time when the picture is taken.

[0125] As an implementation method, the image may be processed before the boundary is determined.

[0126] The purpose of image processing is to eliminate noise in the image, enhance specific details or information of the image, reduce the amount of calculation, etc., so as to provide clearer and more reliable image data for subsequent operations.

[0127] Specific processing methods may include image distortion correction, image grayscale processing, image binarization processing, image processing using different filters, image edge detection, etc. In practical applications, one or more image processing methods may be selected as needed to process the image of the antenna surface.

[0128] Image distortion correction can remove image distortion caused by the physical structure of the camera and lens distortion, thereby providing reliable image data for subsequent image processing.

[0129] If the distortion of the captured image is relatively small, distortion correction can be omitted and grayscale processing can be performed directly, followed by edge extraction and binarization.

[0130] If the distortion of the captured image is relatively large, the image can be subjected to distortion correction, grayscale processing, edge extraction, and finally binarization.

[0131] As an implementation method, the following scheme may be used to process the image:

[0132] First, the image is subjected to distortion correction using the distortion coefficient of the camera obtained by pre-calibrating the camera.

[0133] Then, the distortion-corrected image is converted into a grayscale image;

[0134] The distortion-corrected image is a color image. Converting a color image to a grayscale image reduces the image data size without affecting the image structure, thereby increasing image processing speed. Furthermore, each pixel in a grayscale image contains only a single degree of brightness, making grayscale imaging relatively simple and allowing for better edge characterization in subsequent image processing.

[0135] Then, an edge detection algorithm is used to extract edges from the grayscale image, and the image after edge extraction is binarized to obtain a binarized image.

[0136] Edge detection is an important image processing technique that can extract contour information from an image. Specifically, you can select an appropriate edge detection algorithm to extract edges in a grayscale image, such as the Canny edge detection algorithm, the Sobel edge detection algorithm, the Laplacian edge detection algorithm, etc.

[0137] Then, the image obtained after edge detection is binarized to convert the pixels at the edge into black or white, making the edge clearer and more obvious, thereby facilitating the subsequent detection of the boundary position of the antenna surface in the image.

[0138] Then, at least two opposite boundaries of the antenna surface in the image can be determined based on the auxiliary points.

[0139] In the case where the shape of the antenna surface is rectangular, the following solution may be used to determine the four boundaries of the antenna surface in the image based on auxiliary points.

[0140] First, determine the length of the reference interval.

[0141] Taking the auxiliary point as the center, determining the number of pixel points of the reference interval in the height and width directions of the image, and obtaining the length of a first reference interval in the height direction and the length of a second reference interval in the width direction;

[0142] Then, determining a first reference interval based on the auxiliary point and in combination with the length of the first reference interval, and determining a second reference interval based on the auxiliary point and in combination with the length of the second reference interval;

[0143] The four boundaries of the antenna surface are determined based on the auxiliary point and in combination with the first reference interval length, the first reference interval, the second reference interval length, and the second reference interval.

[0144] Performing pixel traversal observation and spatial projection on the binary image of the image within the first reference interval to determine a left boundary or a right boundary of the antenna surface in the image;

[0145] In the second reference interval, pixel traversal observation and spatial projection are performed on the binary image of the image based on the auxiliary points and in combination with the length of the second reference interval to determine the upper boundary or the lower boundary of the antenna surface in the image.

[0146] As an implementation manner, the spatial projection may specifically be Hough spatial projection.

[0147] A pixel point traversal observation and Hough space projection may be performed based on the auxiliary point and in combination with the first reference interval length to determine a left boundary or a right boundary of the antenna surface in the image;

[0148] 3 , which is a schematic diagram of pixel point traversal observation and spatial projection based on the auxiliary points and in combination with the first reference interval length in an embodiment of the base station antenna surface detection method of the present application.

[0149] As an embodiment, the first reference interval length is used in the height direction of the binary image to traverse and observe to the left or right of the binary image, and the observed pixel points of the binary image are projected into the Hough space;

[0150] When it is detected that the point value in the Hough space is greater than a first preset threshold, the current pixel position is determined to be the left boundary or the right boundary of the antenna surface.

[0151] An appropriate first preset threshold value may be determined based on experience or experiments, and the first preset threshold value may be adjusted based on specific circumstances.

[0152] Similarly, pixel point traversal observation and Hough space projection are performed based on the auxiliary points and in combination with the length of the second reference interval to determine the upper boundary or the lower boundary of the antenna surface in the image.

[0153] 4 , which is a schematic diagram of pixel point traversal observation and Hough space projection based on the auxiliary points and in combination with the second reference interval length in an embodiment of the base station antenna surface detection method of the present application.

[0154] As an embodiment, the second reference interval length is used in the width direction of the binary image to traverse and observe toward the upper side or the lower side of the binary image, and the observed pixel points of the binary image are projected into the Hough space;

[0155] When it is detected that the point value in the Hough space is greater than a first preset threshold, the straight line corresponding to the pixel position of the point with the maximum current value is determined to be the upper boundary or the lower boundary of the antenna surface. Then, based on the positions of the straight lines of the left boundary, right boundary, upper boundary, and lower boundary, four corner points of the antenna surface, i.e., the intersection points of the straight lines of the four boundaries, can be determined. The four corner points are used as key feature points to obtain the pixel positions of the key feature points.

[0156] In a second solution, when the shape of the antenna surface is rectangular or arc-shaped, the following solution may be used to determine two opposite boundaries of the antenna surface in the binary image based on auxiliary points.

[0157] The image processing process may refer to the first solution mentioned above.

[0158] First, determine the length of the reference interval.

[0159] Taking the auxiliary point as the center, the number of pixel points of the reference interval in the height direction of the image is determined to obtain the length of the third reference interval in the height direction.

[0160] Then, a third reference interval is determined based on the auxiliary point and in combination with the length of the third reference interval; within the third reference interval, pixel point traversal observation and spatial projection are performed on the binary image of the image to determine the left boundary or the right boundary of the antenna surface in the image.

[0161] Using the third reference interval length in the height direction of the image, traversing and observing to the left or right of the binary image, and projecting the observed pixel points of the binary image into the Hough space;

[0162] When it is detected that the point value in the Hough space is greater than a second preset threshold, the current pixel position is determined to be the left boundary or the right boundary of the antenna surface.

[0163] An appropriate second preset threshold value may be determined based on experience or experiments, and the second preset threshold value may be adjusted according to specific circumstances.

[0164] Then, the four corner points of the antenna surface may be determined according to the straight line positions of the left boundary and the right boundary, and the four corner points may be used as key feature points to obtain the pixel positions of the key feature points.

[0165] The following scheme can be used to determine the four corner points:

[0166] Searching in both the upward and downward directions along the left boundary of the antenna surface, and detecting changes in pixels within a reference interval to the right of the left boundary during the search process;

[0167] When a change in the pixel points within the right reference interval of the left boundary is greater than a third preset threshold, determining the current pixel position as a corner point position, and obtaining the corner point positions in the upper and lower directions of the left boundary;

[0168] An appropriate third preset threshold value may be determined based on experience or experiments, and the third preset threshold value may be adjusted based on specific circumstances.

[0169] Searching in both the upward and downward directions along the right boundary of the antenna surface, and detecting changes in pixels within a reference interval to the left of the right boundary during the search process;

[0170] When a change in the pixel points within the left reference interval of the right boundary is greater than a third preset threshold, determining the current pixel position as a corner point position, and obtaining the corner point positions in the upper and lower directions of the right boundary;

[0171] The upper and lower corner positions of the left boundary and the right boundary are used as the pixel positions of the key feature points.

[0172] It can be seen from this that the key feature points of the antenna surface can be determined by the intersection of the boundaries (such as the first solution mentioned above) or by the pixel point change threshold (such as the second solution mentioned above).

[0173] The third option:

[0174] In each shot, one or more first-category auxiliary points are identified according to a user's click instruction on the front of the antenna surface, and one or more second-category auxiliary points are identified according to a user's click instruction on the side of the antenna surface;

[0175] Based on this, the step of determining at least two opposite boundaries of the antenna surface in the image based on the auxiliary points may include:

[0176] At least two opposite boundaries of the antenna surface in the image are determined based on the first type of auxiliary points and the second type of auxiliary points.

[0177] As an embodiment, the step of determining at least two relative boundaries of the antenna surface in the image based on the first type of auxiliary points and the second type of auxiliary points may include:

[0178] Based on the first type of auxiliary points and the second type of auxiliary points, and using an AI algorithm to extract the antenna surface area from the image, a mask of the antenna surface is obtained;

[0179] At least two opposing boundaries of the antenna face in the image are determined based on the mask.

[0180] The specific implementation process is as follows:

[0181] First, perform distortion correction on the image. For images with significant distortion, distortion correction can be performed. For images with minimal distortion, distortion correction can be omitted and the following mask extraction can be performed directly.

[0182] Then, based on the auxiliary points, the antenna surface area is extracted from the image through an AI algorithm to obtain a mask of the antenna surface.

[0183] The mask refers to an image obtained by processing the image of the antenna surface and distinguishing the pixel values ​​on the front of the antenna surface and the pixel values ​​outside the front of the antenna surface as 1 and 0, so as to facilitate the subsequent detection of key feature points of the antenna.

[0184] Since the first and second auxiliary points identify the front face of the antenna surface and the area outside the front face of the antenna surface, respectively, the antenna surface area and the area outside the antenna surface in the distortion-corrected image can be distinguished based on the first and second auxiliary points and the AI ​​algorithm to obtain the mask of the antenna surface.

[0185] Then, searching for left edge points corresponding to different heights in the mask;

[0186] As an implementation method, if the pixel value of the front side of the antenna surface in the image is 1, each row of pixels in the mask is scanned from left to right, and the first pixel point in each row with a pixel value of 1 is used as the left edge point of the row.

[0187] Then, a straight line fitting is performed on the left edge points to obtain the left boundary of the antenna surface.

[0188] Linear fitting is a method of representing discrete data points with a straight line. Its essence is to calculate these discrete data points using the least squares method so that the sum of the distances from these discrete data points to the fitted line is minimized, thereby obtaining the most suitable fitted line to describe these discrete data points.

[0189] As an implementation manner, before performing straight line fitting on the left edge points to obtain the left boundary of the antenna surface, outlier filtering may be performed on the left edge points.

[0190] Points with a large position deviation from most of the left edge points can be regarded as outliers and filtered out.

[0191] Similarly, the right boundary of the antenna surface is obtained.

[0192] Then, based on the left boundary and the right boundary, the upper and lower corner positions of the left boundary and the right boundary can be determined as the pixel positions of the key feature points.

[0193] This embodiment, through the above-described scheme, specifically obtains an image of the base station antenna surface, wherein auxiliary points are marked in the image; detects key feature points of the antenna surface in the image based on the auxiliary points, and obtains the pixel positions of the key feature points; and calculates the three-dimensional spatial positions of the key feature points based on the pixel positions of the key feature points. The image can be converted into a grayscale image; an edge detection algorithm is used to extract edges from the grayscale image, and the image after edge extraction is binarized to obtain a binarized image. Then, based on the auxiliary points and in combination with a predetermined reference interval length, at least two opposing boundaries of the antenna surface are determined. Furthermore, with the auxiliary point as the center, the number of pixel points in the reference interval in the height and width directions of the image is determined to obtain the first reference interval length in the height direction and the second reference interval length in the width direction; the first reference interval is determined based on the auxiliary point and in combination with the first reference interval length, and the second reference interval is determined based on the auxiliary point and in combination with the second reference interval length; within the first reference interval, the binary image of the image is subjected to pixel traversal observation and spatial projection to determine the left or right boundary of the antenna surface in the image; the upper or lower boundary of the antenna surface in the image is determined by pixel traversal observation and spatial projection based on the auxiliary point and in combination with the second reference interval length. In addition, in each shot, the corresponding first type of auxiliary point can be identified based on the user's click instruction on the front of the antenna surface, and the corresponding second type of auxiliary point can be identified based on the user's click instruction on the side of the antenna surface; at least two relative boundaries of the antenna surface in the image are determined based on the first type of auxiliary point and the second type of auxiliary point. Furthermore, based on the first type of auxiliary points and the second type of auxiliary points, the antenna surface area is extracted from the image through an AI algorithm to obtain a mask of the antenna surface; and based on the mask, at least two relative boundaries of the antenna surface in the image are determined.

[0194] Through the embodiments of the present application, auxiliary points can be identified on the antenna surface to assist in detecting the antenna surface boundary, thereby avoiding interference from irrelevant points in a complex background and improving the accuracy of antenna surface detection. Distortion correction of the image can remove image distortion caused by the camera's physical structure and lens distortion, thereby providing reliable image data for subsequent image processing. Converting the distortion-corrected image to a grayscale image can reduce the amount of image data without affecting the image structure, thereby increasing image processing speed. Grayscale images are relatively simple to create and can better reflect edge features in subsequent image processing. Binarization of the image after edge detection can convert edge pixels to black or white, making the edge clearer and more distinct, thereby facilitating subsequent detection of the antenna surface boundary in the image. Furthermore, the pixels of the binarized image are projected into Hough space. When the point value in the Hough space is detected to be greater than a preset threshold, the current pixel position is determined to be the antenna surface boundary. Analysis of the Hough space allows for rapid detection of the antenna surface boundary in the image, thereby increasing the speed of antenna surface detection. In addition, the first type of auxiliary points are located on the front of the antenna surface. These first types of auxiliary points help the AI ​​algorithm determine the position of the antenna surface in the image. The second type of auxiliary points are located outside the front of the antenna surface, such as on the side or in the background. These second types of auxiliary points help the AI ​​algorithm better segment and extract the antenna surface, thereby improving the accuracy and reliability of the mask. Then, based on the left and right edge points corresponding to different heights in the mask, outliers are filtered out and straight line fitting is performed, which can further improve the detection accuracy of the antenna surface boundary and provide reliable data for subsequent analysis.

[0195] This embodiment is based on the first embodiment. In the above step S10, an image of the base station antenna surface is acquired. Before the auxiliary point is marked in the image, the following steps may be further included:

[0196] Calibrate a camera that captures an image of the base station antenna surface to obtain an intrinsic parameter matrix and distortion coefficients of the camera.

[0197] A camera calibration algorithm, such as the Zhang Zhengyou calibration method, may be used to calibrate the intrinsic parameter matrix and distortion coefficients of a camera that captures the image of the base station antenna surface.

[0198] The internal parameter matrix can be expressed as the following matrix (4):

[0199] The intrinsic parameter matrix depends on the internal parameters of the camera. Here, f is the image distance, dX and dY represent the physical length of a pixel on the camera plate in the X and Y directions, respectively, i.e., the length of a pixel on the plate in millimeters, u0 and v0 represent the coordinates of the center of the camera plate in the pixel coordinate system, and θ represents the angle between the horizontal and vertical edges of the plate.

[0200] In addition, the camera radial distortion model (2nd order) is as follows:

[0201] Among them, (x, y) is the ideal normalized image coordinate without distortion, is the normalized image coordinate after distortion, r is the distance from the image pixel to the image center, that is, r 2 =x 2 +y 2 .

[0202] Where k1 and k2 are the distortion coefficients.

[0203] This embodiment, through the above-described scheme, obtains an image of the base station antenna surface, with auxiliary points marked in the image; detects key feature points of the antenna surface in the image based on the auxiliary points, and obtains the pixel positions of the key feature points; and calculates the three-dimensional spatial positions of the key feature points based on the pixel positions of the key feature points. Furthermore, the camera used to capture the image of the base station antenna surface is calibrated to obtain the camera's intrinsic parameter matrix and distortion coefficients.

[0204] Through the embodiment of the present application, auxiliary points can be identified on the antenna surface, and the auxiliary points can be used to assist in the detection of line segments on the antenna surface, thereby avoiding the interference of irrelevant line segments in a complex background and improving the accuracy of antenna surface detection.

[0205] 5 , FIG5 is a flow chart of a fourth embodiment of the base station antenna surface detection method of the present application. This embodiment is based on the first embodiment, and in the above step S30, after the three-dimensional spatial position of the key feature point is obtained by solving the pixel position of the key feature point, the following steps may be included:

[0206] Step S40: Calculate the engineering parameters of the antenna surface according to the three-dimensional spatial positions of the key feature points.

[0207] The engineering parameters may include the three-dimensional spatial position of the antenna surface, the azimuth angle and downtilt angle of the antenna surface, etc.

[0208] The four key feature points define a plane. The normal vector to the plane on which the antenna surface lies can be calculated from the three-dimensional spatial positions of the four key feature points. The downtilt and azimuth angles of the antenna surface can then be calculated from the normal vector to the plane on which the antenna surface lies. The normal vector to the plane on which the antenna surface lies can be obtained by taking the outer product of two vectors formed by any three key feature points.

[0209] In addition, the three-dimensional spatial position of the center point of the plane where the antenna surface is located, that is, the center position of the four key feature points, can be calculated through the three-dimensional spatial positions of the four key feature points.

[0210] Then, the three-dimensional spatial position of the antenna surface can be obtained through the three-dimensional spatial position of the key feature point, the inclination angle of the antenna surface and the three-dimensional spatial position of the center point of the plane where the antenna surface is located.

[0211] This embodiment, through the above-mentioned solution, specifically obtains an image of the base station antenna surface, wherein auxiliary points are marked in the image; detects key feature points of the antenna surface in the image based on the auxiliary points, and obtains the pixel positions of the key feature points; and calculates the three-dimensional spatial positions of the key feature points based on the pixel positions of the key feature points. Furthermore, based on the three-dimensional spatial positions of the key feature points, engineering parameters such as the three-dimensional spatial position of the antenna surface, the azimuth angle, and the downtilt angle of the antenna surface can be calculated.

[0212] Through the embodiments of the present application, auxiliary points can be identified on the antenna surface, which can be used to assist in the detection of line segments on the antenna surface, thereby avoiding interference from irrelevant line segments in complex backgrounds and improving the accuracy of antenna surface detection. In addition, the embodiments of the present application calculate the engineering parameters of the antenna surface based on the three-dimensional spatial positions of the key feature points, and can detect and calibrate the antenna surface based on the engineering parameters of the antenna surface.

[0213] The detailed process of performing real-time base station antenna surface detection in the embodiment of the present application can be shown in FIG6 , and specifically includes:

[0214] Step S1001: camera calibration.

[0215] Using a chessboard with known length and width, use a camera to shoot the chessboard from different angles, and calculate the camera's distortion coefficient and intrinsic parameter matrix.

[0216] Step S1002, acquiring an image.

[0217] Photograph the antenna surface from two or more different angles, and select one or more auxiliary points for each picture during the shooting process.

[0218] Step S1003: key point detection.

[0219] Among them, the key points are the key feature points in the above embodiments.

[0220] With the help of auxiliary points, locate the four corner points of the antenna surface on the image. The four corner points of the antenna surface are the key points.

[0221] Step S1004: three-dimensional solution of key point space.

[0222] The three-dimensional spatial position of the key points is calculated based on the pixel positions of the corner points on different images, the corresponding camera position and inclination, and the intrinsic parameter matrix.

[0223] Step S1005: Calculate engineering parameters.

[0224] The engineering parameters are calculated based on the three-dimensional spatial position of the key points to obtain the three-dimensional spatial position of the antenna surface, the azimuth angle and the downtilt angle of the antenna surface.

[0225] This embodiment uses the above-mentioned solution to illustrate the process of real-time base station antenna surface inspection. Using only a mobile phone or drone, antenna surface inspection and calculation of engineering parameters are simple and cost-effective. The use of auxiliary points mitigates the impact of complex backgrounds on visual inspection of the antenna surface, improving inspection accuracy.

[0226] In addition, an embodiment of the present application further provides a base station antenna surface detection device, the base station antenna surface detection device comprising:

[0227] An image acquisition module, configured to, in response to a shooting instruction for a base station antenna surface, shoot an image of the antenna surface and mark auxiliary points on the image;

[0228] a feature point detection module, configured to detect key feature points of the antenna surface in the image based on the auxiliary points, and obtain pixel positions of the key feature points;

[0229] The three-dimensional space solving module is used to solve the three-dimensional space position of the key feature point according to the pixel position of the key feature point.

[0230] In one embodiment, a parameter calculation module may be further included to calculate the engineering parameters of the antenna surface based on the three-dimensional spatial positions of the key feature points. The principle and implementation process of implementing base station antenna surface detection in this embodiment can be referred to the above embodiments and will not be repeated here.

[0231] In addition, an embodiment of the present application also proposes a terminal device, which includes a memory, a processor, and a base station antenna surface detection program stored on the memory and runnable on the processor. When the base station antenna surface detection program is executed by the processor, the steps of the base station antenna surface detection method described above are implemented.

[0232] Since the base station antenna surface detection program adopts all the technical solutions of all the aforementioned embodiments when executed by the processor, it has at least all the beneficial effects brought by all the technical solutions of all the aforementioned embodiments, which will not be described one by one here.

[0233] In addition, an embodiment of the present application further proposes a computer-readable storage medium, on which a base station antenna surface detection program is stored. When the base station antenna surface detection program is executed by a processor, the steps of the base station antenna surface detection method described above are implemented.

[0234] Since the base station antenna surface detection program adopts all the technical solutions of all the aforementioned embodiments when executed by the processor, it has at least all the beneficial effects brought by all the technical solutions of all the aforementioned embodiments, which will not be described one by one here.

[0235] This embodiment, through the above-mentioned scheme, specifically obtains an image of the base station antenna surface, wherein auxiliary points are marked in the image; detects key feature points of the antenna surface in the image based on the auxiliary points, and obtains the pixel positions of the key feature points; and calculates the three-dimensional spatial positions of the key feature points based on the pixel positions of the key feature points. Through the scheme of the embodiment of the present application, auxiliary points can be marked on the antenna surface, and the auxiliary points can be used to assist in the detection of line segments on the antenna surface, thereby avoiding interference from irrelevant line segments in complex backgrounds and improving the accuracy of antenna surface detection.

[0236] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or method that includes a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or method. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, article, or method that includes the element.

[0237] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0238] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as mentioned above, and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, controlled terminal, or network device, etc.) to execute the method of each embodiment of the present application.

[0239] The above are merely optional embodiments of the present application and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A base station antenna surface detection method, wherein: The method comprises the following steps: Acquire an image of the base station antenna surface, wherein the image has auxiliary points marked therein; Detect key feature points of the antenna surface in the image based on the auxiliary points, and obtain pixel positions of the key feature points; The three-dimensional spatial position of the key feature point is calculated according to the pixel position of the key feature point.

2. The method according to claim 1, wherein: The auxiliary point is located near the center of the antenna surface.

3. The method according to claim 2, wherein: The step of obtaining an image of the base station antenna surface, wherein the image has auxiliary points marked therein, comprises: The images of the antenna surface at different angles are obtained, and corresponding auxiliary points are marked and saved on the images according to a click instruction of a user near the center of the antenna surface.

4. The method according to claim 1, wherein: The step of calculating the three-dimensional spatial position of the key feature point according to the pixel position of the key feature point comprises: The three-dimensional spatial position of the key feature point is calculated using a three-dimensional spatial positioning algorithm according to the pixel position of the key feature point on the image at different angles, the corresponding shooting position and inclination of the camera, and the intrinsic parameter matrix of the camera obtained by pre-calibrating the camera.

5. The method according to claim 1, wherein: The step of detecting the key feature points of the antenna surface in the image based on the auxiliary points and obtaining the pixel positions of the key feature points comprises: determining at least two opposite boundaries of the antenna surface in the image based on the auxiliary points; The pixel positions of the key feature points of the antenna surface are determined according to at least two opposite boundaries of the antenna surface.

6. The method according to claim 5, wherein: The step of determining at least two opposite boundaries of the antenna surface in the image based on the auxiliary points comprises: At least two opposite boundaries of the antenna surface are determined based on the auxiliary points and in combination with a predetermined reference interval length.

7. The method according to claim 5, wherein: The step of acquiring an image of the base station antenna surface, wherein the image has auxiliary points marked therein, further comprises: According to a click instruction of a user on the front side of the antenna surface, one or more corresponding first-type auxiliary points are identified, and according to a click instruction of a user on the side side of the antenna surface, one or more corresponding second-type auxiliary points are identified; The step of determining at least two relative boundaries of the antenna surface in the image based on the auxiliary points comprises: At least two opposite boundaries of the antenna surface in the image are determined based on the first type of auxiliary points and the second type of auxiliary points.

8. The method according to claim 6, wherein: Before the step of determining at least two relative boundaries of the antenna surface in the image based on the auxiliary points, the method further includes: Taking the auxiliary point as the center, determining the number of pixel points of the reference interval in the height and / or width direction of the image, and obtaining the length of the reference interval in the height and / or width direction; The step of determining at least two opposite boundaries of the antenna surface based on the auxiliary points and in combination with a predetermined reference interval length comprises: Determine a reference interval based on the auxiliary point and in combination with the length of the reference interval; In the reference interval, pixel point traversal observation and spatial projection are performed on the binary image of the image to determine the left and right boundaries or the upper and lower boundaries of the antenna surface in the image.

9. The method according to claim 7, wherein: The step of determining at least two relative boundaries of the antenna surface in the image based on the first type of auxiliary points and the second type of auxiliary points comprises: Based on the first type of auxiliary points and the second type of auxiliary points, and by using an AI algorithm, an antenna surface area is extracted from the image to obtain a mask of the antenna surface; At least two opposing boundaries of the antenna face in the image are determined based on the mask.

10. The method according to any one of claims 1 to 9, wherein: The method further comprises: The engineering parameters of the antenna surface are calculated according to the three-dimensional spatial positions of the key feature points.

11. A terminal device, wherein: The terminal device includes a memory, a processor, and a base station antenna surface detection program stored in the memory and executable on the processor. When the base station antenna surface detection program is executed by the processor, the steps of the base station antenna surface detection method as described in any one of claims 1 to 9 are implemented.

12. A computer-readable storage medium, wherein: The computer-readable storage medium stores a base station antenna surface detection program, and when the base station antenna surface detection program is executed by the processor, the steps of the base station antenna surface detection method according to any one of claims 1 to 9 are implemented.

Images