Abstract
Moving target detection is involved in many engineering applications, but basketball has some difficulties because of the time‐varying speed and uncertain path. The purpose of this paper is to use computer vision image analysis to identify the path and speed of a basketball goal, so as to meet the needs of recognition and achieve trajectory prediction. This research mainly discusses the basketball goal recognition method based on computer vision. In the research process, Kalman filter is used to improve the KCF tracking algorithm to track the basketball path. The algorithm of this research is based on MATLAB, so it can avoid the mixed programming of MATLAB and other languages and reduce the difficulty of interface design software. In the aspect of data acquisition, the extended EPROM is used to store user programs, and parallel interface chips (such as 8255A) can be configured in the system to output switch control signals and display and print operations. The automatic basketball bowling counter based on 8031 microprocessor is used as the host computer. After the level conversion by MAX232, it is connected with the RS232C serial port of PC, and the collected data is sent to the workstation recording the results. In order to consider the convenience of user operation, the GUI design of MATLAB is used to facilitate the exchange of information between users and computers so that users can see the competition results intuitively. The processing frame rate of the tested video image can reach 60 frames/second, more than 25 frames/second, which meet the real‐time requirements of the system. The results show that the basketball goal recognition method used in this study has strong anti‐interference ability and stable performance.
Highlights
From the early stage of vision to the final stage of classification and recognition, computer vision applications differ greatly in operation, data representation, and memory access patterns
The hardware system used for computer vision must provide a high degree of flexibility without compromising performance, make full use of spatially parallel operations, and must maintain high throughput on complex data-dependent program flows
In order to better solve the problems existing in the traditional fixed-point shooting device, such as easy damage, high replacement rate, high installation and production costs, and misjudgment, the use of image processing technology can solve the above problems [3, 4]
Summary
From the early stage of vision to the final stage of classification and recognition, computer vision applications differ greatly in operation, data representation, and memory access patterns. Image processing technology is a technology that uses a computer to process image information. It mainly includes image digitization, image enhancement and restoration, image data coding, image segmentation, and image recognition. With the rapid development of image processing technology, the detection technology of moving objects in video has been more and more widely used. With the rapid development of the times, more and more video processing applications are proposed [3]. In order to better solve the problems existing in the traditional fixed-point shooting device, such as easy damage, high replacement rate, high installation and production costs, and misjudgment, the use of image processing technology can solve the above problems [3, 4]
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