Design and Image Research of Tennis Line Examination Based on Machine Vision Analysis

Abstract

In view of the intelligent demand of tennis line examination, this paper performs a systematic analysis on the intelligent recognition of tennis line examination. Then, a tennis line recognition method based on machine vision is proposed. In this paper, the color region of the image recognition region is divided based on the region growth, and the rough estimation of the court boundary is realized. In order to achieve the effect of camera calibration, a fast camera calibration method which can be used for a variety of court types is proposed. On the basis of camera calibration, a tennis line examination and segmentation system based on machine vision analysis is constructed, and the experimental results are verified by design experiments. The results show that the machine vision analysis-based intelligent segmentation system of tennis line examination has high recognition accuracy and can meet the actual needs of tennis line examination.

exploratory investigation of traditional scoring in diving and relationships to the development of Artificial Intelligence opportunities

“…In attempts to minimise human error and provide greater transparency, some sports have already introduced video technology. Video Assistant Referee (VAR) was adopted by the International Football Association Board (IFAB) and is now used extensively via a variety of technological systems (IFAB, 2018), while tennis has the "Hawk-eye" line examination system (Hawk-Eye Innovations Ltd., Sony Business Europe, Basingstoke, England) to enhance and sometimes replace the line judges who use the naked eye (Spitz et al, 2021;Yan and Xin, 2021). In some cases, the main aim of introducing AI was not to limit human error, but to assist with score prediction in sports or injury risk assessment/prevention (Li and Xu, 2021;Claudino, et al, 2019).…”