Design and Image Research of Tennis Line Examination Based on Machine Vision Analysis
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 regi...
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2021-01-01
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Series: | Computational Intelligence and Neuroscience |
Online Access: | http://dx.doi.org/10.1155/2021/2436120 |
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doaj-411dbc4f778e444e9393293ba306424b2021-10-04T01:57:29ZengHindawi LimitedComputational Intelligence and Neuroscience1687-52732021-01-01202110.1155/2021/2436120Design and Image Research of Tennis Line Examination Based on Machine Vision AnalysisLiu Yan0Sun Xin1College of Sports ScienceHarbin Finance UniversityIn 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.http://dx.doi.org/10.1155/2021/2436120 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Liu Yan Sun Xin |
spellingShingle |
Liu Yan Sun Xin Design and Image Research of Tennis Line Examination Based on Machine Vision Analysis Computational Intelligence and Neuroscience |
author_facet |
Liu Yan Sun Xin |
author_sort |
Liu Yan |
title |
Design and Image Research of Tennis Line Examination Based on Machine Vision Analysis |
title_short |
Design and Image Research of Tennis Line Examination Based on Machine Vision Analysis |
title_full |
Design and Image Research of Tennis Line Examination Based on Machine Vision Analysis |
title_fullStr |
Design and Image Research of Tennis Line Examination Based on Machine Vision Analysis |
title_full_unstemmed |
Design and Image Research of Tennis Line Examination Based on Machine Vision Analysis |
title_sort |
design and image research of tennis line examination based on machine vision analysis |
publisher |
Hindawi Limited |
series |
Computational Intelligence and Neuroscience |
issn |
1687-5273 |
publishDate |
2021-01-01 |
description |
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. |
url |
http://dx.doi.org/10.1155/2021/2436120 |
work_keys_str_mv |
AT liuyan designandimageresearchoftennislineexaminationbasedonmachinevisionanalysis AT sunxin designandimageresearchoftennislineexaminationbasedonmachinevisionanalysis |
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1716844726997483520 |