Open AccessDesign of Intelligent Assistant System for Billiards Hit Training
Author(s) -
Zerui Zhang,
Wenhao Zhang,
Weizheng Chen
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1802/3/032117
Subject(s) - ball (mathematics) , dynamical billiards , artificial intelligence , hough transform , computer science , computer vision , segmentation , histogram , edge detection , image processing , mathematics , geometry , image (mathematics)
Image processing technology has increasing important applications in sports in recent years, such as result prediction, technical analysis, and foul determination. For most billiards beginners, how to hit the billiard ball into the ball belt is not a simple matter. In order to assist the beginners in billiards training, this article proposes an assisted hitting system. The system is divided into three parts: bag detection, billiard detection, and hitting suggestions. In the ball belt detection, double-peak histogram threshold segmentation, edge detection and Hough transform are used to detect the edge line, and then the ball belt position is detected. In billiard ball detection, the normalized RGB method is used to extract the foreground, the Hough transform circle detection method is used to detect the center and radius of the sphere, and the neural network is used to determine the white ball. In the shot suggestion, the force and angle of the shot are given by the dynamic formula, and the path simulation of the ball in the background is given. Experiments show that the recognition method is effective and the path simulation is consistent with reality, which can assist beginners in the training of billiards to a large extent.