Tactical Analysis of Table Tennis Video Skills Based on Image Fuzzy Edge Recognition Algorithm

Abstract

To improve the effect of table tennis tactical analysis, this study proposed a table tennis video tactical analysis method based on image fuzzy edge recognition algorithm. This algorithm can effectively recognize edges in images to improve recognition accuracy and reduce errors and rejection rates. In addition, this research combines the methods of target tracking and trajectory estimation to build a table tennis video game tactical analysis platform. The experimental data show that the recognition accuracy of the proposed fuzzy edge recognition algorithm is 98.1%, and the error and rejection rates are less than 1.6%. Compared with the image edge detection algorithm based on interval value fuzzy, the proposed algorithm has better performance. When the positioning error is 10%, the precision of the table tennis target tracking algorithm can reach 94.3%, which is 9.3% higher than that of the direct linear transform algorithm. The table tennis video game tactical analysis platform can analyze the velocity of ping-pong ball according to the video, and records the droppoint of ping-pong ball, which helps the players to develop more effective tactics and strategies to improve their competitive level and achievements.

Keywords

• Image processing
• fuzzy edge recognition
• target tracking
• trajectory estimation
• ping-pong ball tactics