Algorithm of Basketball Posture Motion Feature Extraction Based on Image Processing Technology

In the field of basketball, the existing training concept is based on the simulated observation and personal experience of the coaches, and it is subject to subjective judgment of inadequacies. Using image technology to train athletes is mainly to help coaches make decisions and improve the strength of athletes through the identification and recognition of athletes' states and transfer characteristics. The purpose of this paper is to study the basketball pose motion feature extraction algorithm based on image processing technology. This paper firstly builds the basketball posture model, introduces the feature extraction and selection in basketball posture, analyzes the application of image processing algorithm in basketball posture movement feature extraction, and mainly uses filtering algorithm to denoise the moving image. The algorithm in this paper mainly selects the normalized data processing algorithm to perform data induction processing on the feature data extracted in this paper. Experiments show that after image processing technology, the recognition rate of motion features by BP neural network is the highest, and the average recognition rate reaches 96%, which can effectively recognize the motion features of basketball posture.