Application of fast behavior detection based on image optical processing in basketball training image recognition

Basketball is a sport that is widely participated in all over the world. Accurately identifying the behavior in basketball training is beneficial to the improvement of athletes' skills and the evaluation of training effects. The traditional basketball behavior detection methods are usually limited by complex sports scenes and various actions, which leads to the inaccuracy and low efficiency of the recognition results. The aim of this study is to use image optical processing technology to propose a fast behavior detection method to realize the accurate recognition and analysis of basketball training images. Based on the image optical processing technology, the behavior detection is carried out by shooting the image of the basketball training scene, and then using the image processing algorithm to extract the key information and features. Then the deep learning algorithm is used to classify and identify the behaviors in order to realize the accurate detection of different basketball training behaviors. Finally, through experimental verification and performance evaluation, the fast behavior detection method based on image optical processing has achieved remarkable results in recognizing the behavior in basketball training images. Compared with traditional methods, the proposed method has better performance in terms of accuracy and response time.