Recognition Method of Volleyball Players' Spike and Take-Off Action Based on DTW Algorithm

In order to improve the recognition ability of volleyball players' spike take-off, and thus promote the accuracy of volleyball spike, this article puts forward the recognition technology of volleyball players' spike take-off based on DTW algorithm combined with image recognition technology. The transmission relation model of detail features of volleyball players' spike take- off action images is constructed, and the edge contour features of volleyball players' spike take-off action images are detected and processed by detail wavelet feature decomposition and DWT algorithm. Using prior Atlas knowledge instead of dark primary color, the detailed information and color of the image are obtained. Through the method of filtering and maintaining, the image is guided to filter the details of the input volleyball player's spike and take-off action image. Sobel operator is used to detect the weak edge information of the animation image. In the edge area, high-order moment feature decomposition and wavelet feature separation are used to enhance the details of the volleyball player's spike and take-off action image and detect and enlarge the key action feature points, so as to improve the ability of enhancing and identifying the details of the action feature points of the image. The test shows that this method can effectively solve the noise and error in the process of recognizing the spike and take-off action of volleyball players, reduce the recognition error, and improve the ability to accurately locate the spike and take-off force point.