Abstract
In this paper, the sports image analysis system has been redesigned, the functions of each part have been strengthened, and the technologies such as visualization processing, large-capacity database and evaluation system, newly developed image acquisition and joint position extraction have been added. The successful development of this system will be of great benefit to sports technical action analysis. Aiming at the defects of rough image segmentation results and high spatial distortion rate in current sports video image segmentation methods, a sports video image segmentation method based on fuzzy clustering algorithm is proposed. The basic theory of fuzzy clustering algorithm is introduced. Second-order fuzzy attributes with normal distribution and gray value are established with the help of time-domain difference images, and then the time-domain difference images are fuzzy clustered, and then motion video image segmentation is obtained through edge detection. result. Experimental results prove that the method has high spatial accuracy, good noise iteration performance, low spatial distortion rate, and can accurately segment complex moving video images to obtain high-definition images.
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