Research on fast recognition of athletes' abnormal mood based on improved MEDA algorithm Online publication date: Mon, 08-Jul-2024
by Pin Lv; Haixin Huang
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 16, No. 3, 2024
Abstract: In order to improve the accuracy and average recognition rate of athletes' abnormal emotions and reduce the recognition time, a fast recognition method of athletes' abnormal mood based on improved MEDA algorithm was proposed. Firstly, mathematical morphology is used to refine the edge of athlete's abnormal emotion image, and the edge isolated points in the image are removed. Secondly, the wolf colony algorithm is used to segment different regions of the image, and the rotation correction method is used to extract the region of interest of the image. Finally, the improved MEDA algorithm is used to effectively select the features of the region of interest of the image, and the abnormal emotion type is judged by combining the regional feature screening results. The experimental results show that the proposed method has obvious advantages in recognition accuracy, average recognition rate and recognition time, and the recognition effect are good.
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