Title: Method for accurately identifying local fuzzy features of sprinting video images
Authors: Zhiling Chen
Addresses: College of Physical Education, University of South China, Hengyang 421001, China
Abstract: In order to improve the recognition ability of sprinter video image features, a method of image local fuzzy feature recognition based on edge contour feature matching was designed. Based on the model of image visual feature sampling, the spatial block region planning is carried out. The attitude determination model of the local fuzzy region is established, and the local fuzzy features are extracted by combining template matching and wavelet multi-scale decomposition. Block recognition and information enhancement technology are used to enhance the fuzzy region information so as to extract the edge contour feature set of the fuzzy region and realise the accurate recognition of the local fuzzy features of the image. The simulation results show that this method can accurately identify the local fuzzy features of sprint video images, and the highest recognition accuracy can reach 95.7%.
Keywords: sprinting; video image; local fuzzy feature; accurate identification; edge contour detection.
International Journal of Biometrics, 2021 Vol.13 No.1, pp.30 - 39
Received: 02 Jan 2020
Accepted: 05 Mar 2020
Published online: 05 Jan 2021 *