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Method for accurately identifying local fuzzy features of sprinting video images

Method for accurately identifying local fuzzy features of sprinting video images 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%. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Biometrics Inderscience Publishers

Method for accurately identifying local fuzzy features of sprinting video images

International Journal of Biometrics , Volume 13 (1): 10 – Jan 1, 2021

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1755-8301
eISSN
1755-831X
DOI
10.1504/IJBM.2021.112213
Publisher site
See Article on Publisher Site

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%.

Journal

International Journal of BiometricsInderscience Publishers

Published: Jan 1, 2021

There are no references for this article.