Contour extraction of gait recognition based on improved GVF Snake model

Authors:
Fan Zhang;Xinhong Zhang;Kui Cao;Rui Li
Affiliations:
Institute of Image Processing and Pattern Recognition, Henan University, Kaifeng 475001, China and College of Computer and Information Engineering, Henan University, Kaifeng 475001, China;Computing Center, Henan University, Kaifeng 475001, China;College of Computer and Information Engineering, Henan University, Kaifeng 475001, China;College of Computer and Information Engineering, Henan University, Kaifeng 475001, China
Venue:
Computers and Electrical Engineering
Year:
2012

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Abstract

Contourlet transform can be used to captures smooth contours and edges at any orientation. In order to solve the initial active contour problem of Snake model, Contourlet transform is introduced into the GVF (Gradient Vector Flow) Snake model, which will provides a way to set the initial contour, as a result, will improves the edge detection results of GVF Snake model effectively. The multi-scale decomposition is handled by a Laplacian pyramid. The directional decomposition is handled by a directional filter bank. Firstly, the contours of the object in images can be obtained based on Contourlet transform, and this contours will be identified as the initial contour of GVF Snake model. Secondly, then GVF Snake model is used to detect the contour edge of human gait motion. Experimental results show that the proposed method can extract the edge feature accurately and efficiently.