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Proceedings Paper

Vehicle feature extraction by patch-based sampling
Author(s): William Wai Leung Lam; Clement Chun Cheong Pang; Nelson Hon Ching Yung
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Paper Abstract

In modern traffic surveillance, computer vision methods are often employed to detect vehicles of interest because of the rich information content contained in an image. In this paper, we propose an efficient method for extracting the boundary of vehicles free from their moving cast shadows and reflective regions. The extraction method is based on the hypothesis that regions of similar texture are less discriminative, disregarding intensity differences between the vehicle body and the cast shadow or reflection on the vehicle. In this novel algorithm, a united likelihood map that based on the relationship of texture, luminance and chrominance of each pixel is initially constructed. Subsequently, a foreground mask is constructed by applying morphological operations. Vehicles can be successfully extracted and different vehicle components can be efficiently distinguished by the related autocorrelation index within the vehicle mask.

Paper Details

Date Published: 7 May 2003
PDF: 12 pages
Proc. SPIE 5022, Image and Video Communications and Processing 2003, (7 May 2003); doi: 10.1117/12.476650
Show Author Affiliations
William Wai Leung Lam, Univ. of Hong Kong (China)
Clement Chun Cheong Pang, Univ. of Hong Kong (China)
Nelson Hon Ching Yung, Univ. of Hong Kong (China)

Published in SPIE Proceedings Vol. 5022:
Image and Video Communications and Processing 2003
Bhaskaran Vasudev; T. Russell Hsing; Andrew G. Tescher; Touradj Ebrahimi, Editor(s)

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