Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/262
Title: Human face recognition using a spatially weighted Hausdorff distance
Authors: Guo, Baofeng
Lam, Kin-man Kenneth
Siu, Wan-chi
Yang, Shuyuan
Subjects: Face recognition
Hausdorff distance
Issue Date: 2001
Publisher: IEEE
Source: 2001 IEEE International Symposium on Circuits and Systems : ISCAS 2001 : conference proceedings : 6-9 May 2001, Sydney Convention and Exhibition Centre, Darling Harbour, Sydney, Australia, p. II145-II148
Abstract: The edge map of a facial image contains abundant information about its shape and structure, which is useful for face recognition. To compare edge images, Hausdroff distance is an efficient measure that can determine the degree of their resemblance, and does not require a knowledge of correspondence among those points in the two edge maps. In this paper, a new modified Hausdorff distance measure is proposed, which has a better noise immunity capability and better discriminant power. As the different facial regions have different relative importance for face recognition, the modified Hausdorff distance is weighted according to a weighted function derived from the spatial. information of the human face; hence crucial regions are emphasized for face identification. Experimental results show that the distance measure can achieve recognition rates of 82%, 93%, and 97% for the first, the first three, and the first five likely matched faces, respectively.
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Type: Conference Paper
URI: http://hdl.handle.net/10397/262
ISBN: 0780366859
Appears in Collections:EIE Conference Papers & Presentations

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