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|Title: ||Human face recognition using a spatially weighted Hausdorff distance|
|Authors: ||Guo, Baofeng|
Lam, Kin-man Kenneth
|Subjects: ||Face recognition|
|Issue Date: ||2001 |
|Citation: ||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.|
|Rights: ||© 2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
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|Type: ||Conference Paper|
|Appears in Collections:||EIE Conference Papers & Presentations|
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