Human face recognition using a spatially weighted Hausdorff distance

Baofeng Guo; Kin Man Lam; Wan Chi Siu; Shuyuan Yang

doi:10.1109/ISCAS.2001.921027

Human face recognition using a spatially weighted Hausdorff distance

Baofeng Guo, Kin Man Lam, Wan Chi Siu, Shuyuan Yang

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

13 Citations (Scopus)

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.

Original language	English
Title of host publication	ISCAS 2001 - 2001 IEEE International Symposium on Circuits and Systems, Conference Proceedings
Pages	145-148
Number of pages	4
Volume	2
DOIs	https://doi.org/10.1109/ISCAS.2001.921027
Publication status	Published - 1 Dec 2001
Event	2001 IEEE International Symposium on Circuits and Systems, ISCAS 2001 - Sydney, NSW, Australia Duration: 6 May 2001 → 9 May 2001

Conference

Conference	2001 IEEE International Symposium on Circuits and Systems, ISCAS 2001
Country/Territory	Australia
City	Sydney, NSW
Period	6/05/01 → 9/05/01

ASJC Scopus subject areas

Hardware and Architecture
Electrical and Electronic Engineering
Electronic, Optical and Magnetic Materials

More information

10.1109/ISCAS.2001.921027

Cite this

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title = "Human face recognition using a spatially weighted Hausdorff distance",

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.",

author = "Baofeng Guo and Lam, {Kin Man} and Siu, {Wan Chi} and Shuyuan Yang",

year = "2001",

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doi = "10.1109/ISCAS.2001.921027",

language = "English",

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note = "2001 IEEE International Symposium on Circuits and Systems, ISCAS 2001 ; Conference date: 06-05-2001 Through 09-05-2001",

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Guo, B, Lam, KM, Siu, WC & Yang, S 2001, Human face recognition using a spatially weighted Hausdorff distance. in ISCAS 2001 - 2001 IEEE International Symposium on Circuits and Systems, Conference Proceedings. vol. 2, 921027, pp. 145-148, 2001 IEEE International Symposium on Circuits and Systems, ISCAS 2001, Sydney, NSW, Australia, 6/05/01. https://doi.org/10.1109/ISCAS.2001.921027

Human face recognition using a spatially weighted Hausdorff distance. / Guo, Baofeng; Lam, Kin Man; Siu, Wan Chi et al.
ISCAS 2001 - 2001 IEEE International Symposium on Circuits and Systems, Conference Proceedings. Vol. 2 2001. p. 145-148 921027.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Human face recognition using a spatially weighted Hausdorff distance

AU - Guo, Baofeng

AU - Lam, Kin Man

AU - Siu, Wan Chi

AU - Yang, Shuyuan

PY - 2001/12/1

Y1 - 2001/12/1

N2 - 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.

AB - 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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SN - 9780780366855

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SP - 145

EP - 148

BT - ISCAS 2001 - 2001 IEEE International Symposium on Circuits and Systems, Conference Proceedings

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ER -

Human face recognition using a spatially weighted Hausdorff distance

Abstract

Conference

ASJC Scopus subject areas

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