Automatic human face recognition system using fractal dimension and modified Hausdorff distance1

Kwan Ho Lin; Baofeng Guo; Kin Man Lam; Wan Chi Siu

Automatic human face recognition system using fractal dimension and modified Hausdorff distance¹

Kwan Ho Lin, Baofeng Guo, Kin Man Lam, Wan Chi Siu

The Hong Kong Polytechnic University

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

Abstract

In this paper, an efficient automatic human face recognition system is proposed. Fractal dimension is an efficient representation of texture which is used to locate the eyes in a human face. We propose a modified approach to estimate the fractal dimensions which is less sensitive to lighting conditions and provides information about the orientation of an image under consideration. Based on the position of the eyes, two face images are normalized, aligned and then compared by a new modified Hausdorff distance measure. As different facial regions have different degrees of importance for face recognition, the modified Hausdorff distance is weighted according to a weighted function derived from the spatial information of the human face. Experimental results show that our approach can achieve recognition rates of 76%, 84%, and 92% for the first one, the first five, first ten likely matched faces, respectively. If the position of the eyes is selected manually, the corresponding recognition rates are 82%, 95% and 98%, respectively. The average processing time for detecting the eyes and recognize a human face is less than two seconds.

Original language	English
Title of host publication	Advances in Multimedia Information Processing - PCM 2001 - 2nd IEEE Pacific Rim Conference on Multimedia, Proceedings
Publisher	Springer Verlag
Pages	277-284
Number of pages	8
ISBN (Print)	3540426809, 9783540426806
Publication status	Published - 1 Jan 2001
Event	2nd IEEE Pacific-Rim Conference on Multimedia, IEEE-PCM 2001 - Beijing, China Duration: 24 Oct 2001 → 26 Oct 2001

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2195
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd IEEE Pacific-Rim Conference on Multimedia, IEEE-PCM 2001
Country/Territory	China
City	Beijing
Period	24/10/01 → 26/10/01

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Cite this

Lin, K. H., Guo, B., Lam, K. M., & Siu, W. C. (2001). Automatic human face recognition system using fractal dimension and modified Hausdorff distance¹. In Advances in Multimedia Information Processing - PCM 2001 - 2nd IEEE Pacific Rim Conference on Multimedia, Proceedings (pp. 277-284). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2195). Springer Verlag.

Lin, Kwan Ho ; Guo, Baofeng ; Lam, Kin Man et al. / Automatic human face recognition system using fractal dimension and modified Hausdorff distance¹. Advances in Multimedia Information Processing - PCM 2001 - 2nd IEEE Pacific Rim Conference on Multimedia, Proceedings. Springer Verlag, 2001. pp. 277-284 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "In this paper, an efficient automatic human face recognition system is proposed. Fractal dimension is an efficient representation of texture which is used to locate the eyes in a human face. We propose a modified approach to estimate the fractal dimensions which is less sensitive to lighting conditions and provides information about the orientation of an image under consideration. Based on the position of the eyes, two face images are normalized, aligned and then compared by a new modified Hausdorff distance measure. As different facial regions have different degrees of importance for face recognition, the modified Hausdorff distance is weighted according to a weighted function derived from the spatial information of the human face. Experimental results show that our approach can achieve recognition rates of 76%, 84%, and 92% for the first one, the first five, first ten likely matched faces, respectively. If the position of the eyes is selected manually, the corresponding recognition rates are 82%, 95% and 98%, respectively. The average processing time for detecting the eyes and recognize a human face is less than two seconds.",

author = "Lin, {Kwan Ho} and Baofeng Guo and Lam, {Kin Man} and Siu, {Wan Chi}",

year = "2001",

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Lin, KH, Guo, B, Lam, KM & Siu, WC 2001, Automatic human face recognition system using fractal dimension and modified Hausdorff distance¹. in Advances in Multimedia Information Processing - PCM 2001 - 2nd IEEE Pacific Rim Conference on Multimedia, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2195, Springer Verlag, pp. 277-284, 2nd IEEE Pacific-Rim Conference on Multimedia, IEEE-PCM 2001, Beijing, China, 24/10/01.

Automatic human face recognition system using fractal dimension and modified Hausdorff distance¹. / Lin, Kwan Ho; Guo, Baofeng; Lam, Kin Man et al.
Advances in Multimedia Information Processing - PCM 2001 - 2nd IEEE Pacific Rim Conference on Multimedia, Proceedings. Springer Verlag, 2001. p. 277-284 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2195).

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

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T1 - Automatic human face recognition system using fractal dimension and modified Hausdorff distance1

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Y1 - 2001/1/1

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AB - In this paper, an efficient automatic human face recognition system is proposed. Fractal dimension is an efficient representation of texture which is used to locate the eyes in a human face. We propose a modified approach to estimate the fractal dimensions which is less sensitive to lighting conditions and provides information about the orientation of an image under consideration. Based on the position of the eyes, two face images are normalized, aligned and then compared by a new modified Hausdorff distance measure. As different facial regions have different degrees of importance for face recognition, the modified Hausdorff distance is weighted according to a weighted function derived from the spatial information of the human face. Experimental results show that our approach can achieve recognition rates of 76%, 84%, and 92% for the first one, the first five, first ten likely matched faces, respectively. If the position of the eyes is selected manually, the corresponding recognition rates are 82%, 95% and 98%, respectively. The average processing time for detecting the eyes and recognize a human face is less than two seconds.

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Lin KH, Guo B, Lam KM, Siu WC. Automatic human face recognition system using fractal dimension and modified Hausdorff distance¹. In Advances in Multimedia Information Processing - PCM 2001 - 2nd IEEE Pacific Rim Conference on Multimedia, Proceedings. Springer Verlag. 2001. p. 277-284. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).