Computing Eigenface from edge images for face recognition based on Hausdorff distance

Huachun Tan*, Yu Jin Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Citations (Scopus)

Abstract

The different face regions have different degrees of importance for face recognition. In previous Hausdorff distance measures for face recognition, such as Spatially Eigen-Weighted Hausdorff distance (SEWHD) in which the weighting function is computed from grayscale images. However, Hausdorff distance is a measure for two binary point sets, not for grayscale point sets. Based on our previous work on Weighted Hausdorff distance (EFWHD) for face localization, a new weighting function of Hausdorff distance measure termed Edge Eigenface Weighted Hausdorff distance (EEWHD) is proposed for face recognition in this paper. The weighting function, which reflects the discriminative properties of face edge images effectively, is based on the eigenface of face edge images, not the eigenface of grayscale images in SEWHD, nor the edge points appearing frequency in EFWHD. The weighted Hausdorff distance Experimental results show the new method achieves higher recognition rate comparing with previous Hausdorff distance measures.

Original languageEnglish
Title of host publicationProceedings of the 4th International Conference on Image and Graphics, ICIG 2007
Pages639-644
Number of pages6
DOIs
Publication statusPublished - 2007
Event4th International Conference on Image and Graphics, ICIG 2007 - Chengdu, China
Duration: 22 Aug 200724 Aug 2007

Publication series

NameProceedings of the 4th International Conference on Image and Graphics, ICIG 2007

Conference

Conference4th International Conference on Image and Graphics, ICIG 2007
Country/TerritoryChina
CityChengdu
Period22/08/0724/08/07

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