Share Email Print

Proceedings Paper

Robust face recognition using gradient map and Hausdorff distance measure
Author(s): Jing Chi; DuanSheng Chen
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

A gradient-based face recognition method using Partial Hausdorff Distance (PHD) measure is proposed in this paper. First, in order to achieve a performance independent of lighting conditions, the image is transformed into a Gradient Map (GM). And then, Hausdorff distance measure is introduced to calculate the dissimilarity between two Gradient Maps. The experimental data show that the measure is suitable for face recognition. As we can see later, this distance measure is robust to lighting variations, slight pose differences and expression changes in face images. At last, recognition accuracy is given tested on AR and FERET databases, and comparisons with Edge Map (EM) and Line segment Edge Map (LEM) approaches are also presented.

Paper Details

Date Published: 15 November 2007
PDF: 9 pages
Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67882J (15 November 2007); doi: 10.1117/12.753405
Show Author Affiliations
Jing Chi, HuaQiao Univ. (China)
DuanSheng Chen, HuaQiao Univ. (China)

Published in SPIE Proceedings Vol. 6788:
MIPPR 2007: Pattern Recognition and Computer Vision
S. J. Maybank; Mingyue Ding; F. Wahl; Yaoting Zhu, Editor(s)

© SPIE. Terms of Use
Back to Top