Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/70152
Title: Face recognition based on binary template matching
Authors: Song, J
Chen, B
Chi, Z 
Qiu, X
Wang, W
Issue Date: 2007
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2007, v. 4681, p. 1131-1139
Abstract: In this paper, a novel face recognition method based on binary face edges is presented to deal with the illumination problem. The Binary Face Edge Map (BFEM) is extracted using the Locally Adaptive Threshold (LAT) algorithm. Based on BEFM, a new image similarity metric is proposed. Experimental results show that face recognition rates of 76.32% and 82.67% are achieved respectively on 798 AR images and 150 Yale images with changed lighting conditions and facial expression variations when one sample per subject is used as the target image. The proposed method takes less time for image matching and outperforms some existing face recognition approaches, especially in changed lighting conditions.
Keywords: Face recognition
Binary template matching
Binary edge map
Illumination
Publisher: Springer
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
ISBN: 978-3-540-74170-1
978-3-540-74171-8
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-540-74171-8_115
Description: Third International Conference on Intelligent Computing (ICIC'2007), Qingdao, China, August 21-24, 2007
Appears in Collections:Conference Paper

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