Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/24058
Title: A robust eye detection method using combined binary edge and intensity information
Authors: Song, J
Chi, Z 
Liu, J
Keywords: Binary edge images
Eye detection
Light dots
Multi-level eye detection
Multi-resolution face image analysis
Issue Date: 2006
Publisher: Elsevier
Source: Pattern recognition, 2006, v. 39, no. 6, p. 1110-1125 How to cite?
Journal: Pattern recognition 
Abstract: In this paper, a new eye detection method is presented. The method consists of three steps: (1) extraction of binary edge images (BEIs) from the grayscale face image based on multi-resolution wavelet transform, (2) extraction of eye regions and segments from BEIs and (3) eye localization based on light dots and intensity information. In the paper, an improved face region extraction algorithm and a light dots detection algorithm are proposed for better eye detection performance. Also a multi-level eye detection scheme is adopted. Experimental results show that a correct eye detection rate of 98.7% can be achieved on 150 Bern images with variations in views and gaze directions and 96.6% can be achieved on 564 AR images with different facial expressions and lighting conditions.
URI: http://hdl.handle.net/10397/24058
ISSN: 0031-3203
EISSN: 1873-5142
DOI: 10.1016/j.patcog.2005.11.015
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