Abstract
In this paper, a novel method for automatic localization of human eyes from front-view face images is presented. By applying the grayscale morphology operation to a face image, we can obtain a valley map with a good property in which as a whole the number of pixels at a grayscale decreases significantly as the grayscale level increases. The valley map is then binarized with a set of threshold values determined adaptively, and several candidate eye locations are detected from the resultant binary images. The final eye positions are determined using a Principle Component Analysis (PCA) method. Experimental results on the AR, Yale and our own face image databases show that the correct eye location rate is over 93% and the location disparity on average is below 1/3 of the radius of an eye ball.
Original language | Chinese (Simplified) |
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Pages (from-to) | 540-545 |
Number of pages | 6 |
Journal | Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics |
Volume | 17 |
Issue number | 3 |
Publication status | Published - 1 Mar 2005 |
Keywords
- Eyes localization
- Face image processing
- Grayscale mathematical morphology
- Valley map
ASJC Scopus subject areas
- Software
- Computer Graphics and Computer-Aided Design