An efficient eye location using context-aware binarization method

1Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Face recognition system needs the method of locating facial components like eyes, mouth, etc, for extracting features used in recognition process. In this paper we propose a method of locating eyes using context-aware binarization. The proposed method consists of binarization, connected region segmentation, eye candidate area extraction by heuristic rules that use geometric information, eye candidate pair detection, and eye area pair determining by ranking method. Binarization plays an important role in this system that converts a source image to a binary image suitable for locating eyes. We consider edge detection based and segmentation based binarization methods. However, each method cannot be a solution in general environment because these are influenced by the factors such as light direction, contrast, brightness, and spectral composition. We propose a hybrid binarization using the concept of illumination context-awareness that mixes two binarization methods in general environment. We apply this methodology to eye location, and we achieved encouraging experiment results in general environment. © Springer-Verlag Berlin Heidelberg 2005.

Cite

CITATION STYLE

APA

Jung, J. N., Nam, M. Y., & Rhee, P. K. (2005). An efficient eye location using context-aware binarization method. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3683 LNAI, pp. 662–669). Springer Verlag. https://doi.org/10.1007/11553939_95

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free