An Effective Method for Eye Detection Based on Texture Information

Abstract

In this paper, we present a novel method for eye detection based on texture information, referred to as the eye filter. The proposed method is composed of the following four steps: automatic extraction of facial regions using AdaBoost, illumination normalization using local information, estimation of eye candidates by the eye filter based on texture information, and detection of eye locations using geometrical information of face. Experimental results show that the eye detection rate of the proposed method is 99.2% for 3137 face images in the CAS-PEAL database and JAFFE database.