S. Singh et al. (Eds.): ICAPR 2005, LNCS 3687, pp. 302 – 308, 2005. © Springer-Verlag Berlin Heidelberg 2005 A Robust and Efficient Algorithm for Eye Detection on Gray Intensity Face Kun Peng 1 , Liming Chen 1 , Su Ruan 2 , and Georgy Kukharev 3 1 Laboratoire d'InfoRmatique en Images et Systems d'information (LIRIS), Département MI, Ecole centrale de Lyon, BP 163, 36 avenue Guy de Collongue, 69131 Ecully Cedex, France {Kun.Peng, Liming.Chen}@ec-lyon.fr 2 Equipe Image, CReSTIC, Département GE&II, IUT de Troyes, 9 rue de Quebec, 10026 Troyes, France s.ruan@iut-troyes.univ-reims.fr 3 Faculty of Computer Science and Information Technology, Technical University of Szczecin, Zolnierska 49, 71-210 Szczecin, Poland pmasicz@wi.ps.pl Abstract. This paper presents a robust and efficient eye detection algorithm for gray intensity images. The idea of our method is to combine the respective advantages of two existing techniques, feature based method and template based method, and to overcome their shortcomings. Firstly, after the location of face region is detected, a feature based method will be used to detect two rough regions of both eyes on the face. Then an accurate detection of iris centers will be continued by applying a template based method in these two rough regions. Results of experiments to the faces without spectacles show that the proposed approach is not only robust but also quite efficient. 1 Introduction As one of the salient features of the human face, human eyes play an important role in face recognition. In fact, the eyes can be considered salient and relatively stable fea- ture on the face in comparison with other facial features. Therefore, when we detect facial features, it is advantageous to detect eyes before the detection of other facial features. The position of other facial features can be estimated using the eye position [1]. In addition, the size, the location and the image-plane rotation of face in the im- age can be normalized by only the position of both eyes. Eye detection is divided into eye position detection [1, 2] and eye contour detection [3, 15, 16]. (The second plays an important role in applications such as video confer- encing and vision assisted user interface [2]. However, most algorithms for eye con- tour detection, which use the deformable template proposed by Yuille et al. [3], re- quire the detection of eye positions to initialize eye templates. Thus, eye position detection is important not only for face recognition but also for eye contour detection. In this paper eye detection means eye position detection.