Eye-verifier using ternary template for reliable eye detection in facial color images

This paper introduces an eye-verifier for reliable detection of eyes in facial color images. At first, the eye region candidates are searched by the circular filter to the binary face image. The eye candidates are then fed into an eye-verifier. The eye-verifier uses a ternary template, generated from the eye area consisting of iris, sclera and skin. Then the template matching is made by ternary Hamming distance. Experimental results evaluating the proposed method on our own face database and FERET database show promising performance in terms of detection rate. The proposed algorithm showed a robust performance to the face poses and eye directions.