Detection of eyes by circular Hough transform and histogram of gradient

摘要

) space. The second step of the proposed method is evaluation of likelihood of eye using histogram of gradient and Support Vector Machine (SVM). The eye detection step of proposed method firstly detects possible eye center by the circular Hough transform. Then it extracts histogram of gradient from rectangular window centered at each eye center. Likelihood of eye of the extracted feature vector is evaluated by SVM, and pairs of eyes satisfying predefined conditions are generated and ordered by sum of the likelihood of both eyes. Evaluation experiment is conducted using 1,409 images of the FERET database of frontal face image. The experimental result shows that the proposed method achieves 98.65% detection rate of both eyes.