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Knowledge-based eye detection for human face recognition

Human facial feature detection is a significant but difficult task. An algorithm of knowledge based eye detection is presented. The algorithm consists of two main stages: the face and eye region locating stage and the eye detection stage. In the first stage, an effective approach to fast location of the face and eye region is developed. In the second stage, eye edge contour searching directed by knowledge is introduced in detail. Regional image processing techniques are also described in the second stage. The main purpose of the first stage is to locate the eye region roughly. The algorithm employed in the second stage is restricted to application in just this region. It reduces the complexity of the first stage and improves the reliability in the second stage. The Yale Face Database is used to evaluate the capability of the proposed methods and the results are promising.