Face Detection Model Based on Distance Measure of Regional Feature

This paper proposes a new model for face detection based on statistics by applying the mosaic method. The model is insensitive to illumination and can adapt to the distortion and slope of face in some degree. Moreover there is an extra good feature of this model, i.e. attention focusing capability. Firstly a distance measure, that is MD (Mahalanobis Distance), is presented, which is suitable for vector clustering. Secondly the standard deviation of gradient norm and direction angle in each mosaic block are selected as the regional features in the model. The tested images are detected as human faces when both the MDs of gradient norm and direction angle to the collectivity of human faces are small. Eventually, abundant experiments have been made under different conditions and the results of the experiments have reached the expectations.