Face detection is important in the processing of images and video.Based on multilevel gradient energy (MGE)

an algorithm of face detection in DCT (Discrete Cosine Transform) compressed domain is presented.In preprocessing procedure

skin color segmentation based on the DC of chromatic components is applied to the input image for reducing the detected regions.According to the map of skin segmentation

MGE based feature vector is extracted

viz.normalized feature vectors are extracted from the detecting windows of various sizes to describe faces of different sizes.Then cascade classifier is employed to classify the feature vectors as face or non-face.Cascade classifier is comprised of several simple classifiers and a neural network classifier.Lots of feature vectors that belong to non-face are removed by simple classifiers which embedded preknowledge rules.The left vectors are classified by neural network.We combined MGE features together with image scaling to allow faces of various sizes.The simplicity of feature extraction accelerated detection by reducing the times of image scaling which is more time cost.The experiment results show that the proposed method is efficient and effective.