Face Recognition Based on Sub-image Feature Extraction and LS-SVM

Based on sub-image feature extraction method of face images and least square support vector machine (LS-SVM) classifier, a face recognition model is proposed. In this model, face images are divided into sub-images firstly, then the discrete cosine transform is operated on each sub-image and the optimal coefficients are selected to denote the sub-image, and combine them into a single feature vector of the whole face image, finally LS-SVM is employed as a classifier with its optimized parameters. On ORL face database, experimental results show the proposed method is effective and has fast recognition speed.