A non linear face recognition system using Support Vector Machine

A face recognition system uses face to verify individuals using computing capability. However, its performances often degrade due to high dimensional data and large feature appearance of the face image. This paper present a face recognition system based on non linear feature extraction technique to reduce the dimensionality of the face image, called Locally Linear Embedding. This method considers the hidden layer of face manifold to be the input of a SVM multiclass classifier. The performance is evaluated using the ORL database and achieved better recognition rates than the Principal Component Analysis.