Nowadays personal identification is a very important issue. There is a wide range of applications in different spheres, such as video surveillance security systems, control of documents, forensics systems and etc. We consider a range of most significant aspects of face identification system based on support vector machines in this paper. At first we propose improved face detector to get the region of interest for next face recognition. In paper the technique of face detection jointly image normalization is introduced. We compare three algorithms of feature extraction in application on face identification (PCA NIPALS, NNPCA, kernel PCA). The presented system is intended for process the image with low quality, the photo with the different facial expressions. Our goal is to develop face recognition techniques and create the system for face identification.

The development of automatic visual control system is a very important research topic in computer vision. This face identification system must be robust to the various quality of the images such as light, face expression, glasses, beards, moustaches etc. We propose using the wavelet transformation algorithms for reduction the source data space. We have realized the method of the expansion of the values of pixels to the whole intensity range and the algorithm of the equalization of histogram to adjust image intensity values. The support vector machines (SVM) technology has been used for the face recognition in our work.

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In this work we consider pyramidal decomposition algorithm for support vector machines classification problem. This algorithm is proposed to solve multi-class classification problem with use some binary SVM-classifiers for the strategy "one-against-one''.

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