Implement of face recognition system based on Hidden Markov Model

This paper achieves the face recognition systems based on Hidden Markov and the extraction of feature vectors which is based on PC. Hidden Markov Model is established according to the facial feature, and the image is preprocessed using the method of Wavelet Transform. After that, the original image is processed in overlap sampling and the method of multi-scale decomposition is applied to each sample block in the wavelet domain. Moreover, it gets dimensionality reduction by using PCA. Finally, the system traines Hidden Markov Model through taking advantage of the result of observation vector. In this way, the recognition rate of the target image will have a certain improvement.