Face Recognition System Using PCA and DCT in HMM

Abstract: The speed of procedures became necessities during recent years; therefore using computers turn out to be the most important factors to increase the speed of implementation especially in security aspect such as recognition of people.There are a lot of waysto recognize the people face recognition is one of them. In this work the details of the face have been taken as blocks and Discrete Cosine Transform (DCT) is used, applied on face image’s blocks. Then without doing inverse DCT Principal Component Analysis (PCA) is applied directly for dimensionality reduction this makes the system very fast. Olivetti Research Laboratory (ORL) database of faces had been used to obtain the results.Each face is considered as a numerical sequence (blocks) that can be easily modelled by HMM. On 400 face images of the (ORL) face database the system has been examined. The experiments showed a recognition rate of 95.211%, using half of the images for training.

Keywords: Face Recognition, Hidden Markov Model, Discrete Cosine Transform (DCT), Principal Component Analysis (PCA).