Image verification using Gabor filter bank with Hidden markov model

Abstract: This dissertation relates to the design, implementation and evaluation of identification of Facial images. Face identification system is a mechanism of identifying various faces against some stored pattern faces. It takes input an image of a human being face and searches for a match in the stored face images. If there is match, the user can see the result as face identified or not identified. Outsider cannot generate any type of modification in the stored image records. The vendor of the system has authentication to renew the storage records.This system is based on Gabor features extraction using Gabor filter bank. Gabor-based face representation has achieved enormous success in face recognition. In particular, the use of HMM (Hidden Markov Models) in various forms is investigated as a recognition tool various for matching the input face image to the template images.Current face identification techniques are very dependent on issues like background noise, lighting and position of key features (i.e. eyes, lips etc). In this dissertation the system developed uses the hidden Markov model (HMM) in various forms is investigated as a recognition tool and critically evaluated

Keywords: HMM(Hidden Markov Model),DRT(Discrete Random Transform)