Hidden Using Markov Models and Wavelets for face recognition
M. Bicego, U. Castellani, V. Murino
Dipartimento di Informatica, Universit` di Verona a Ca Vignal 2, Strada Le Grazie 15 37134 Verona, Italia bicego,castellani,murino @sci.univr.it
Abstract
In this paper, a new system for face recognition is proposed, based on Hidden Markov Models (HMMs) and wavelet coding. A sequence of overlapping sub-images is extracted from each face image, computing the wavelet coefcients for each of them. The whole sequence is then modelled by using Hidden Markov Models. The proposed method is compared with a DCT coefcients-based approach [9], showing comparable results. By using an accurate model selection procedure, we show that results proposed in [9] can be improved even more. The obtained results outperform all results presented in the literature on the Olivetti Research Laboratory (ORL) face database, reaching a recognition rate. These performances proves the suitability of HMMs to deal with the new JPEG2000 image compression standard.
1. Introduction
Face recognition is undoubtedly an interesting research area, growing in importance in recent years, due to its applicability as a biometric system in commercial and security applications. These systems could be used to prevent unauthorized access or fraudulent use of ATMs, cellular phones, smart cards, desktop PCs, workstations, and computer networks. The appealing characteristic of a face recognition system is that, differently from ngerprint or iris biometric systems, it represents a not invasive control tool. A large literature is available on this topic (for a review see [4]). The rst approaches, proposed in the 70s, were based on geometric features [8]. Subsequently, one of the well known face recognition algorithms is the so-called Eigenface method [22, 25], that uses the Principal Component Analysis to project faces into a low-dimensional space, where each face can be expressed as a linear combination of the eigenfaces. This method showed to be not very robust to variations of the face orientation, and one solution
to this problem was provided by the vie...
Bicego_ICIAP03