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Vol: 47(61) No: 1 / March 2002 Identity Confirmation System Based on CTAG and HMM Robert Stefan Gyorodi Department of Electronic and Computer Engineering, University of Limerick, National Technological Park, Limerick, Ireland, phone: +353 (0) 61 212-095, e-mail: Robert.Gyorodi@ul.ie, web: http://www.ece.ul.ie/robert Stefan Holban Computer Science and Engineering Department, Politehnica University of Timisoara, Bd. Vasile Parvan 2, 1900, Timisoara, Romania, phone: +40(0)56 204-333 ext, e-mail: stefan@cs.utt.ro, web: http://www.cs.utt.ro/~stefan Tom Coffey Department of Electronic and Computer Engineering, University of Limerick, National Technological Park, Limerick, Ireland, phone: +353 (0) 61 212-268, e-mail: Tom.Coffey@ul.ie, web: http://www.ece.ul.ie/ Cornelia Aurora Gyorodi Department of Computer Science, Faculty of Electrotehnics and Informatics, University of Oradea, Str. Armatei Romane 5, 3700, Oradea, Romania, phone: +40 (0) 59 432-830, e-mail: cgyorodi@univ.uoradea.ro Keywords: Face recognition, embedded HMM, CTAG, Identity Confirmation. Abstract Facial recognition from still images and video sequences is emerging as an active research area with numerous commercial and law enforcement applications. Hidden Markov Models (HMM) have been successfully used for speech and action recognition where the data that is to be modeled is one-dimensional. Although attempts to use these one-dimensional HMMs for face recognition have been moderately successful, images are two-dimensional (2-D) and consequently a two dimensional model should perform better. In this paper we present a new approach for face recognition using an embedded HMM and compare this approach to other HMM-based methods. References [1] O. Agazzi, S. Kuo, E. Levin şi R. Pieraccini – ”Connected and degraded text recognition using planar HMM”, International Conference on Acoustics, Speech and Signal Processing ’93, vol 5, pp. 113-116, 1993. [2] F. Samaria – ”Face segmentation for identification using hidden Markov models”, British Machine Vision Conference, 1993. [3] F. Samaria şi F. Fallside – ”Face identification and feature extraction using hidden Markov models”, Image Processing: Theory and Applications, 1993. [4] F. Samaria şi F. Fallside – ”Automated face identification using hidden Markov models”, Proceedings of the International Conference on Advanced Mechatronics, pp. 1-9, 1993. [5] F. Samaria şi A. Harter – ”Parametrisation of stohastic model for human face identification”, Proceedings of the Second IEEE Workshop on Application of Computer Vision, pp. 138-142, 1994. [6] F. Samaria – ”Face Recognition Using Hidden Markov Models”, PhD thesis, University of Cambridge, 1994. [7] A.V. Nefian, M.H. Hayes – ”Face Recognition Using an Embedded HMM”, Proceedings of the IEEE Conference on Audio and Video-based Biometric Person Authentication, pp. 19-24, Martie 1999. [8] A.V. Nefian – ”A Hidden Markov Model-Based Approach for Faces Detection and Recognition”, PhD thesis, Georgia Institute of Technology , 1999. [9] Robert Gyorodi, Dr. Mark H. Fisher, Juliana Camapum - “Multi-scale color texture description” - 12th International Conference on Systems Engineering, Vol1, Coventry University, 9-11 September 1997, UK, pp. 284-289. [10] Robert Gyorodi – “Contributions to Feature Selection in the Image Recognition and Interpretation Process”, PhD thesis, Politehnica University of Timisoara, Romania, 2001. [11] L. Rabiner – “A tutorial on Hidden Markov Models and selected applications in speech recognition”, Proceedings of IEEE, vol. 77, pp. 257-286, February 1989. |