In this paper, a new system for face recognition is proposed, based on hidden Markov models (HMM) and wavelet coding. A sequence of overlapping sub-images is extracted from each face image, computing the wavelet coefficients for each of them. The whole sequence is then modelled by using hidden Markov models. The proposed method is compared with a DCT coefficient-based approach (Kohir et al. (1998)), showing comparable results. By using an accurate model selection procedure, we show that results proposed in Kohir 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 100% recognition rate. This performance proves the suitability of HMM to deal with the new JPEG2000 image compression standard.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Using hidden Markov models and wavelets for face recognition


    Contributors:
    Bicego, M. (author) / Castellani, U. (author) / Murino, V. (author)


    Publication date :

    2003-01-01


    Size :

    410896 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Using Hidden Markov Models and Wavelets for Face Recognition

    Bicego, M. / Castellani, U. / Murino, V. et al. | British Library Conference Proceedings | 2003


    Video-Based Face Recognition Using Adaptive Hidden Markov Models

    Liu, X. / Chen, T. / IEEE | British Library Conference Proceedings | 2003


    Video-based face recognition using adaptive hidden Markov models

    Xiaoming Liu, / Tsuhan Cheng, | IEEE | 2003


    Vehicle Recognition Based on Gabor Wavelets Transform and Hidden Markov Model

    Deng, T.-m. / Shao, Y.-m. / Li, M. et al. | British Library Conference Proceedings | 2007


    Vehicle Recognition Based on Gabor Wavelets Transform and Hidden Markov Model

    Deng, Tian-min / Shao, Yi-ming / Li, Min et al. | ASCE | 2007