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Volume: 4 | Article ID: art00100
Spectral Color Image Segmentation Using Hidden Markov Models
  DOI :  10.2352/CGIV.2008.4.1.art00100  Published OnlineJanuary 2008

In this paper, we propose an approach based on a hidden Markov model (HMM) which accounts for the structure of a spectrum for unsupervised image segmentation. We compute feature sequences representing spectra for training and testing the HMM. In our study, each HMM models one class of a spectral color image. The algorithm computes the model parameters and the discrimination information between the HMMs. The experiments show that the proposed approach gives promising results.

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V. Bochko, J. Parkkinen, M. Hauta-Kasari, T. Jaaskelainen, "Spectral Color Image Segmentation Using Hidden Markov Modelsin Proc. IS&T CGIV 2008/MCS'08 4th European Conf. on Colour in Graphics, Imaging, and Vision 10th Int'l Symp. on Multispectral Colour Science,  2008,  pp 467 - 470,

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