@article{(Open Science Index):https://publications.waset.org/pdf/1939,
	  title     = {Unsupervised Segmentation by Hidden Markov Chain with Bi-dimensional Observed Process},
	  author    = {Abdelali Joumad and  Abdelaziz Nasroallah},
	  country	= {},
	  institution	= {},
	  abstract     = {In unsupervised segmentation context, we propose a bi-dimensional hidden Markov chain model (X,Y) that we adapt to the image segmentation problem. The bi-dimensional observed process Y = (Y 1, Y 2) is such that Y 1 represents the noisy image and Y 2 represents a noisy supplementary information on the image, for example a noisy proportion of pixels of the same type in a neighborhood of the current pixel. The proposed model can be seen as a competitive alternative to the Hilbert-Peano scan. We propose a bayesian algorithm to estimate parameters of the considered model. The performance of this algorithm is globally favorable, compared to the bi-dimensional EM algorithm through numerical and visual data.
},
	    journal   = {International Journal of Mathematical and Computational Sciences},
	  volume    = {5},
	  number    = {12},
	  year      = {2011},
	  pages     = {1992 - 2001},
	  ee        = {https://publications.waset.org/pdf/1939},
	  url   	= {https://publications.waset.org/vol/60},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 60, 2011},
	}