| Paper: | IMDSP-P11.3 | ||
| Session: | Image Segmentation | ||
| Time: | Thursday, May 18, 14:00 - 16:00 | ||
| Presentation: | Poster | ||
| Topic: | Image and Multidimensional Signal Processing: Image Segmentation | ||
| Title: | Contextual Estimation of Hidden Markov Chains with Application to Image Segmentation | ||
| Authors: | Stephane Derrode, EGIM / Institut Fresnel, France; Lamia Benyoussef, GRIFT Lab. Cristal, Tunisia; Wojciech Pieczynski, UMR 5157, France | ||
| Abstract: | This paper presents a contextual algorithm for the computation of Baum's forward and backward probabilities, which are extensively used in the framework of Hidden Markov Chain (HMC) models. The method differs from the original algorithm since it only takes into account a neighborhood of limited length and not all the chain for computations. Comparative experiments have been conducted on both Markovian and not Markovian data, by mean of supervised and unsupervised classifications. Numerical results with respect to the neighborhood size confirm the validity of the method. | ||
©2018 Conference Management Services, Inc. -||- email: webmaster@icassp2006.org -||- Last updated Friday, August 17, 2012