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Joint segmentation and image interpretation using hidden Markov models

DSpace at IIT Bombay

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Title Joint segmentation and image interpretation using hidden Markov models
 
Creator KAMATH, N
SUNIL KUMAR, K
DESAI, UB
DUGUD, R
 
Subject computer vision
hidden markov models
image segmentation
knowledge representation
probability
 
Description Image interpretation consists of interleaving the low-level task of image segmentation and the high-level task of interpretation. The idea being that the interpretation block guides the segmentation block which in turn helps the interpretation block in better interpretation. In this paper we develop a joint segmentation and image interpretation scheme using the notion of joint hidden Markov model (HMM) for probabilistic modeling of spatial relationship. We find the optimal interpretation labels, which are nothing but the optimal state sequence of the HMM.
 
Publisher IEEE
 
Date 2008-12-09T06:23:53Z
2011-11-28T09:17:38Z
2011-12-15T09:58:03Z
2008-12-09T06:23:53Z
2011-11-28T09:17:38Z
2011-12-15T09:58:03Z
1998
 
Type Article
 
Identifier Proceedings of the Fourteenth International Conference on Pattern Recognition (V 2), Brisbane, Australia, 16-20 August 1998, 1840-1842
0-8186-8512-3
10.1109/ICPR.1998.712088
http://hdl.handle.net/10054/233
http://dspace.library.iitb.ac.in/xmlui/handle/10054/233
 
Language en