Joint segmentation and image interpretation using hidden Markov models
DSpace at IIT Bombay
View Archive InfoField | Value | |
Title |
Joint segmentation and image interpretation using hidden Markov models
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Creator |
KAMATH, N
SUNIL KUMAR, K DESAI, UB DUGUD, R |
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Subject |
computer vision
hidden markov models image segmentation knowledge representation probability |
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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.
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Publisher |
IEEE
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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 |
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Type |
Article
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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 |
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Language |
en
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