DocumentCode :
2250525
Title :
Image interpretation using hidden Markov models
Author :
Dugad, Rakesh ; Desai, U.B.
Author_Institution :
Coordinated Sci. Lab., Illinois Univ., Urbana, IL, USA
Volume :
3
fYear :
1997
fDate :
9-12 Sep 1997
Firstpage :
1532
Abstract :
Image interpretation involves giving meaning to an image by identifying significant objects in the image and also inferring their semantic relationship. In this correspondence we propose the use of hidden Markov models to construct the clique functions of the MRF model used for interpretation. We show how HMMs can be used to represent the features of the given image and also the domain knowledge
Keywords :
hidden Markov models; image representation; HMMs; MRF model; clique functions; domain knowledge; hidden Markov models; image feature representation; image interpretation; semantic relationship; significant objects; Bayesian methods; Hidden Markov models; Image segmentation; Labeling; Markov random fields; Multilayer perceptrons; Pixel; Probability distribution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information, Communications and Signal Processing, 1997. ICICS., Proceedings of 1997 International Conference on
Print_ISBN :
0-7803-3676-3
Type :
conf
DOI :
10.1109/ICICS.1997.652250
Filename :
652250
Link To Document :
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