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