Referenced Items are not available for this document.
This paper addresses the problem of using noncausal hidden Markov models (HMMs) for texture classification. In noncausal models, the state of each pixel may be dependent on its neighbors in all directions. New algorithms are given to learn the parameters of a noncausal HMM of a texture and to classify it into one of several learned categories. Texture classification results using these algorithms are provided
Published in:
Pattern Analysis and Machine Intelligence, IEEE Transactions on
(Volume:17
,
Issue:
10
)
Date of Publication: Oct 1995
- Page(s):
- 1010 - 1014
- ISSN :
- 0162-8828
- INSPEC Accession Number:
- 5076484
- Digital Object Identifier :
- 10.1109/34.464564
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Oct 1995
- Sponsored by :
- IEEE Computer Society
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