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Pattern Recognition, International Conference on (2002)
Quebec City, QC, Canada
Aug. 11, 2002 to Aug. 15, 2002
ISSN: 1051-4651
ISBN: 0-7695-1695-X
pp: 10192
Li Cheng , University of Alberta
Terry Caelli , University of Alberta
Victor Ochoa , University of Alberta
In this paper we consider how to annotate or label regions of grey-level or multispectral images based upon known labels and a set of interacting hierarchical doubly stochastic processes. The proposed model extends current work on the use of hierarchical Markovian models for image processing using multiscale representations. In this paper we explore a new objective up-down algorithm whereby the spatio-spectral context of specific image region signatures are encoded via different types of trainable support kernels for the upward and downward Operations.
Hierarchical Markovian models, Image Annotation

V. Ochoa, T. Caelli and L. Cheng, "A Trainable Hierarchical Hidden Markov Tree Model for Color Image Annotation," Pattern Recognition, International Conference on(ICPR), Quebec City, QC, Canada, 2002, pp. 10192.
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