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ICIP
2005
IEEE
15 years 11 months ago
Segmenting non stationary images with triplet Markov fields
The hidden Markov field (HMF) model has been used in many model-based solutions to image analysis problems, including that of image segmentation, and generally gives satisfying re...
Dalila Benboudjema, Wojciech Pieczynski
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ICIP
2002
IEEE
15 years 11 months ago
Robust video text segmentation and recognition with multiple hypotheses
A method for segmenting and recognizing text embedded in video and images is proposed in this paper. In the method, multiple segmentation of the same text region is performed, thu...
Jean-Marc Odobez, Datong Chen
ICIP
2003
IEEE
15 years 11 months ago
A probabilistic framework for image segmentation
A new probabilistic image segmentation model based on hypothesis testing and Gibbs Random Fields is introduced. First, a probabilistic difference measure derived from a set of hyp...
Slawo Wesolkowski, Paul W. Fieguth
ICIP
2009
IEEE
15 years 8 months ago
A Markov Random Field Model for Extracting Near-Circular Shapes
We propose a binary Markov Random Field (MRF) model that assigns high probability to regions in the image domain consisting of an unknown number of circles of a given radius. We...
Tamas Blaskovics, Zoltan Kato, and Ian Jermyn
ICPR
2008
IEEE
15 years 3 months ago
A probabilistic model for classifying segmented images
In this work we introduce a probabilistic model for classifying segmented images. The proposed classifier is very general and it can deal both with images that were segmented wit...
Liang Wu, Predrag Neskovic, Leon N. Cooper