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CVPR
2008
IEEE

A Bayesian approach for image segmentation with shape priors

15 years 1 months ago
A Bayesian approach for image segmentation with shape priors
Color and texture have been widely used in image segmentation; however, their performance is often hindered by scene ambiguities, overlapping objects, or missing parts. In this paper, we propose an interactive image segmentation approach with shape prior models within a Bayesian framework. Interactive features, through mouse strokes, reduce ambiguities, and the incorporation of shape priors enhances quality of the segmentation where color and/or texture are not solely adequate. The novelties of our approach are in (i) formulating the segmentation problem in a well-defined Bayesian framework with multiple shape priors, (ii) efficiently estimating parameters of the Bayesian model, and (iii) multi-object segmentation through userspecified priors. We demonstrate the effectiveness of our method on a set of natural and synthetic images.
Hang Chang, Qing Yang, Bahram Parvin
Added 12 Oct 2009
Updated 12 Oct 2009
Type Conference
Year 2008
Where CVPR
Authors Hang Chang, Qing Yang, Bahram Parvin
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