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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/15691

Title: Range Image Segmentation by Randomized Region Growing and Bayesian Edge Regularization
Authors: Smaine Mazouzi
Mohamed Batouche
Keywords: Image segmentation, range image, randomized region growing, bayesian estimation,markov random field
Issue Date: 2007
Publisher: Journal of Computer Science
Abstract: We presented and evaluated a new Bayesian method for range image segmentation. The method proceeds in to stages. First, an initial segmentation was produced by a randomized region growing technique. The produced segmentation was considered as a degraded version of the ideal segmentation, which should be then refined. In the second stage, image pixels not labeled in the first stage were labeled by using a Bayesian estimation, based on some prior assumptions on the regions in the image. Image priors were modeled by a new Markov Random Field (MRF) model. Contrary to most of the authors in range image segmentation, who use only surface smoothness MRF models, our MRF model takes into account also the smoothness of region boundaries. Tests performed with real images from the ABW database show the great potential of the proposed method for significantly improving the segmentation results.
URI: http://hdl.handle.net/123456789/15691
Appears in Collections:College of Computer and Information Sciences

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