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Textured image segmentation using multiresolution Markov random fields and a two-component texture model

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Li, Chang-Tsun and Wilson, Roland (1997) Textured image segmentation using multiresolution Markov random fields and a two-component texture model. University of Warwick. Department of Computer Science. (Department of Computer Science research report). (Unpublished)

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Abstract

In this paper we propose a multiresolution Markov Random Field (MMRF) model for segmenting textured images. The Multiresolution Fourier Transform (MFT) is used to provide a set of spatially localised texture descriptors, which are based on a two-component model of texture, in which one component is a deformation, representing the structural or deterministic elements and the other is a stochastic one. Stochastic relaxation labelling is adopted to maximise the likelihood and assign the class label with highest probability to the block (site) being visited. Class information is propagated from low spatial resolution to high spatial resolution, via appropriate modifications to the interaction energies defining the field, to minimise class-position uncertainty. Experiments on the segmentation of natural textures are used to show the potential of the method.

Item Type: Report
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH): Markov random fields, Image segmentation, Texture mapping
Series Name: Department of Computer Science research report
Publisher: University of Warwick. Department of Computer Science
Official Date: March 1997
Dates:
DateEvent
March 1997Completion
Number: Number 321
Number of Pages: 10
DOI: CS-RR-321
Institution: University of Warwick
Theses Department: Department of Computer Science
Status: Not Peer Reviewed
Publication Status: Unpublished
Publisher Statement: C.-T.&nbsp;Li and R.G.&nbsp;Wilson, &ldquo;Textured Image Segmentation Using Multiresolution Markov Random Fields and a Two-component Texture Model&rdquo;, <i>Proceedings of SCIA-10</i>, Lappenranta (1997)
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