UNSPECIFIED (2001) Unsupervised image segmentation combining region and boundary. IMAGE AND VISION COMPUTING, 19 (6). pp. 353-368. ISSN 0262-8856

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Abstract

An integrated approach to image segmentation is presented that combines region and boundary information using maximum a posteriori estimation and decision theory. The algorithm employs iterative, decision-directed estimation performed on a novel multi-resolution representation. The use of a multi-resolution technique ensures both robustness in noise and efficiency of computation, while the model-based estimation and decision process is flexible and spatially local, thus avoiding assumptions about global homogeneity or size and number of regions. A comparative evaluation of the method against region-only and boundary-only methods is presented and is shown to produce accurate segmentations at quite low signal-to-noise ratios. (C) 2001 Elsevier Science B.V. All rights reserved.

Item Type:	Journal Article
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering Q Science > QC Physics
Journal or Publication Title:	IMAGE AND VISION COMPUTING
Publisher:	ELSEVIER SCIENCE BV
ISSN:	0262-8856
Date:	15 April 2001
Volume:	19
Number:	6
Number of Pages:	16
Page Range:	pp. 353-368
Publication Status:	Published
URI:	http://wrap.warwick.ac.uk/id/eprint/12241

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