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Unsupervised image segmentation combining region and boundary
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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 | ||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering Q Science > QC Physics |
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Journal or Publication Title: | IMAGE AND VISION COMPUTING | ||||
Publisher: | ELSEVIER SCIENCE BV | ||||
ISSN: | 0262-8856 | ||||
Official Date: | 15 April 2001 | ||||
Dates: |
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Volume: | 19 | ||||
Number: | 6 | ||||
Number of Pages: | 16 | ||||
Page Range: | pp. 353-368 | ||||
Publication Status: | Published |
Data sourced from Thomson Reuters' Web of Knowledge
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