Unsupervised image segmentation combining region and boundary
UNSPECIFIED. (2001) Unsupervised image segmentation combining region and boundary. IMAGE AND VISION COMPUTING, 19 (6). pp. 353-368. ISSN 0262-8856Full text not available from this repository.
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|
|Official Date:||15 April 2001|
|Number of Pages:||16|
|Page Range:||pp. 353-368|
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