Image segmentation is an important task in computer vision and understanding. Graph Cuts have been shown to be useful in image segmentation problems. Using a criterion for segmentation optimality, they can obtain segmentation without relying heavily on a priori information regarding the specific type of object. Discussed here are a few approximations to the Normalized Cut criterion, the solving of which has been shown to be an NP-hard problem. Two Normalized Cut algorithms have been previously proposed, and a third is proposed here which accomplishes approximation by a similar method as one of the previous algorithms. It is also more efficient than either of the previously proposed Normalized Cut approximations.
| Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-2415 |
| Date | 01 May 2011 |
| Creators | Monroe, William Stonewall |
| Contributors | Wu, Xiaodong, Dr. |
| Publisher | University of Iowa |
| Source Sets | University of Iowa |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
| Source | Theses and Dissertations |
| Rights | Copyright 2011 William Stonewall Monroe |
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