DOI
10.17077/etd.4cet1r5y
Document Type
Thesis
Date of Degree
Spring 2011
Degree Name
MS (Master of Science)
Degree In
Electrical and Computer Engineering
First Advisor
Xiaodong Wu
First Committee Member
Milan Sonka
Second Committee Member
Mona Garvin
Abstract
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.
Keywords
Algorithms, Graph cuts, Normalized Cuts
Pages
vi, 38 pages
Bibliography
Includes bibliographical references (pages 37-38).
Copyright
Copyright 2011 William Stonewall Monroe
Recommended Citation
Monroe, William Stonewall. "Normalized Cut Approximations." MS (Master of Science) thesis, University of Iowa, 2011.
https://doi.org/10.17077/etd.4cet1r5y.