Date of Degree

2011

Document Type

Master's thesis

Degree Name

MS (Master of Science)

Department

Electrical and Computer Engineering

First Advisor

Xiaodong Wu

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.

Pages

vi, 38

Bibliography

37-38

Copyright

Copyright 2011 William Stonewall Monroe