Graph Models and Shape Deformation for Image Segmentation
Wang, Song
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https://hdl.handle.net/2142/80807
Description
Title
Graph Models and Shape Deformation for Image Segmentation
Author(s)
Wang, Song
Issue Date
2002
Doctoral Committee Chair(s)
Liang, Zhi-Pei
Department of Study
Electrical Engineering
Discipline
Electrical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Computer Science
Language
eng
Abstract
The second part of this thesis is focused on using prior geometric information to improve the reliability and accuracy of image segmentation. Specifically, a new shape-deformation method is proposed to incorporate prior template shape information into image segmentation by deforming a given template shape to fit the detected low-level edge features in a target image. Combining the support vector machine and thin-plate splines, this method increases the robustness to the detection noise as well as the reliability to preserve the template shape topology. In addition, an efficient algorithm is developed to optimize the deformation cost function using quadratic programming.
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