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Proceedings Paper

Application of SGRBF for level set based image segmentation
Author(s): Yingxuan Zhu; Miyoung Shin; Amrit L. Goel
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Paper Abstract

In this study, the radial basis functions based SG algorithm (SGRBF) is applied for evolution of level sets in image segmentation. The implementation of level set method in image processing often involves solving partial differential equations (PDEs). Finite differences implicit scheme is a prevalent method to solve PDE for extending the evolution of level sets. Instead of using finite differences method, SGRBF is used in our study for evolving level sets. The SGRBF is a mathematical framework developed for function approximation using Gaussian RBFs. In SGRBF, the number and centers of the basis functions are determined in a systematic and mathematically sound way using a purely algebraic approach. The numerical results show that, except for a continuous representation of both the implicit function and its level sets, the algorithm we introduce here can reduce the computation cost by selecting the most contributive centers for radial basis functions.

Paper Details

Date Published: 10 February 2009
PDF: 10 pages
Proc. SPIE 7245, Image Processing: Algorithms and Systems VII, 724514 (10 February 2009); doi: 10.1117/12.805503
Show Author Affiliations
Yingxuan Zhu, Syracuse Univ. (United States)
Miyoung Shin, Kyungpook National Univ. (Korea, Republic of)
Amrit L. Goel, Syracuse Univ. (United States)

Published in SPIE Proceedings Vol. 7245:
Image Processing: Algorithms and Systems VII
Nasser M. Nasrabadi; Jaakko T. Astola; Karen O. Egiazarian; Syed A. Rizvi, Editor(s)

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