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Proceedings Paper

Robust level set method for computer vision
Author(s): Jia-rui Si; Xiao-pei Li; Hong-wei Zhang
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Paper Abstract

Level set method provides powerful numerical techniques for analyzing and solving interface evolution problems based on partial differential equations. It is particularly appropriate for image segmentation and other computer vision tasks. However, there exists noise in every image and the noise is the main obstacle to image segmentation. In level set method, the propagation fronts are apt to leak through the gaps at locations of missing or fuzzy boundaries that are caused by noise. The robust level set method proposed in this paper is based on the adaptive Gaussian filter. The fast marching method provides a fast implementation for level set method and the adaptive Gaussian filter can adapt itself to the local characteristics of an image by adjusting its variance. Thus, the different parts of an image can be smoothed in different way according to the degree of noisiness and the type of edges. Experiments results demonstrate that the adaptive Gaussian filter can greatly reduce the noise without distorting the image and made the level set methods more robust and accurate.

Paper Details

Date Published: 20 February 2006
PDF: 5 pages
Proc. SPIE 6041, ICMIT 2005: Information Systems and Signal Processing, 60410B (20 February 2006); doi: 10.1117/12.664288
Show Author Affiliations
Jia-rui Si, Tianjin Medical Univ. (China)
Tianjin Univ. (China)
Xiao-pei Li, Tianjin Medical Univ. (China)
Hong-wei Zhang, Tianjin Univ. (China)

Published in SPIE Proceedings Vol. 6041:
ICMIT 2005: Information Systems and Signal Processing
Yunlong Wei; Kil To Chong; Takayuki Takahashi, Editor(s)

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