20 February 2006 Robust level set method for computer vision
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Proceedings Volume 6041, ICMIT 2005: Information Systems and Signal Processing; 60410B (2006) https://doi.org/10.1117/12.664288
Event: ICMIT 2005: Merchatronics, MEMS, and Smart Materials, 2005, Chongqing, China
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.
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Jia-rui Si, Xiao-pei Li, Hong-wei Zhang, "Robust level set method for computer vision", Proc. SPIE 6041, ICMIT 2005: Information Systems and Signal Processing, 60410B (20 February 2006); doi: 10.1117/12.664288; https://doi.org/10.1117/12.664288
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