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Proceedings Paper

Variational segmentation of x-ray image with overlapped objects
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Paper Abstract

Image segmentation is a classical and challenging problem in image processing and computer vision. Most of the segmentation algorithms, however, do not consider overlapped objects. Due to the special characteristics of X-ray imaging, the overlapping of objects is very commonly seen in X-ray images and needs to be carefully dealt with. In this paper, we propose a novel energy functional to solve this problem. The Euler-Lagrange equation is derived and the segmentation is converted to a front propagating problem that can be efficiently solved by level set methods. We noticed that the proposed energy functional has no unique extremum and the solution relies on the initialization. Thus, an initialization method is proposed to get satisfying results. The experiment on real data validated our proposed method.

Paper Details

Date Published: 17 February 2006
PDF: 11 pages
Proc. SPIE 6064, Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning, 60640W (17 February 2006); doi: 10.1117/12.650449
Show Author Affiliations
Guoqiang Yu, Nuctech Co. Ltd. (China)
Li Zhang, Nuctech Co. Ltd. (China)
Tsinghua Univ. (China)
Jin Zhang, Tsinghua Univ. (China)
Yuxiang Xing, Nuctech Co. Ltd. (China)
Tsinghua Univ. (China)
Hewei Gao, Tsinghua Univ. (China)


Published in SPIE Proceedings Vol. 6064:
Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning
Nasser M. Nasrabadi; Edward R. Dougherty; Jaakko T. Astola; Syed A. Rizvi; Karen O. Egiazarian, Editor(s)

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