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Proceedings Paper

Interactive dynamic graph cut based image segmentation with shape priors
Author(s): Chen Liu; Fengxia Li; Shouyi Zhan
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Paper Abstract

In this paper, we present a new method bases on dynamic graph cut and captures both the shape and the nature information of the image for interactive image segmentation. While traditional interactive graph cut approaches for image segmentation are often successful, they may fail in camouflage. Prior shape knowledge can largely mitigate this problem. In this paper, two kinds of shape priors are taken into account to obtain more accurate results. In order to use the information from user input more effectively, a weight function is introduced to control the relative importance of shape knowledge. Then, a one-shot fully dynamic graph cut algorithm is introduced to minimize the energy function, and during this procedure, only a subset of pixels in the image is considered, which greatly reduces the complexity of dynamic graph cut algorithm. Extensive experiments, including comparisons with some state-of-the-arts, show the effectiveness of our methods in improving the segmentation performance and saving the processing time.

Paper Details

Date Published: 15 November 2007
PDF: 9 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67862I (15 November 2007); doi: 10.1117/12.749684
Show Author Affiliations
Chen Liu, Beijing Institute of Technology (China)
Fengxia Li, Beijing Institute of Technology (China)
Shouyi Zhan, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition

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