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Proceedings Paper

Maximal probability method of boundary extraction based on particle motion
Author(s): Liantang Lou; Zhongliang Fu; Si Jiang
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Paper Abstract

To overcome the main drawbacks of global minimal for active contour models (L. D. Cohen and Ron Kimmel) that the contour is only extracted partially for low SNR images, we present a new boundary extraction method, called maximal probability method of boundary extraction. We extend the description of boundary extraction from the point of view of classic mechanics to quantum mechanics, and propose a new boundary extraction approach based on maximal probability of a moving particle from one point to another. Our method is based on finding a path of maximal probability. The method includes four sequential parts: Explain boundary extraction from quantum mechanics; Estimate the probability that a particle moves from a point to another; Find a path of maximal probability between two points; Extract closed boundary from a single point by dividing the image into two small images. We show examples of our method applied to real images to compare our method with global minimal for active contour models. The experiments demonstrate that our method can overcome the main drawbacks of global minimal for active contour models.

Paper Details

Date Published: 15 November 2007
PDF: 5 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67861F (15 November 2007); doi: 10.1117/12.748326
Show Author Affiliations
Liantang Lou, Wuhan Univ. (China)
Wuhan Institute of Technology (China)
Zhongliang Fu, Wuhan Univ. (China)
Si Jiang, Wuhan 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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