Maximal probability method of boundary extraction based on particle motion

Liantang Lou; Zhongliang Fu; Si Jiang

doi:10.1117/12.748326

15 November 2007 Maximal probability method of boundary extraction based on particle motion

Liantang Lou, Zhongliang Fu, Si Jiang

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67861F (2007) https://doi.org/10.1117/12.748326
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Liantang Lou, Zhongliang Fu, and Si Jiang "Maximal probability method of boundary extraction based on particle motion", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67861F (15 November 2007); https://doi.org/10.1117/12.748326

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