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Proceedings Paper

A fast level set implementation method for image segmentation and object tracking
Author(s): Shuqun Zhang
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Paper Abstract

The high computational complexity of level set methods has excluded themselves from many real-time applications. The high algorithm complexity is mainly due to the need of solving partial differential equations (PDEs) numerically. For image segmentation and object tracking applications, it is possible to approximate level set curve evolution process without solving PDEs since we are interested in the final object boundary instead of the accurate curve evolution process. This paper proposes a fast parallel method to simplify curve evolution process using simple binary morphological operations. The proposed fast implementation allows real-time image segmentation and object tracking using level set curve evolution, while preserves the advantage of level set methods for automatically handling topological changes. It can utilize the parallel processing capability of existing embedded hardware, parallel computers or optical processors for fast curve evolution.

Paper Details

Date Published: 24 August 2006
PDF: 8 pages
Proc. SPIE 6312, Applications of Digital Image Processing XXIX, 63121R (24 August 2006); doi: 10.1117/12.682228
Show Author Affiliations
Shuqun Zhang, College of Staten Island/CUNY (United States)

Published in SPIE Proceedings Vol. 6312:
Applications of Digital Image Processing XXIX
Andrew G. Tescher, Editor(s)

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