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A sensitivity analysis of initial conditions for the Mumford-Shah based level set method of image segmentation (student paper)
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Source ACM Southeast Regional Conference archive
Proceedings of the 45th annual southeast regional conference table of contents
Winston-Salem, North Carolina
SESSION: Papers table of contents
Pages: 19 - 23  
Year of Publication: 2007
ISBN:978-1-59593-629-5
Authors
Bruce Johnson  Knoxville, TN
Yongsheng Pan  Knoxville, TN
Sponsor
SIGAPP: ACM Special Interest Group on Applied Computing
Publisher
ACM  New York, NY, USA
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ABSTRACT

The level set method provides a means of segmenting images. Fundamentally, the level set method for image segmentation is a search algorithm that determines where an evolving curve's boundary pixels - who are meant to encompass an image segment's perimeter - should be placed according to some criteria. A method has been devised that utilizes the Mumford-Shah functional as a means of establishing that criteria. It has been shown that this method for image segmentation has limitations that, while mentioned in the original research, were not quantified with examples. We present evidence of these limitations, discuss how they occurred and describe our preliminary attempts at overcoming them. We conclude by offering a direction where this research might lead. This work is part of an ongoing research project.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Seedahmed, G. and Martucci, L., "Automated Image Registration Using Geometrically Invariant Parameter Space Clustering (GIPSC)," Archives of the International Society of Photogrammetry and Remote Sensing, 2002.
 
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Sethian, J. A. Tracking Interfaces with Level Sets, American Scientist, May-June, 1997.
 
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Wasilewski, M. Active Contours using Level Sets for Medical Image Segmentation, http://www.postulate.org/segmentation/segmentation.pdf
 
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Collaborative Colleagues:
Bruce Johnson: colleagues
Yongsheng Pan: colleagues