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Proceedings Paper

Single level set based fast images segmentation model with multiple regions
Author(s): Honghui Zhang; Yong Tan; Shanshan Li
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Paper Abstract

In traditional image segmentation models based on single level set function, only two regions can be identified because different regions are identified by the signs of single level set function. Though several segmentation models with multiple regions have been proposed, but the largest number of regions that can be identified was limited by the number of embedded level set functions in them. Moreover, the more embedded level set functions, the higher the time cost, usually increasing linearly with the increase of embedded level set functions. In this paper, by introducing the segmentation-measure function, a new model for multi-regions image segmentation based on single level set function is proposed. At the same time, a new initialization function for the level set function is also proposed in order to reduce the time cost of the segmentation model. The experiment results show that the new Image segmentation mode with multiple regions proposed in this paper performs well and dramatically reduces the time cost compared with the popular model for multiple regions proposed by Vese and Chan.

Paper Details

Date Published: 15 November 2007
PDF: 8 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67861T (15 November 2007); doi: 10.1117/12.748925
Show Author Affiliations
Honghui Zhang, Univ. of Science and Technology of China (China)
Yong Tan, Univ. of Science and Technology of China (China)
Shanshan Li, Univ. of Science and Technology of China (China)


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

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