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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Image Segmentation Using Multiphase Curve Evolution Based on Level Set
verfasst von : Li Liu, Xiaowei Tu, Wenju Zhou, Minrui Fei, Aolei Yang, Jun Yue
Erschienen in: Computational Intelligence, Networked Systems and Their Applications
Verlag: Springer Berlin Heidelberg
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A novel multiphase curve evolution based on level set (MCELS) is presented, which is used for image segmentation. The MCELS method introduces
N
level set functions partition 2
N
sub-regions, which reduces the computational complexity. The double curve function is developed on the modified penalty function during the evolution. The experimental objects employ tablet packaging images. From the simulation results, the MCELS method can be used to partition multiple gray regions images for the noise, uneven gray scale, and intensity inhomogeneities. Comparing with recent researches based on level set methods, the characteristics of MCELS for image segmentation are superior robustness for noise, less run time and preferable computational efficiency.