Please use this identifier to cite or link to this item: https://doi.org/10.1007/s11263-006-9140-x
Title: Image segmentation using some piecewise constant level set methods with MBO type of projection
Authors: Tai, X.-C.
Christiansen, O.
Lin, P. 
Skjælaaen, I.
Keywords: Image segmentation
Level set method
Phase field model
Total variation regularization
Issue Date: Jun-2007
Citation: Tai, X.-C., Christiansen, O., Lin, P., Skjælaaen, I. (2007-06). Image segmentation using some piecewise constant level set methods with MBO type of projection. International Journal of Computer Vision 73 (1) : 61-76. ScholarBank@NUS Repository. https://doi.org/10.1007/s11263-006-9140-x
Abstract: In this work, we are trying to propose fast algorithms for Mumford-Shah image segmentation using some recently proposed piecewise constant level set methods (PCLSM). Two variants of the PCLSM will be considered in this work. The first variant, which we call the binary level set method, needs a level set function which only takes values ±1 to identify the regions. The second variant only needs to use one piecewise constant level set function to identify arbitrary number of regions. For the Mumford-Shah image segmentation model with these new level set methods, one needs to minimize some smooth energy functionals under some constrains. A penalty method will be used to deal with the constraint. AOS (additive operator splitting) and MOS (multiplicative operator splitting) schemes will be used to solve the Euler-Lagrange equations for the minimization problems. By doing this, we obtain some algorithms which are essentially applying the MBO scheme for our segmentation models. Advantages and disadvantages are discussed for the proposed schemes. © Springer Science + Business Media, LLC 2007.
Source Title: International Journal of Computer Vision
URI: http://scholarbank.nus.edu.sg/handle/10635/103398
ISSN: 09205691
DOI: 10.1007/s11263-006-9140-x
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