Moving objects segmentation based on piecewise constant Mumford-Shah model solving by additive operator splitting

We propose a moving objects segmentation method for color image sequences based on the piecewise constant Mumford-Shah model (also known as the C-V model) solving by the semi-implicit additive operator splitting (AOS) scheme, which is unconditionally stable, fast, and easy to implement. The method f...

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Bibliographic Details
Published in:Optical Engineering 2010-03, Vol.49 (3), p.037004-037004
Main Authors: Wang, Dengwei, Zhang, Tianxu, Shi, Wenjun, Wang, Zhonghua, Yang, Xiaoyu, Wei, Longsheng
Format: Article
Language:English
Subjects:
Additives
Evolution
Gaussian
Mathematical models
Operators
Segmentation
Splitting
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Summary:We propose a moving objects segmentation method for color image sequences based on the piecewise constant Mumford-Shah model (also known as the C-V model) solving by the semi-implicit additive operator splitting (AOS) scheme, which is unconditionally stable, fast, and easy to implement. The method first uses the Gaussian mixture model for background modeling and then subtracts the background to obtain the moving regions that are the handling objects of our method. As a result of the introduction of the AOS scheme, we could use a rather large time step and still maintain the stability of the evolution process. Additionally, the method can easily be parallelized because the AOS scheme decomposes the equations into a sequence of one-dimensional (1-D) systems. The experimental results demonstrate that under real moving objects video tests, the AOS scheme accelerates the evolution of the curve and significantly reduces the number of iterations, and also demonstrates the validity of our method.
ISSN:0091-3286
1560-2303
DOI:10.1117/1.3363833