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Coefficient of Variation Based Image Selective Segmentation Model Using Active Contours

Published online by Cambridge University Press:  28 May 2015

Noor Badshah ,
Ke Chen ,
Haider Ali  and
Ghulam Murtaza
Noor Badshah*
Affiliation:
Department of Basic Sciences, UET Peshawar, Pakistan
Ke Chen*
Affiliation:
Centre for Mathematical Imaging Techniques and Department of Mathematical Sciences, The University of Liverpool, United Kingdom
Haider Ali
Affiliation:
Department of Basic Sciences, UET Peshawar, Pakistan
Ghulam Murtaza
Affiliation:
Department of Basic Sciences, UET Peshawar, Pakistan
*
Corresponding author. Email: noor2knoor@googlemail.com
Corresponding author. Email: k.chen@liv.ac.uk
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Abstract

Most image segmentation techniques efficiently segment images with prominent edges, but are less efficient for some images with low frequencies and overlapping regions of homogeneous intensities. A recently proposed selective segmentation model often works well, but not for such challenging images. In this paper, we introduce a new model using the coefficient of variation as a fidelity term, and our test results show it performs much better in these challenging cases.

Keywords

68U1062G30SegmentationCoefficient of Variation (CoV)level setfunctional minimisiationTotal Variation (TV)

Information

Type
Research Article
Information
East Asian Journal on Applied Mathematics , Volume 2 , Issue 2 , May 2012 , pp. 150 - 169
Copyright
Copyright © Global-Science Press 2012

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