East Asian Journal on Applied Mathematics, 2 (2012), pp. 150-169.


Coefficient of Variation Based Image Selective Segmentation Model Using Active Contours

Noor Badshah 1, Ke Chen 2*, Haider Ali 1, Ghulam Murtaza 1

1 Department of Basic Sciences, UET Peshawar, Pakistan.
2 Centre for Mathematical Imaging Techniques and Department of Mathematical Sciences, The University of Liverpool, United Kingdom.

Received 9 March 2012; Accepted (in revised version) 8 April 2012
Available online 27 April 2012
doi:10.4208/eajam.090312.080412a

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.

AMS subject classifications: 68U10, 62G30
Key words: Segmentation, Coefficient of Variation (CoV), level set, functional minimisiation, Total Variation (TV).

*Corresponding author.
Email: noor2knoor@googlemail.com (N. Badshah), k.chen@liv.ac.uk (K. Chen)
 

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