Coefficient of Variation Based Image Selective Segmentation Model Using Active Contours
Noor Badshah 1, Ke Chen 2*, Haider Ali 1, Ghulam Murtaza 11 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
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).
Email: firstname.lastname@example.org (N. Badshah), email@example.com (K. Chen)