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Volume 2, Issue 2
Coefficient of Variation Based Image Selective Segmentation Model Using Active Contours

Noor Badshah, Ke Chen, Haider Ali & Ghulam Murtaza

DOI: 10.4208/eajam.090312.190412a

East Asian J. Appl. Math., 2 (2012), pp. 150-169.

Published online: 2018-02

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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

Segmentation, Coefficient of Variation (CoV), level set, functional minimisation, Total Variation (TV).

  • AMS Subject Headings

68U10, 62G30

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{EAJAM-2-150, author = {Noor Badshah, Ke Chen, Haider Ali and Ghulam Murtaza}, title = {Coefficient of Variation Based Image Selective Segmentation Model Using Active Contours}, journal = {East Asian Journal on Applied Mathematics}, year = {2018}, volume = {2}, number = {2}, pages = {150--169}, 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.

}, issn = {2079-7370}, doi = {https://doi.org/10.4208/eajam.090312.190412a}, url = {http://global-sci.org/intro/article_detail/eajam/10872.html} }
TY - JOUR T1 - Coefficient of Variation Based Image Selective Segmentation Model Using Active Contours AU - Noor Badshah, Ke Chen, Haider Ali & Ghulam Murtaza JO - East Asian Journal on Applied Mathematics VL - 2 SP - 150 EP - 169 PY - 2018 DA - 2018/02 SN - 2 DO - http://doi.org/10.4208/eajam.090312.190412a UR - https://global-sci.org/intro/article_detail/eajam/10872.html KW - Segmentation, Coefficient of Variation (CoV), level set, functional minimisation, Total Variation (TV). AB -

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.

Noor Badshah, Ke Chen, Haider Ali and Ghulam Murtaza. (2018). Coefficient of Variation Based Image Selective Segmentation Model Using Active Contours. East Asian Journal on Applied Mathematics. 2 (2). 150-169. doi:10.4208/eajam.090312.190412a
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