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

Noor Badshah, Ke Chen, Haider Ali & Ghulam Murtaza

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 minimisiation 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://dor.org/10.4208/eajam.090312.190412a UR - https://global-sci.org/intro/article_detail/eajam/10872.html KW - Segmentation KW - Coefficient of Variation (CoV) KW - level set KW - functional minimisiation KW - 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 & Ghulam Murtaza. (1970). 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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