IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/1524286.html
   My bibliography  Save this article

Segmentation of Melanoma Skin Lesion Using Perceptual Color Difference Saliency with Morphological Analysis

Author

Listed:
  • Oludayo O. Olugbara
  • Tunmike B. Taiwo
  • Delene Heukelman

Abstract

The prevalence of melanoma skin cancer disease is rapidly increasing as recorded death cases of its patients continue to annually escalate. Reliable segmentation of skin lesion is one essential requirement of an efficient noninvasive computer aided diagnosis tool for accelerating the identification process of melanoma. This paper presents a new algorithm based on perceptual color difference saliency along with binary morphological analysis for segmentation of melanoma skin lesion in dermoscopic images. The new algorithm is compared with existing image segmentation algorithms on benchmark dermoscopic images acquired from public corpora. Results of both qualitative and quantitative evaluations of the new algorithm are encouraging as the algorithm performs excellently in comparison with the existing image segmentation algorithms.

Suggested Citation

  • Oludayo O. Olugbara & Tunmike B. Taiwo & Delene Heukelman, 2018. "Segmentation of Melanoma Skin Lesion Using Perceptual Color Difference Saliency with Morphological Analysis," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-19, February.
    • Handle: RePEc:hin:jnlmpe:1524286
    DOI: 10.1155/2018/1524286
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2018/1524286.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2018/1524286.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2018/1524286?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:1524286. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.