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A dynamic threshold approach for skin tone detection in colour images
School of Computing and Intelligent Systems (SCIS), University of Ulster, BT48 7JL, United Kingdom.
School of Computing and Intelligent Systems (SCIS), University of Ulster, BT48 7JL, United Kingdom.
School of Computing and Intelligent Systems (SCIS), University of Ulster, BT48 7JL, United Kingdom.
School of Computing and Intelligent Systems (SCIS), University of Ulster, BT48 7JL, United Kingdom.
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2012 (English)In: International Journal of Biometrics (IJBM), ISSN 1755-8301, E-ISSN 1755-831X, Vol. 4, no 1, p. 38-55Article in journal (Refereed) Published
Abstract [en]

This paper presents a novel dynamic threshold approach to discriminate skin pixels and non-skin pixels in colour images. Fixed decision boundaries (or fixed threshold) classification approaches are successfully applied to detect human skin tone in colour images. These fixed thresholds mostly failed in two situations as they only search for a certain skin colour range: • any non-skin object may be classified as skin if non-skin objects's colour values belong to fixed threshold range • any true skin may be mistakenly classified as non-skin if the skin colour values do not belong to fixed threshold range. Therefore in this paper, instead of predefined fixed thresholds, novel online learned dynamic thresholds are used to overcome the above drawbacks. The experimental results show that our method is robust in overcoming these drawbacks. © 2012 Inderscience Enterprises Ltd.

Place, publisher, year, edition, pages
InderScience Publishers, 2012. Vol. 4, no 1, p. 38-55
Keywords [en]
Dynamic threshold, Skin tone detection
National Category
Dermatology and Venereal Diseases
Identifiers
URN: urn:nbn:se:umu:diva-212658DOI: 10.1504/IJBM.2012.044291ISI: 000214642800003Scopus ID: 2-s2.0-84857299710OAI: oai:DiVA.org:umu-212658DiVA, id: diva2:1789566
Available from: 2023-08-21 Created: 2023-08-21 Last updated: 2023-08-21Bibliographically approved

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Cheddad, Abbas

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Umeå Centre for Molecular Medicine (UCMM)
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CiteExportLink to record
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  • apa
  • ieee
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • asciidoc
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