• DocumentCode
    3412990
  • Title

    Fuzzy Mamdani Inference System Skin Detection

  • Author

    Selamat, Ali ; Maarof, Mohd Aizaini ; Chin, Tey Yi

  • Author_Institution
    Fac. of Comput. Sci. & Inf. Syst., Univ. Teknol. Malaysia, Skudai, Malaysia
  • Volume
    3
  • fYear
    2009
  • fDate
    12-14 Aug. 2009
  • Firstpage
    57
  • Lastpage
    62
  • Abstract
    Skin detection is well known to detect the appearance of human and human parts within an image. However, there are several limitations exist in skin detection when using skin colour as cue to detect skin appearance. These limitations include problems such as illumination, skin-like pixels and camera characteristic. In this paper, a set of modified fuzzy rules has been introduced to deal with the skin-lie pixels problem. These modified fuzzy rules were integrated with skin modelling method in order to discriminate skin pixel and non-skin pixel. The experiment conducted in this paper is classification of human skin image and animal images. The experimental result is then compared with explicitly defined skin region and fuzzy Sugeno classification method. From the experiments, we have found that the proposed fuzzy rules are applicable if the RGB value of pixel does not close to low value.
  • Keywords
    fuzzy reasoning; image colour analysis; object detection; skin; RGB value; fuzzy Sugeno classification method; fuzzy mamdani inference system; fuzzy rule; human skin image classification; skin appearance detection; skin colour; Cameras; Face detection; Feature extraction; Fuzzy sets; Fuzzy systems; Humans; Hybrid intelligent systems; Lighting; Lightning; Skin; fuzzy mamdani; fuzzy rules; skin detections;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Hybrid Intelligent Systems, 2009. HIS '09. Ninth International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-0-7695-3745-0
  • Type

    conf

  • DOI
    10.1109/HIS.2009.224
  • Filename
    5254534