Efficient skin region segmentation using low complexity fuzzy decision tree model

Rajen B. Bhatt, Abhinav Dhall, Gaurav Sharma, Santanu Chaudhury

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

34 Citations (Scopus)

Abstract

We propose an efficient skin region segmentation methodology using low complexity fuzzy decision tree constructed over B, G, R colour space. Skin and nonskin training dataset has been generated by using various skin textures obtained from face images of diversity of age, gender, and race people and nonskin pixels obtained from arbitrary thousands of random sampling of nonskin textures. Compact fuzzy model with very few numbers of rules allow to raster scan consumer photographs and classify each pixel as skin or nonskin for various face and human detection applications for embedded platforms.

Original languageEnglish
Title of host publicationProceedings of INDICON 2009 - An IEEE India Council Conference
DOIs
Publication statusPublished - 1 Dec 2009
Externally publishedYes
EventAnnual Conference of the IEEE India Council 2009 - Ahmedabad, India
Duration: 18 Dec 200920 Dec 2009
https://ieeexplore.ieee.org/xpl/conhome/5409246/proceeding (Proceedings)

Publication series

NameProceedings of INDICON 2009 - An IEEE India Council Conference

Conference

ConferenceAnnual Conference of the IEEE India Council 2009
Abbreviated titleINDICON 2009
Country/TerritoryIndia
CityAhmedabad
Period18/12/0920/12/09
Internet address

Keywords

  • Fuzzy decision trees
  • Skin Segmentation

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