Efficient Skin Region Segmentation Using Low Complexity Fuzzy Decision Tree Model

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...

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Bibliographic Details
Published in2009 Annual IEEE India Conference pp. 1 - 4
Main Authors Bhatt, R.B., Dhall, A., Sharma, G., Chaudhury, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2009
Subjects
Classification tree analysis
Decision trees
Embedded system
Face detection
Humans
Image databases
Image sampling
Image segmentation
Induction generators
Skin
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Summary: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.
ISBN:1424448581
9781424448586
ISSN:2325-940X
DOI:10.1109/INDCON.2009.5409447