NDLI: Skin Detection Using Contourlet-Based Texture Analysis

Content Provider	IEEE Xplore Digital Library
Author	Fotouhi, M. Rohban, M.H. Kasaei, S.
Copyright Year	2009
Abstract	Detection of skin pixels in arbitrary images is addressed in this paper. We have combined texture and color information to segment skin regions. First, a pixel-based boosted skin detection method is used to locate skin pixels. To further improve the detect performance, skin region texture features are employed using the nonsubsampled contourlet coefficients. For the candidate skin pixels, the set of 8x8 patches around that pixel in all subimages are selected and the feature vector of each patch is extracted. Multilayer perceptron is then utilized to learn features and classify any given input sample. The proposed algorithm has achieved true positive rate of about 82.8% and false positive rate of about 7.6% on the test set that contains 300 images. Experimental results show the effectiveness of the proposed method when compared to the other state-of-the-art texture-based skin segmentation approaches.
Starting Page	59
Ending Page	64
File Size	710066
Page Count	6
File Format	PDF
ISBN	9780769536958
DOI	10.1109/ICDT.2009.18
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-07-20
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Skin Pixel Image analysis Image segmentation Data mining Telecommunication computing Multilayer perceptrons Face detection Image texture analysis Lighting Texture Analysis Skin Detection Pixel-Based Skin Detection Region-Based Skin Detection
Content Type	Text
Resource Type	Article

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