Almost optimal skin detection approach within the Gaussian framework

Youtian Du; Zhongmin Cai; Xiaohong Guan; Qian Li

doi:10.1117/1.OE.51.2.027007

16 March 2012 Almost optimal skin detection approach within the Gaussian framework

Youtian Du, Zhongmin Cai, Xiaohong Guan, Qian Li

Author Affiliations +

Optical Engineering, Vol. 51, Issue 2, 027007 (March 2012). https://doi.org/10.1117/1.OE.51.2.027007

Abstract

Skin detection plays an important role in many applications, including face detection, human motion analysis, and objectionable image filtering. We propose a novel skin detection approach named multiple Gaussian models (MGMs). This approach combines multiple single Gaussian models and determines each model in order to maximize the true positive rate (TPR) of skin detection subject to a fixed predefined false positive rate (FPR). We derive the discrete and continuous forms of MGM approaches in the paper. The proposed approach has almost optimal performance for a broad range of FPRs in the Gaussian framework. Moreover, it has low computational costs in skin detection for new image instances. Experimental results show that the MGM approach has better skin detection performance than previous methods within the Gaussian framework.

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Youtian Du, Zhongmin Cai, Xiaohong Guan, and Qian Li "Almost optimal skin detection approach within the Gaussian framework," Optical Engineering 51(2), 027007 (16 March 2012). https://doi.org/10.1117/1.OE.51.2.027007

Published: 16 March 2012

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