Skin Colour Detection Using the Statistical Decision Theory

被引：3

作者：

Fang, Gu ^{[1
]}

Kwok, Ngai Ming ^{[2
]}

Dissanayake, Gamini ^{[3
]}

机构：

[1] Univ Western Sydney, Sch Comp Engn & Math, Penrith, NSW 2751, Australia

[2] Univ New S Wales, Sch Mech & Mfg Engn, Sydney, NSW 2052, Australia

[3] Univ Technol Sydney, Sch Elec Mech & Mechatron Syst, Sydney, NSW 2007, Australia

来源：

MANUFACTURING PROCESS AND EQUIPMENT, PTS 1-4 | 2013年 / 694-697卷

关键词：

Skin colour detection; skin modelling; decision theory; sign test;

D O I：

10.4028/www.scientific.net/AMR.694-697.1891

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Skin colour is an important attribute that can be used to detect human presence in an image. In this paper, a new method is introduced to detect skin pixels in an image based on statistical decision theory. The proposed method uses a parametric model to produce a pixel seed that represents a potential skin pixel. Then the validity of the pixel is confirmed using a moving window and the nonparametric sign test. Experiments show that the proposed method can produce very accurate skin detection results.

引用

页码：1891 / +

页数：2

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