北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2018, Vol. 41 ›› Issue (1): 24-30.doi: 10.13190/j.jbupt.2017-184

• 论文 • 上一篇    下一篇

基于特征选择的皮肤检测混合颜色空间的选取

刘新华1, 赵子谦1, 旷海兰1, 马小林1, 李方敏2   

  1. 1. 武汉理工大学 信息工程学院, 武汉 430070;
    2. 长沙学院 数学与计算机系, 长沙 410022
  • 收稿日期:2017-08-30 出版日期:2018-02-28 发布日期:2018-01-04
  • 作者简介:刘新华(1974-),男,教授,硕士生导师,E-mail:liuxinhua@whut.edu.cn.
  • 基金资助:
    国家自然科学基金项目(61373042,61502361);湖北省自然科学基金项目(2014CFB869)

Selection of Hybrid Color Space for Skin Detection Based on Feature Selection Method

LIU Xin-hua1, ZHAO Zi-qian1, KUANG Hai-lan1, MA Xiao-lin1, LI Fang-min2   

  1. 1. School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China;
    2. Department of Mathematics and Computer Science, Changsha University, Changsha 410022, China
  • Received:2017-08-30 Online:2018-02-28 Published:2018-01-04

摘要: 通过特征选择的方法解决皮肤检测过程中颜色空间的选取问题,针对现有基于互信息的特征选择方法的不足,提出了改进方法:1)使用互信息缩小特征选择范围,然后选择使分类效果最佳的特征子集;2)尝试多种可能的特征子集初始化方案,然后选择其中最优的方案.实验结果和对比分析表明,使用改进后的特征选择方法得到的混合颜色空间,其皮肤检测效果优于传统颜色空间和已有混合颜色空间.

关键词: 皮肤检测, 最优特征空间, 混合颜色空间, 互信息, 特征选择

Abstract: To solve the problem of selecting appropriate color space for skin detection, a feature-selection-based method is exploited and two improvements on traditional method are proposed:Firstly, mutual information is used to narrow the feature selection range, then feature subset which produces the best classification accuracy will be selected; Secondly, a variety of possible feature subset initialization schemes are tested, and then choose feature set that reveal the best result. Experimental results and comparative analysis show that the hybrid color spaces obtained by the improved feature selection method have better skin detection performance than traditional color spaces and existing hybrid color spaces.

Key words: skin detection, optimal feature space, hybrid color space, mutual information, feature selection

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