计算机应用 ›› 2012, Vol. 32 ›› Issue (04): 1126-1129.DOI: 10.3724/SP.J.1087.2012.01126

• 图形图像技术 • 上一篇    下一篇

基于三维肤色模型的人脸检测预处理方法

孙劲光,周玉成,孟祥福,李扬   

  1. 辽宁工程技术大学 电子与信息工程学院, 辽宁 葫芦岛 125105
  • 收稿日期:2011-09-26 修回日期:2011-11-20 发布日期:2012-04-20 出版日期:2012-04-01
  • 通讯作者: 周玉成
  • 作者简介:孙劲光(1962-),女,辽宁阜新人,教授,博士生导师,主要研究方向:图形图像、数据挖掘;
    周玉成(1986-),男,河北唐山人,硕士研究生,主要研究方向:模式识别;
    孟祥福(1981-),男,辽宁朝阳人,讲师,博士,主要研究方向:Web数据库、XML个性化柔性查询;
    李扬(1985-),天津人,硕士研究生,主要研究方向:模式识别。
  • 基金资助:
    国家青年科学基金资助项目;辽宁省重点实验室资助项目

Face detection pre-processing method based on three-dimensional skin color model

SUN Jin-guang1,ZHOU Yu-chengZHOU2,MENG Xiang-fu1,LI Yang1   

  1. 1. School of Electronic and Information Engineering, Liaoning Technical University, Huludao Liaoning 125105, China
    2. School of Electronic and Information Engineering, Liaoning Technical University, Huludao Liaoning 125105, China
  • Received:2011-09-26 Revised:2011-11-20 Online:2012-04-20 Published:2012-04-01
  • Contact: ZHOU Yu-chengZHOU

摘要: 为了改善在光照变化和复杂背景影响下的人脸检测效果,在预处理阶段提出一种基于直接最小二乘拟合的三维肤色聚类模型算法。该算法首先将肤色在CbCrCg空间中的三个平面投影分布作为拟合对象,然后使用中值滤波和Sobel算子获取平滑边缘,最后通过直接最小二乘拟合法获取最佳三维肤色模型。在实验中分别将公共人脸库和户外拍摄的人脸图像作为实验对象,实验结果表明,该算法较传统肤色预处理算法具有更好的肤色分割效果,并且能够有效地提高人脸检测率。

关键词: 人脸检测, 肤色聚类, 最小二乘法, CbCrCg空间, 三维肤色模型

Abstract: In order to improve the face detection test results under the influence of illumination change and complex background, an algorithm of 3D color clustering model based on direct least squares estimate was proposed during the preprocessing phrase. Firstly, three plane projection distributions of skin color were seen as fitting objects in CbCrCg space, and then smooth edge was got by median filter and Sobel operator, at last the best 3D color model was got through direct least squares. In experiment, the public face library and face image got by outdoor shooting were seen as objects, and the experimental results show that, this algorithm has better segmentation effects than traditional color preprocessing algorithm, and it has improved the detection rate more effectively.

Key words: face detection, skin color clustering, least square, CbCrCg space, 3D skin color model

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