J4 ›› 2011, Vol. 38 ›› Issue (2): 61-65+111.doi: 10.3969/j.issn.1001-2400.2011.02.011

• 研究论文 • 上一篇    下一篇

一种新的人脸归一化算法

靳薇1,2;张建奇1;梁建霞2;王加强2   

  1. (1. 西安电子科技大学 技术物理学院,陕西 西安  710071;
    2. 北京市新技术应用研究所,北京  100021)
  • 收稿日期:2010-06-23 出版日期:2011-04-20 发布日期:2011-05-26
  • 通讯作者: 靳薇
  • 作者简介:靳薇(1977-),女,西安电子科技大学博士研究生,E-mail: jindaweizi2006@sina.com.
  • 基金资助:

    国家自然科学基金资助项目(60777042);北京市科学技术研究院萌芽计划资助项目

New algorithm for normalization of the face image

JIN Wei1,2;ZHANG Jianqi1;LIANG Jianxia2;WANG Jiaqiang2   

  1. (1. School of Technical Physics, Xidian Univ., Xi'an  710071, China;
    2. Beijing Institute of New Technology Application, Beijing  100012, China)
  • Received:2010-06-23 Online:2011-04-20 Published:2011-05-26
  • Contact: JIN Wei

摘要:

提出了一种基于改进的局部梯度算子进行嘴角定位、同时结合双眼位置进行人脸归一化的新方法.该方法首先通过Adaboost算法检测出人脸图像、眼睛和嘴部区域大致位置,然后采用灰度积分投影法精确定位两眼位置,并根据改进的局部梯度算子提取嘴部轮廓,最终依据两眼与嘴角的精确位置对人脸进行旋转和双向尺寸缩放处理.实验结果表明,该算法对特征点定位准确,能够更加精确地对人脸进行归一化处理.

关键词: 归一化, 人脸识别, 嘴角定位, 局部梯度算子

Abstract:

This paper presents a novel face normalization method by integrating the location of eyes and the corner of the mouth for the normalization in the vertical direction. In the first step, the regions of eyes and the mouth are roughly detected by making use of Adaboost all through the whole face image. The Grey Integral Projection and the improved Local Gradient Operator algorithms are then applied to find the accurate positions of the eyes and the corner of the mouth in the face image, respectively. Finally, the face image is rotated and zoomed according to the relative position of eyes and the mouth in vertical and horizontal directions. Experimental results demonstrate that the proposed method can locate the feature points accurately and present better normalization performance by introducing the zoom criterion in the vertical direction.

Key words: face normalization, face recognition, mouth corners location, local gradient operator

中图分类号: 

  • TP391