计算机科学 ›› 2019, Vol. 46 ›› Issue (10): 307-310.doi: 10.11896/jsjkx.190300061

• 图形图像与模式识别 • 上一篇    下一篇

基于自适应加权子模式判别邻域投影的人脸识别方法

杨柳1, 陈丽敏1, 易玉根2   

  1. (牡丹江师范学院计算机与信息技术学院 黑龙江 牡丹江157012)1
    (江西师范大学软件学院 南昌 330022)2
  • 收稿日期:2019-03-15 修回日期:2019-05-22 出版日期:2019-10-15 发布日期:2019-10-21
  • 通讯作者: 杨柳(1969-),教授,硕士生导师,主要研究方向为信息检索、机器学习,E-mail:yshjl@126.com。
  • 作者简介:陈丽敏(1970-),博士,教授,硕士生导师,主要研究方向为数据挖掘、机器学习;易玉根(1986-),博士,讲师,主要研究方向为计算机视觉、图像处理、模式识别与机器学习。
  • 基金资助:
    本文受黑龙江省自然科学基金项目(LH2019F051)资助。

Face Recognition Method Based on Adaptively Weighted Sub-pattern Discriminant Neighborhood Projection

YANG Liu1, CHEN Li-min1, YI Yu-gen2   

  1. (School of Computer Science and Information Technology,Mudanjiang Normal University,Mudanjiang,Heilongjiang 157012,China)1
    (School of Software,Jiangxi Normal University,Nanchang 330022,China)2
  • Received:2019-03-15 Revised:2019-05-22 Online:2019-10-15 Published:2019-10-21

摘要: 人脸识别是图像处理和模式识别中的研究热点问题之一,对此,文中提出了一种基于自适应加权子模式判别邻域投影的人脸识别方法。该方法首先将人脸图像划分成较小的人脸图像块,并将相同位置的子图像构建成子模式集;其次,为了提高低维特征的判别能力,同时考虑数据的局部结构信息和类别标签信息,对于每个子模式集,构建一个局部判别邻域图;最后,考虑不同子模式集对人脸图像识别的贡献,引入一个非负权值向量结合所有子模式集的局部散度矩阵,以找出同幅人脸图像的不同子图像之间的互补信息。实验结果表明,相比于其他方法,所提方法的性能更优。

关键词: 标签信息, 局部结构, 人脸识别, 子模式, 自适应加权

Abstract: Face recognition is one of the hot topics in the image processing and pattern recognition,an adaptively weighted sub-pattern discriminant neighborhood projection method was proposed for face recognition.Firstly,the face images are divided into several small blocks,and the sub images with same position are used to construct the sub-pattern set.Then,in order to improve the discrimination ability of low dimensional features,the local data structure information and the label information of each sub pattern set are employed to construct a local discriminant neighborhood graph.Finally,for taking different contribution of different sub-pattern into account,a non negative weight vector is introduced to combine with the local scatter matrices of all sub-pattern sets,in order to find out the complementary information between different sub-image of the same faceimage.The experimental results show that the proposed method is superior to other methods.

Key words: Adaptive weighting, Face recognition, Label information, Local structure, Sub-pattern

中图分类号: 

  • TP391.4
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