[1]张琳梅,张雪峰.曲波变换和独立分量分析的人脸识别[J].南京理工大学学报(自然科学版),2017,41(01):74.[doi:10.14177/j.cnki.32-1397n.2017.41.01.010]
 Zhang Linmei,Zhang Xuefeng.Face recognition based on curvelet transform and independentcomponent analysis[J].Journal of Nanjing University of Science and Technology,2017,41(01):74.[doi:10.14177/j.cnki.32-1397n.2017.41.01.010]
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曲波变换和独立分量分析的人脸识别()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
41卷
期数:
2017年01期
页码:
74
栏目:
出版日期:
2017-02-28

文章信息/Info

Title:
Face recognition based on curvelet transform and independentcomponent analysis
文章编号:
1005-9830(2017)01-0074-06
作者:
张琳梅张雪峰
信阳农林学院 信息工程学院,河南 信阳 464000
Author(s):
Zhang LinmeiZhang Xuefeng
College of Information Engineering,Xinyang College of Agriculture and Forestry,Xinyang 464000,China
关键词:
人脸识别 特征提取 曲波变换 独立分量分析 小波变换
Keywords:
face recognition feature extraction curvelet transform independent component analysis wavelet transform
分类号:
TP391
DOI:
10.14177/j.cnki.32-1397n.2017.41.01.010
摘要:
为了获得更高的人脸识别率,加快人脸识别速度,提出了曲波变换和独立分量分析相融合的人脸识别算法。首先采用曲波变换对人脸图像进行处理,得到尺度和方向上的曲波系数,并对曲波系数进行加权和融合,然后采用独立分量分析选择对人脸识别具有重要贡献的特征,减少冗余特征,加快人脸分类器的识别速度,最后采用最小二乘支持向量机建立人脸识别的分类器,并采用经典人脸数据库进行仿真分析。结果表明,该文算法的人脸平均识别率超过了95%,平均识别时间完全可以满足人脸在线识别要求。
Abstract:
In order to obtain high recognition rate and accelerate the speed of face recognition,a face recognition algorithm is proposed by combining curvelet transform and independent component analysis.Firstly,face images are processed by curvelet transform and get curvelet coefficients in scale and direction.The obtained curvelet coefficients are weighted and fused and then independent component analysis is used to select the features which have important contributions,reducing the feature dimension to accelerate the recognition speed of face classifier.Finally,least square support vector machine is used to establish face recognition classifier,and the classical face database is used to test the performance of face recognition.The experimental results show that the average recognition rate of the proposed algorithm is more than 95%,and the average recognition time can meet the requirements of face recognition.

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备注/Memo

备注/Memo:
收稿日期:2016-04-18 修回日期:2016-11-10
基金项目:河南省教育厅科学技术研究重点项目(16A520091)
作者简介:张琳梅(1981-),女,硕士,讲师,主要研究方向:图形图像处理,软件应用与开发,E-mail:zhang123zlm@sina.com。
引文格式:张琳梅,张雪峰.曲波变换和独立分量分析的人脸识别[J].南京理工大学学报,2017,41(1):74-79.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2017-02-28