计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (27): 199-200.

• 工程与应用 • 上一篇    下一篇

基于Curvelet的人脸识别

张九龙1,张志禹2,屈小娥1,黄 薇2   

  1. 1.安理工大学 计算机科学与工程学院,西安 710048
    2.安理工大学 自动化与信息工程学院,西安 710048
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-09-21 发布日期:2007-09-21
  • 通讯作者: 张九龙

Face recognition based on Curvelet

ZHANG Jiu-long1,ZHANG Zhi-yu2,QU Xiao-e1,HUANG Wei2   

  1. 1.School of Computer Science and Engineering,Xi’an University of Technology,Xi’an 710048,China
    2.School of Automation and Information Engineering,Xi’an University of Technology,Xi’an 710048,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-09-21 Published:2007-09-21
  • Contact: ZHANG Jiu-long

摘要: 人脸的主要特征是曲线信息,提出了一种基于Curvelet变换的人脸识别算法。Curvelet变换在表达图像的曲线奇异性时,比小波变换和脊波变换能获得更稀疏的图像表示。在人脸识别中,用人脸的曲波系数来提取特征能更好地反映人脸的主要特征,文中使用支持向量机进行了识别。结果表明该方法比小波方法更有效。

关键词: 曲波变换, 人脸识别, 支持向量机, 小波变换

Abstract: A feature extraction method using Curvelet transform is presented for face recognition.Contrasting with wavelet transform,Curvelet transform directly takes edges as the basic representation elements and is anisotropic with strong direction.It is a multiresolution,band pass and directional function analysis method and is useful to represent the image edges and the curved singularities in images more efficiently.It yields a more sparse representation of the image than wavelet and ridgelet transform.In face recognition,the Curvelet coefficients can better represent the main features of the faces.The simulation shows that the proposed method is better than wavelet based method.

Key words: Curvelet transform, face recognition, Support Vector Machine(SVM), wavelet transform