计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (13): 179-181.DOI: 10.3778/j.issn.1002-8331.2009.13.052

• 图形、图像、模式识别 • 上一篇    下一篇

融合小波与2D PCA的贝叶斯人脸识别

牛丽平,郑延斌,李新源,窦育强   

  1. 河南师范大学 计算机与信息技术学院,河南 新乡 453007
  • 收稿日期:2008-12-08 修回日期:2009-02-18 出版日期:2009-05-01 发布日期:2009-05-01
  • 通讯作者: 牛丽平

Bayesian face recognition using wavelet transform and 2DPCA

NIU Li-ping,ZHENG Yan-bin,LI Xin-yuan,DOU Yu-qiang   

  1. College of Computer and Information Technology,Henan Normal University,Xinxiang,Henan 453007,China
  • Received:2008-12-08 Revised:2009-02-18 Online:2009-05-01 Published:2009-05-01
  • Contact: NIU Li-ping

摘要: 提出了融合小波和2DPCA进行贝叶斯人脸识别的方法。对原始图像采用小波分解后,利用2DPCA计算人脸的特征矢量空间。首先对低频子图进行贝叶斯人脸识别,然后对得分前五名的图像再次利用高频子图并行进行识别,通过加权排序得到最后结果。实验表明,与传统的方法相比较,该方法降低了运算量,提高了识别率。

Abstract: A novel Bayesian approach to face recognition based on wavelet transform and 2DPCA is proposed.The original image is decomposed into low frequency and high frequency sub-band images by applying wavelet transform,the 2DPCA algorithm is used to compute the eigenvector space of the face.Firstly Bayesian approach is used to the low-frequency sub-band,secondly for the selected top 5 match faces,Bayesian recognition is parallel processed using these high frequency sub-band images.The face recognition result is gained through weigh-adding arraying.Its efficiency and superiority are clarified by comparative experiment on a subset of FERET face data.