计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (13): 191-194.

• 图形、图像、模式识别 • 上一篇    下一篇

2D双树复小波与判别共同矢量结合的人脸认证

龚卫国1，刘燕飞1，杨利平1，肖 虹2，黄宜民2   

  1. 1.重庆大学 光电技术及系统教育部重点实验室，重庆 400044
    2.重庆建设工业有限责任公司 国防科技工业技术中心，重庆 400054
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-05-01 发布日期:2011-05-01

Fusion of 2D dual-tree complex wavelet transform and discriminative common vector for face verification

GONG Weiguo1，LIU Yanfei1，YANG Liping1，XIAO Hong2，HUANG Yimin2   

  1. 1.Key Lab for Optoelectronic Technology & System of the Education Ministry，Chongqing University，Chongqing 400044，China
    2.Science & Technology Center of National Defense Industry，Chongqing Jianshe Industry Co.，Ltd，Chongqing 400054，China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-05-01 Published:2011-05-01

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摘要： 针对人脸认证中的小样本问题和Gabor小波特征提取的不足，提出一种有效的人脸认证算法。对预处理后的图像进行2D双树复小波变换，将每幅图像不同尺度下多个方向的小波系数幅值作为特征矢量，表征重要的局部信息；将提取的特征矢量向判别共同矢量空间投影，进一步提取具有判别能力的特征，同时进行降维；根据用户特定阈值进行认证。ORL人脸库和FERET子库上的实验结果验证了算法的有效性。

关键词: 2D双树复小波变换, 判别共同矢量, 人脸认证, 特征提取

Abstract: To deal with the small sample size problem and overcome disadvantage of Gabor feature extraction in face verification，an efficient algorithm based on the Discriminative Common Vector（DCV） and 2D Dual-Tree Complex Wavelet Transform（2D DT-CWT） is proposed.The 2D DT-CWT is utilized to filter the preprocessed image，and then the amplitude coefficients of different scales and different orientations are lexicographically ordered to form its feature vector.The dimensionality of 2D DT-CWT features is usually high，so features are projected into DCV subspace to reduce the dimensionality and enhance the discriminative ability.Finally，verification is accomplished according to client-specific threshold.The experimental results on ORL database and FERET subset demonstrate the effectiveness of the proposed algorithm.

Key words: 2D dual-tree complex wavelet transform, discriminative common vector, face verification, feature extraction

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