Face recognition using wavelet transform and adaptive class-augmented PCA

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (35): 199-202.

• 图形、图像、模式识别 • Previous Articles Next Articles

Face recognition using wavelet transform and adaptive class-augmented PCA

ZHAO Dongjuan，LIANG Jiuzhen

College of IoT Engineering，Jiangnan University，Wuxi，Jiangsu 214122，China

Received:1900-01-01 Revised:1900-01-01 Online:2011-12-11 Published:2011-12-11

融合小波和自适应类增广PCA的人脸识别

赵冬娟，梁久祯

江南大学物联网工程学院，江苏无锡 214122

Abstract

Abstract: A face recognition approach based on wavelet transform and adaptive class-augmented PCA is proposed.Human face images are compressed using discrete wavelet transform.The features of low-frequency component are extracted by the adaptive class-augmented PCA.Different from traditional class-augmented PCA，the method does not require constructing the between-class information，so it is used more flexibly.Because of the wavelet transform，the recognition rate and time-consuming are both improved.Experiment on Yale and FERET shows the effectiveness of the algorithm.

Key words: face recognition, Class-Augmented Principal Component Analysis（CAPCA）, wavelet transform, feature extraction

摘要： 提出了融合小波变换和自适应类增广PCA（CAPCA）的人脸识别算法。用离散小波变换对人脸图像进行压缩，提取人脸的低频分量，再利用自适应的类增广PCA方法对小波变换后的人脸低频分量进行特征提取，从而达到进一步降维的目的。不同于类增广PCA，该方法不需要构建样本的类间信息，使用起来更加灵活，又由于小波变换对图像的预处理，算法的识别率和耗时也得到了进一步的优化。Yale和FERET库上的实验表明了该算法的有效性。

关键词: 人脸识别, 类增广PCA, 小波变换, 特征提取

ZHAO Dongjuan，LIANG Jiuzhen. Face recognition using wavelet transform and adaptive class-augmented PCA[J]. Computer Engineering and Applications, 2011, 47(35): 199-202.

赵冬娟，梁久祯. 融合小波和自适应类增广PCA的人脸识别[J]. 计算机工程与应用, 2011, 47(35): 199-202.

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Face recognition using wavelet transform and adaptive class-augmented PCA

融合小波和自适应类增广PCA的人脸识别

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