Application of quaternion wavelet and AdaBoost in face recognition
Wenxue Hong · Computer Engineering and Applications Journal · 2011
This paper proposes a face recognition method based on the Quaternion Wavelet Transform(QWT) magnitude/phase representation and AdaBoost.This recent transform is a near shift-invariant tight frame representation whose coefficients support a magnitude and three phases.The first two QWT phases encode the shifts of image features in the absolute horizontal/vertical coordinate system,while the third phase encodes edge orientation mixtures and textural information.The method preprocesses human face images,uses QWT to extract the wavelet coefficients of multi-orientation,and quaternion amplitude and three phases are computed.These quaternion amplitude and phase features are combined and AdaBoost is used to realize recognition.Experimental results on three face databases including Yale,ORL and FERET show that the method has higher recognition rates than AdaBoost and Gabor+AdaBoost.This method has much better recognizing result on FERET especially.Compared with Gabor wavelet features,QWT features are superior both in accuracy and computation complexity.