Independent circularly symmetrical Gabor feature for face recognition
Guoxia Sun · Computer Engineering and Applications Journal · 2011
This paper presents a new feature extraction method for face recognition using 2D Circularly Symmetrical Gabor Transform(2DCSGT) and Independent Component Analysis(ICA).A circularly symmetrical Gabor feature vector is derived from a set of downsampled circularly symmetrical Gabor wavelet representations of face images.The dimension of the circularly symmetrical Gabor feature vector is reduced by means of Principal Component Analysis(PCA).Independent Circularly Symmetrical Gabor Features(ICSGF) are defined based on Independent Component Analysis.To show the validity of the proposed method,it is applied to face recognition on the ORL,YALE and FERET databases.In particular,the ICSGF method achieves 99.5% correct face recognition accuracy for ORL database,93.33% accuracy for Yale database and 97.14% accuracy for FERET database.Experimental results show that the algorithm is feasible and effective for face recognition.