A novel 2d gabor wavelets window method for face recognition

Authors:
Lin Wang;Yongping Li;Hongzhou Zhang;Chengbo Wang
Affiliations:
Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai, China;Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai, China;Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai, China;Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai, China
Venue:
MRCS'06 Proceedings of the 2006 international conference on Multimedia Content Representation, Classification and Security
Year:
2006

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Abstract

This paper proposed a novel algorithm named 2D Gabor Wavelets Window (GWW) method. The GWW scans the image top left to bottom right to extract the local feature vectors (LFVs). A parametric feature vector is derived by downsampling and concatenating these LFVs for face representation and recognition. Compared with the Gabor Wavelets representation of the whole image, the total cost is reduced by maximum of 39% whilst the performance achieved better than the conventional PCA method when experimented on both the ORL and XM2VTSDB databases without any preprocessing.