Letters: Diagonal Fisher linear discriminant analysis for efficient face recognition

Authors:
S. Noushath;G. Hemantha Kumar;P. Shivakumara
Affiliations:
Department of Studies in Computer Science, University of Mysore, Manasagangothri, Mysore 570006, Karnataka, India;Department of Studies in Computer Science, University of Mysore, Manasagangothri, Mysore 570006, Karnataka, India;Department of Computer Science, School of Computing, National University of Singapore, 3 Science, Drive 2, Singapore 117543, Singapore
Venue:
Neurocomputing
Year:
2006

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Abstract

In this paper, a novel subspace method called diagonal Fisher linear discriminant analysis (DiaFLD) is proposed for face recognition. Unlike conventional principal component analysis and FLD, DiaFLD directly seeks the optimal projection vectors from diagonal face images without image-to-vector transformation. The advantage of the DiaFLD method over the standard 2-dimensional FLD (2DFLD) method is, the former seeks optimal projection vectors by interlacing both row and column information of images while the latter seeks the optimal projection vectors by using only row information of images. Our test results show that the DiaFLD method is superior to standard 2DFLD method and some existing well-known methods.