Letters: Diagonal and secondary diagonal locality preserving projection for object recognition

Authors:
Veerabhadrappa;Lalitha Rangarajan
Affiliations:
Department of Studies in Computer Science, University of Mysore, Manasagangothri, Mysore 570 006, India and Department of Computer Science, University College, Mangalore 575 001, India;Department of Studies in Computer Science, University of Mysore, Manasagangothri, Mysore 570 006, India
Venue:
Neurocomputing
Year:
2010

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Abstract

In this paper, the variants of Two Dimensional Locality Preserving Projection (2DLPP) namely Diagonal Locality Preserving Projection (DiaLPP) and Secondary Diagonal Locality Preserving Projection (SDiaLPP) are proposed as the new dimensionality reduction techniques. The 2DLPP method seeks optimal projection vectors by using the row information of the image and the Alternate 2DLPP method seeks optimal projection vectors by using the column information of the image, whereas the DiaLPP seeks optimal projection vectors by interlacing both the rows and column information of the images. Experimental results on subset of COIL object database show that the proposed methods achieves higher recognition rate than 2DLPP and Diagonal Principal Component Analysis(DiaPCA).