Face recognition via two dimensional locality preserving projection in frequency domain
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
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In this paper, two-dimensional locality preserving projections (2DLPP) was proposed to extract Gabor features for face recognition. 2DPCA is first utilized for dimensionality reduction of Gabor feature space, which is implemented directly from 2D image matrices. The objective of 2DLPP is to preserve the local structure of the image space by detecting the intrinsic manifold structure. In our method, an original image is convolved with Gabor filters corresponding to various orientations and scales to give its Gabor representation. 2DPCA is implemented in the row direction prior to 2DLPP in the column direction. Experiments are conducted on the ORL face database, which shows higher recognition performance of the proposed methods. The top recognition rate can reach 95.5%.