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Expressions invarient face recognition.

Author(s)
S. Ullah Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar, Pakistan
N. Ahmad Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar, Pakistan
K. Ahmad Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar, Pakistan
S. R. Hassnain Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar, Pakistan
Abstract
Variation of Facial expression is one of the most challenging factors in face recognition which significantly degrades the performance of the face recognition system. This paper presents a mechanism for reducing the high false positive rate in face recognition due to facial expression by using a novel Gaussian blurring and decimation algorithms. Extensive experimentation on complex images with variant facial expressions from the ORL dataset shows that removing the higher frequencies in the pre-processing step enhances the performance of eigenfaces algorithm by a significant amount i.e. from 93.75% to 96.5%.
Publication Details
Page(s) 419-422
DOI DOI not available
Published Journal: Sindh University Research Journal, Volume: 46, Issue: 4, Year: 2014

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