Face recognition based two dimensional locality preserving projection in frequency domain

In this paper we propose a new face recognition method based on two-dimensional locality preserving projections (2DLPP) in frequency domain. For this purpose, we first introduce the two-dimensional locality preserving projections. Then the 2DLPP in frequency domain is proposed for face recognition....

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Main Authors: Lu, C., Liu, X., Liu, Wan-Quan
Format: Journal Article
Published: Elsevier BV 2012
Online Access:http://hdl.handle.net/20.500.11937/9608
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author Lu, C.
Liu, X.
Liu, Wan-Quan
author_facet Lu, C.
Liu, X.
Liu, Wan-Quan
author_sort Lu, C.
building Curtin Institutional Repository
collection Online Access
description In this paper we propose a new face recognition method based on two-dimensional locality preserving projections (2DLPP) in frequency domain. For this purpose, we first introduce the two-dimensional locality preserving projections. Then the 2DLPP in frequency domain is proposed for face recognition. In fact, two dimensional discrete cosine transform (2DDCT) is used as a pre-processing step and it transforms the face image signals from spatial domain into frequency domain aiming to reduce the effects of illumination and pose changes in face recognition. Then 2DLPP is applied on the upper left corner blocks of the 2DDCT transformed matrices, which represent main energy of each original image. For demonstration, the Olivetti Research Laboratory (ORL), YALE, FERET and YALE-B face datasets are used to compare the proposed approach with the conventional 2DLPP and 2DDCT approaches with the nearest neighborhood (NN) classifier. The experimental results show that the proposed 2DLPP in frequency domain is superior over the 2DLPP in spatial domain and 2DDCT itself in frequency domain.
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institution Curtin University Malaysia
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publishDate 2012
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spelling curtin-20.500.11937-96082017-09-13T14:50:15Z Face recognition based two dimensional locality preserving projection in frequency domain Lu, C. Liu, X. Liu, Wan-Quan In this paper we propose a new face recognition method based on two-dimensional locality preserving projections (2DLPP) in frequency domain. For this purpose, we first introduce the two-dimensional locality preserving projections. Then the 2DLPP in frequency domain is proposed for face recognition. In fact, two dimensional discrete cosine transform (2DDCT) is used as a pre-processing step and it transforms the face image signals from spatial domain into frequency domain aiming to reduce the effects of illumination and pose changes in face recognition. Then 2DLPP is applied on the upper left corner blocks of the 2DDCT transformed matrices, which represent main energy of each original image. For demonstration, the Olivetti Research Laboratory (ORL), YALE, FERET and YALE-B face datasets are used to compare the proposed approach with the conventional 2DLPP and 2DDCT approaches with the nearest neighborhood (NN) classifier. The experimental results show that the proposed 2DLPP in frequency domain is superior over the 2DLPP in spatial domain and 2DDCT itself in frequency domain. 2012 Journal Article http://hdl.handle.net/20.500.11937/9608 10.1016/j.neucom.2011.08.045 Elsevier BV restricted
spellingShingle Lu, C.
Liu, X.
Liu, Wan-Quan
Face recognition based two dimensional locality preserving projection in frequency domain
title Face recognition based two dimensional locality preserving projection in frequency domain
title_full Face recognition based two dimensional locality preserving projection in frequency domain
title_fullStr Face recognition based two dimensional locality preserving projection in frequency domain
title_full_unstemmed Face recognition based two dimensional locality preserving projection in frequency domain
title_short Face recognition based two dimensional locality preserving projection in frequency domain
title_sort face recognition based two dimensional locality preserving projection in frequency domain
url http://hdl.handle.net/20.500.11937/9608