A Novel Dictionary Learning Model with PT-HLBP for Palmprint Recognition

A novel projective dictionary pair learning (PDPL) model with statistical local features for palmprint recognition is proposed. Pooling technique is used to enhance the invariance of hierarchical local binary pattern (PT-HLBP) for palmprint feature extraction. PDPL is employed to learn an analysis d...

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Main Authors: Xiumei Guo, Weidong Zhou
Format: Article
Language:English
Published: Wiley 2016-01-01
Series:Journal of Electrical and Computer Engineering
Online Access:http://dx.doi.org/10.1155/2016/6423834
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author Xiumei Guo
Weidong Zhou
author_facet Xiumei Guo
Weidong Zhou
author_sort Xiumei Guo
collection DOAJ
description A novel projective dictionary pair learning (PDPL) model with statistical local features for palmprint recognition is proposed. Pooling technique is used to enhance the invariance of hierarchical local binary pattern (PT-HLBP) for palmprint feature extraction. PDPL is employed to learn an analysis dictionary and a synthesis dictionary which are utilized for image discrimination and representation. The proposed algorithm has been tested by the Hong Kong Polytechnic University (PolyU) database (v2) and ideal recognition accuracy can be achieved. Experimental results indicate that the algorithm not only greatly reduces the time complexity in training and testing phase, but also exhibits good robustness for image rotation and corrosion.
format Article
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institution Kabale University
issn 2090-0147
2090-0155
language English
publishDate 2016-01-01
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record_format Article
series Journal of Electrical and Computer Engineering
spelling doaj-art-9ff4cee2e86b4b04812ac569aeecd14f2025-02-03T01:25:42ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552016-01-01201610.1155/2016/64238346423834A Novel Dictionary Learning Model with PT-HLBP for Palmprint RecognitionXiumei Guo0Weidong Zhou1School of Information Science and Engineering, Shandong University, Jinan 250100, ChinaSchool of Information Science and Engineering, Shandong University, Jinan 250100, ChinaA novel projective dictionary pair learning (PDPL) model with statistical local features for palmprint recognition is proposed. Pooling technique is used to enhance the invariance of hierarchical local binary pattern (PT-HLBP) for palmprint feature extraction. PDPL is employed to learn an analysis dictionary and a synthesis dictionary which are utilized for image discrimination and representation. The proposed algorithm has been tested by the Hong Kong Polytechnic University (PolyU) database (v2) and ideal recognition accuracy can be achieved. Experimental results indicate that the algorithm not only greatly reduces the time complexity in training and testing phase, but also exhibits good robustness for image rotation and corrosion.http://dx.doi.org/10.1155/2016/6423834
spellingShingle Xiumei Guo
Weidong Zhou
A Novel Dictionary Learning Model with PT-HLBP for Palmprint Recognition
Journal of Electrical and Computer Engineering
title A Novel Dictionary Learning Model with PT-HLBP for Palmprint Recognition
title_full A Novel Dictionary Learning Model with PT-HLBP for Palmprint Recognition
title_fullStr A Novel Dictionary Learning Model with PT-HLBP for Palmprint Recognition
title_full_unstemmed A Novel Dictionary Learning Model with PT-HLBP for Palmprint Recognition
title_short A Novel Dictionary Learning Model with PT-HLBP for Palmprint Recognition
title_sort novel dictionary learning model with pt hlbp for palmprint recognition
url http://dx.doi.org/10.1155/2016/6423834
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AT weidongzhou anoveldictionarylearningmodelwithpthlbpforpalmprintrecognition
AT xiumeiguo noveldictionarylearningmodelwithpthlbpforpalmprintrecognition
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