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A Novel Dictionary Learning Model with PT-HLBP for Palmprint Recognition
Joint Authors
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-11-22
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Information Technology and Computer Science
Abstract EN
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.
American Psychological Association (APA)
Guo, Xiumei& Zhou, Weidong. 2016. A Novel Dictionary Learning Model with PT-HLBP for Palmprint Recognition. Journal of Electrical and Computer Engineering،Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1108463
Modern Language Association (MLA)
Guo, Xiumei& Zhou, Weidong. A Novel Dictionary Learning Model with PT-HLBP for Palmprint Recognition. Journal of Electrical and Computer Engineering No. 2016 (2016), pp.1-7.
https://search.emarefa.net/detail/BIM-1108463
American Medical Association (AMA)
Guo, Xiumei& Zhou, Weidong. A Novel Dictionary Learning Model with PT-HLBP for Palmprint Recognition. Journal of Electrical and Computer Engineering. 2016. Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1108463
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1108463