A Novel Dictionary Learning Model with PT-HLBP for Palmprint Recognition. (22nd November 2016)

• Record Type: Journal Article
• Authors: Guo, Xiumei; Zhou, Weidong
• Other Names: Tragoudas Spyros Academic Editor.
• Is Part Of: Journal of electrical and computer engineering. Volume 2016(2016)
• Publication Date: 2016-11-22
• Subjects: Computer engineering -- Periodicals; Electrical engineering -- Periodicals; 621.3905
• DOI: 10.1155/2016/6423834
• Languages: English
• ISSNs: 2090-0147

Abstract

Abstract : 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.