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|Title:||Multi-dictionary based collaborative representation : with applications to 3D ear and 3D palmprint identification||Authors:||Zhang, L
|Issue Date:||2019||Publisher:||Hindawi Publishing Corporation||Source:||Mathematical problems in engineering, 2019, v. 2019, 6957415 How to cite?||Journal:||Mathematical problems in engineering||Abstract:||Biometrics based personal authentication has been found to be an effective method for recognizing, with high confidence, a person's identity. With the emergence of reliable and inexpensive 3D scanners, recent years have witnessed a growing interest in developing 3D biometrics systems. As a commonsense, matching algorithms are crucial for such systems. In this paper, we focus on investigating identification methods for two specific 3D biometric identifiers, 3D ear and 3D palmprint. Specifically, we propose a Multi-Dictionary based Collaborative Representation (MDCR) framework for classification, which can reduce the negative effects aroused by some local regions. With MDCR, a range map is partitioned into overlapping blocks and, from each block, a feature vector is extracted. At the dictionary construction stage, feature vectors from blocks having the same locations in gallery samples can form a dictionary and, accordingly, multiple dictionaries are obtained. Given a probe sample, by coding its each feature vector on the corresponding dictionary, multiple class labels can be obtained and then we use a simple majority-based voting scheme to make the final decision. In addition, a novel patch-wise and statistics-based feature extraction scheme is proposed, combining the range image's local surface type information and local dominant orientation information. The effectiveness of the proposed approach has been corroborated by extensive experiments conducted on two large-scale and widely-used benchmark datasets, the UND Collection J2 3D ear dataset and the PolyU 3D palmprint dataset. To make the results reproducible, we have publicly released the source code.||URI:||http://hdl.handle.net/10397/80932||ISSN:||1024-123X||EISSN:||1563-5147||DOI:||10.1155/2019/6957415||Rights:||Copyright © 2019 Lin Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The following publication Lin Zhang, Xining Zhu, and Lida Li, “Multi-Dictionary Based Collaborative Representation: With Applications to 3D Ear and 3D Palmprint Identification,” Mathematical Problems in Engineering, vol. 2019, Article ID 6957415, 13 pages, 2019 is available at https://doi.org/10.1155/2019/6957415
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Citations as of Oct 15, 2019
Citations as of Oct 15, 2019
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