An Improved Multispectral Palmprint Recognition System Using Autoencoder with Regularized Extreme Learning Machine
Joint Authors
Al-Salman, Abdulmalik S.
Gumaei, Abdu
Sammouda, Rachid
Alsanad, Ahmed
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-05-27
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Multispectral palmprint recognition system (MPRS) is an essential technology for effective human identification and verification tasks.
To improve the accuracy and performance of MPRS, a novel approach based on autoencoder (AE) and regularized extreme learning machine (RELM) is proposed in this paper.
The proposed approach is intended to make the recognition faster by reducing the number of palmprint features without degrading the accuracy of classifier.
To achieve this objective, first, the region of interest (ROI) from palmprint images is extracted by David Zhang’s method.
Second, an efficient normalized Gist (NGist) descriptor is used for palmprint feature extraction.
Then, the dimensionality of extracted features is reduced using optimized AE.
Finally, the reduced features are fed to the RELM for classification.
A comprehensive set of experiments are conducted on the benchmark MS-PolyU dataset.
The results were significantly high compared to the state-of-the-art approaches, and the robustness and efficiency of the proposed approach are revealed.
American Psychological Association (APA)
Gumaei, Abdu& Sammouda, Rachid& Al-Salman, Abdulmalik S.& Alsanad, Ahmed. 2018. An Improved Multispectral Palmprint Recognition System Using Autoencoder with Regularized Extreme Learning Machine. Computational Intelligence and Neuroscience،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1130841
Modern Language Association (MLA)
Gumaei, Abdu…[et al.]. An Improved Multispectral Palmprint Recognition System Using Autoencoder with Regularized Extreme Learning Machine. Computational Intelligence and Neuroscience No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1130841
American Medical Association (AMA)
Gumaei, Abdu& Sammouda, Rachid& Al-Salman, Abdulmalik S.& Alsanad, Ahmed. An Improved Multispectral Palmprint Recognition System Using Autoencoder with Regularized Extreme Learning Machine. Computational Intelligence and Neuroscience. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1130841
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1130841