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Hand Recognition Using Thermal Image and Extension Neural Network
Author
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-10-17
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Hand recognition is one of the popular biometry methods for access control systems.
In this paper, a new scheme for personal recognition using thermal images of the hand and an extension neural network (ENN) is presented.
The features of the recognition system are extracted from gray level hand images, which are taken by an infrared camera.
The main advantage of the thermal image is that it can reduce errors and noise in the features extracted stage, which is most important to increase the accuracy of recognition systems.
Moreover, a new recognition method based on the ENN is proposed to perform the core functions of the hand recognition system.
The proposed ENN-based recognition method also permits rapid adaptive processing for a new pattern, as it only tunes the boundaries of classified features or adds a new neural node.
It is feasible to implement the proposed method on a Microcomputer for a portable personal recognition device.
From the tested examples, the proposed method has a significantly high degree of recognition accuracy and shows good tolerance to errors added.
American Psychological Association (APA)
Wang, Meng-Hui. 2011. Hand Recognition Using Thermal Image and Extension Neural Network. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-15.
https://search.emarefa.net/detail/BIM-1002224
Modern Language Association (MLA)
Wang, Meng-Hui. Hand Recognition Using Thermal Image and Extension Neural Network. Mathematical Problems in Engineering No. 2012 (2012), pp.1-15.
https://search.emarefa.net/detail/BIM-1002224
American Medical Association (AMA)
Wang, Meng-Hui. Hand Recognition Using Thermal Image and Extension Neural Network. Mathematical Problems in Engineering. 2011. Vol. 2012, no. 2012, pp.1-15.
https://search.emarefa.net/detail/BIM-1002224
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1002224