DocumentCode :
2859868
Title :
Hand veins feature extraction based on morphology and Cellular Neural Network
Author :
Deng, Jinpeng ; Zhang, Yanzhi
Author_Institution :
Sch. of Software, Shenyang Univ. of Technol., Shenyang, China
Volume :
14
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
Vein pattern recognition is an emerging contactless near infrared biometric technology. It has drawn wide attention in recent years. A fingerprint-based identification system using Cellular Neural Networks has already been proposed. Discrete-time Cellular Neural Network (DT-CNN) is introduced into binary morphology owing to the natural corresponding relationship between them, and then the morphology operation is transformed into multi-layer DT-CNN under some specific template. Multi-layer DT-CNN is transformed into Monolayer DT-CNN by optimizing design to reduce the complexity of the operation. The method has a better performance and converges quickly.
Keywords :
authorisation; biometrics (access control); blood vessels; cellular neural nets; feature extraction; infrared imaging; binary morphology; contactless near infrared biometric technology; fingerprint based identification system; hand veins feature extraction; multilayer discrete time cellular neural network; vein pattern recognition; Biomedical imaging; Computational modeling; Gray-scale; IEEE Lasers and Electro-Optics Society; Immune system; Pixel; Veins; Cellular Neural Network; hand vein recognition; image processingformatting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5622355
Filename :
5622355
Link To Document :
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