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Vein feature extraction using DT-CNNs

Malki, Suleyman LU ; Fuqiang, Y and Spaanenburg, Lambert LU (2006) 10th International Workshop on Cellular Neural Networks and their Applications (CNNA) In 10th International Workshop on Cellular Neural Networks and Their Applications, 2006. CNNA '06. p.307-312
Abstract
Biometric identification is an important security application that requires non-intrusive capture and real-time processing. Security systems based on fingerprints and retina patterns have been widely developed, but can be easily falsified. Recently, identification by vein patterns has been suggested as a promising alternative. In this paper an existing feature extraction algorithm, that has been developed for fingerprint recognition, is adapted for vein recognition. The algorithm has been implemented as cellular neural network and realized on a field-programmable gate-array. The detection quality is comparable to the 99.45% reached earlier by direct image comparison, but suffers from the image resolution sensitivity of the false feature... (More)
Biometric identification is an important security application that requires non-intrusive capture and real-time processing. Security systems based on fingerprints and retina patterns have been widely developed, but can be easily falsified. Recently, identification by vein patterns has been suggested as a promising alternative. In this paper an existing feature extraction algorithm, that has been developed for fingerprint recognition, is adapted for vein recognition. The algorithm has been implemented as cellular neural network and realized on a field-programmable gate-array. The detection quality is comparable to the 99.45% reached earlier by direct image comparison, but suffers from the image resolution sensitivity of the false feature elimination (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Field Programmable Gate Arrays, Discrete-Time Cellular Neural Networks, Vein Feature Extraction.
in
10th International Workshop on Cellular Neural Networks and Their Applications, 2006. CNNA '06.
pages
307 - 312
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
10th International Workshop on Cellular Neural Networks and their Applications (CNNA)
external identifiers
  • WOS:000245392200066
  • Scopus:47549110002
ISBN
1-4244-0640-4
DOI
10.1109/CNNA.2006.341650
language
English
LU publication?
yes
id
bd331a72-b1d6-410f-a9fc-ee315fc9ed25 (old id 603786)
date added to LUP
2007-12-04 14:02:18
date last changed
2016-10-13 04:37:16
@misc{bd331a72-b1d6-410f-a9fc-ee315fc9ed25,
  abstract     = {Biometric identification is an important security application that requires non-intrusive capture and real-time processing. Security systems based on fingerprints and retina patterns have been widely developed, but can be easily falsified. Recently, identification by vein patterns has been suggested as a promising alternative. In this paper an existing feature extraction algorithm, that has been developed for fingerprint recognition, is adapted for vein recognition. The algorithm has been implemented as cellular neural network and realized on a field-programmable gate-array. The detection quality is comparable to the 99.45% reached earlier by direct image comparison, but suffers from the image resolution sensitivity of the false feature elimination},
  author       = {Malki, Suleyman and Fuqiang, Y and Spaanenburg, Lambert},
  isbn         = {1-4244-0640-4},
  keyword      = {Field Programmable Gate Arrays,Discrete-Time Cellular Neural Networks,Vein Feature Extraction.},
  language     = {eng},
  pages        = {307--312},
  publisher    = {ARRAY(0x99d4238)},
  series       = {10th International Workshop on Cellular Neural Networks and Their Applications, 2006. CNNA '06.},
  title        = {Vein feature extraction using DT-CNNs},
  url          = {http://dx.doi.org/10.1109/CNNA.2006.341650},
  year         = {2006},
}