Vein feature extraction using DT-CNNs
(2006) 10th International Workshop on Cellular Neural Networks and their Applications (CNNA) 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:
https://lup.lub.lu.se/record/603786
- author
- Malki, Suleyman LU ; Fuqiang, Y and Spaanenburg, Lambert LU
- organization
- publishing date
- 2006
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Field Programmable Gate Arrays, Discrete-Time Cellular Neural Networks, Vein Feature Extraction.
- host publication
- 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)
- conference dates
- 2006-08-28 - 2006-08-30
- 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
- 2016-04-04 09:58:54
- date last changed
- 2022-01-29 19:37:24
@inproceedings{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}}, booktitle = {{10th International Workshop on Cellular Neural Networks and Their Applications, 2006. CNNA '06.}}, isbn = {{1-4244-0640-4}}, keywords = {{Field Programmable Gate Arrays; Discrete-Time Cellular Neural Networks; Vein Feature Extraction.}}, language = {{eng}}, pages = {{307--312}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Vein feature extraction using DT-CNNs}}, url = {{http://dx.doi.org/10.1109/CNNA.2006.341650}}, doi = {{10.1109/CNNA.2006.341650}}, year = {{2006}}, }