Hand Veins Feature Extraction using DTCNNs
(2006) SSoCC (Swedish System-on-Chip Conference), 2006- Abstract
- Biometric identification is an important security application that requires non-intrusive capture and real-time processing. Recently, identification by vein patterns has been suggested as a promising alternative. In this paper we study the potential of Cellular Neural Networks implemented on a Field-Programmable Gate Array to handle the person identification based on hand veins in real time. With a minimal distance measure of 2 pixels for False Feature Elimination, it has a True Acceptance Rate of 65% and a False Rejection Rate of 5%. The performance rises drastically with increasing pixel distance and will therefore be camera sensitive.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/603766
- 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
- host publication
- Proceedings SSoCC
- conference name
- SSoCC (Swedish System-on-Chip Conference), 2006
- conference location
- Kålmården, Sweden
- conference dates
- 2006-05-04 - 2006-05-05
- language
- English
- LU publication?
- yes
- id
- d05c7aff-8917-4655-b4d8-63d9b2e1b9db (old id 603766)
- date added to LUP
- 2016-04-04 13:20:24
- date last changed
- 2018-11-21 21:13:19
@inproceedings{d05c7aff-8917-4655-b4d8-63d9b2e1b9db, abstract = {{Biometric identification is an important security application that requires non-intrusive capture and real-time processing. Recently, identification by vein patterns has been suggested as a promising alternative. In this paper we study the potential of Cellular Neural Networks implemented on a Field-Programmable Gate Array to handle the person identification based on hand veins in real time. With a minimal distance measure of 2 pixels for False Feature Elimination, it has a True Acceptance Rate of 65% and a False Rejection Rate of 5%. The performance rises drastically with increasing pixel distance and will therefore be camera sensitive.}}, author = {{Malki, Suleyman and Fuqiang, Y and Spaanenburg, Lambert}}, booktitle = {{Proceedings SSoCC}}, language = {{eng}}, title = {{Hand Veins Feature Extraction using DTCNNs}}, year = {{2006}}, }