A real time fingerprint identification
system based on the AFS8600 sensor
and the C6713 DSP processor

dc.contributor.author	Τσέλιος, Κωνσταντίνος	el
dc.contributor.author	Ζώης, Ηλίας Ν.	el
dc.contributor.author	Λιβανός, Νικόλαος-Αντώνιος Ι.	el
dc.contributor.author	Νασιόπουλος, Αθανάσιος Α.	el
dc.date.accessioned	2015-01-09T13:00:14Z
dc.date.available	2015-01-09T13:00:14Z
dc.date.issued	2015-01-09
dc.identifier.uri	http://hdl.handle.net/11400/3620
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://www.wiley-vch.de/publish/dt/	en
dc.subject	Electric Field technology
dc.subject	Images
dc.subject	Ηλεκτρικό πεδίο τεχνολογίας
dc.subject	Εικόνες
dc.title	A real time fingerprint identification system based on the AFS8600 sensor and the C6713 DSP processor	en
heal.type	journalArticle
heal.classification	Electrical engineering
heal.classification	Electronics
heal.classification	Ηλεκτρολογική μηχανική
heal.classification	Ηλεκτρονική
heal.classificationURI	http://skos.um.es/unescothes/C01311
heal.classificationURI	http://zbw.eu/stw/descriptor/10455-2
heal.classificationURI	N/A-Ηλεκτρολογική μηχανική
heal.classificationURI	N/A-Ηλεκτρονική
heal.identifier.secondary	DOI 10.1002/pssc.200780150
heal.language	en
heal.access	forever
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Ηλεκτρονικών Μηχανικών Τ.Ε.	el
heal.publicationDate	2008
heal.bibliographicCitation	Tselios, K., Zois, E., Livanos, N. and Nassiopoulos, A. (September 2008). A real time fingerprint identification system based on the AFS8600 sensor and the C6713 DSP processor. Physica status solidi (c). 5(12). pp. 3846-3849. Wiley-VCH Verlag GmbH & Co. KGaA. Available from: http://www.readcube.com/ [Accessed 16/09/2008]	en
heal.abstract	In this paper, a fingerprint pre-process and identification algorithm is implemented using the TMS320C6713 DSP starter kit (DSK) module, along with the Authentec AFS 8600 fingerprint sensor. Database: Acquisition is performed using a solid state sensor. The sensor postulates emerge from the theory of the Electric Field technology. Method: Images are first subjected to a frequency and orientation processing. This is achieved using Gabor-based filters. This processing has been optimized and implemented on the DSP system. A new method has been developed in order to extract the feature vector of the fingerprint image. A grid, centered at the corepoint of the image, is applied to the fingerprint image in order to derive local information. Classification algorithms are developed, which include training as well as evaluating phase. The types of classifiers used were based on the Bayesian approach along with the K-nearest neighbour. Results: An identification accuracy of 90% was achieved which is comparable to other procedures described in the literature. Conclusion: The combination of a fingerprint processing and identification algorithm using a low cost sensor and DSP module has been presented.	en
heal.publisher	Wiley-VCH Verlag GmbH & Co. KGaA	en
heal.journalName	Physica status solidi (c)	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true