Fingerprint matching with self organizing maps

dc.contributor.author	Ουζούνογλου, Νικόλαος Α.	el
dc.contributor.author	Οικονομόπουλος, Θεόδωρος Λ.	el
dc.contributor.author	Ασβεστάς, Παντελής Α.	el
dc.contributor.author	Ματσόπουλος, Γεώργιος Κ.	el
dc.date.accessioned	2015-02-08T13:44:43Z
dc.date.available	2015-02-08T13:44:43Z
dc.date.issued	2015-02-08
dc.identifier.uri	http://hdl.handle.net/11400/5849
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://link.springer.com/	en
dc.subject	Αλληλογραφία εικόνας δακτυλικών αποτυπωμάτων
dc.subject	Distinctive points extraction
dc.subject	Fingerprint image correspondence
dc.subject	Διακριτικά σημεία εξόρυξης
dc.title	Fingerprint matching with self organizing maps	el
heal.type	bookChapter
heal.generalDescription	Proceedings	en
heal.classification	Medicine
heal.classification	Biomedical engineering
heal.classification	Ιατρική
heal.classification	Βιοϊατρική τεχνολογία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85014237
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Βιοϊατρική τεχνολογία
heal.identifier.secondary	DOI 10.1007/978-3-642-13039-7_77
heal.language	en
heal.access	campus
heal.recordProvider	Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε.	el
heal.publicationDate	2010
heal.bibliographicCitation	Ouzounoglou, N., Economopoulos, T., Asvestas, P. and Matsopoulos, G. (2010). Fingerprint matching with self organizing maps. In: XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010: May 27 – 30, 2010 Chalkidiki, Greece. Bamidis, P. and Pallikarakis, N. (eds.) IFMBE Proceedings. vol. 29. pp. 307-310. Springer Berlin Heidelberg. Available from: http://link.springer.com/	en
heal.abstract	In this paper, an automatic scheme for the identification of fingerprint images is presented. The scheme consists of two main processes: the extraction of distinctive points only from the template fingerprint image and the detection of their corresponding ones (if they exist) on the input fingerprint image using an implementation of the Self Organizing Maps. The correspondence quality is evaluated using a proper metric, which determines the matching between the two images. The proposed scheme was tested on fingerprint image pairs subject to known and unknown transformations using the VeriFinger_Sample_Data_Base of NeuroTechnology. The overall performance for fingerprints originated from the same and different fingers was 94.12% in terms of the Equal Error Rate.	en
heal.publisher	Springer Berlin Heidelberg	en
heal.fullTextAvailability	true
heal.bookName	XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010	en