Biometric systems identify individuals by comparison of the individual biometric traits, such as the fingerprint patterns. In the literature, many relevant methods are based on the localization of a reference “pivot” point of the fingerprint, called principal singular point (PSP). Most of the time, the PSP is selected from the list of the estimated singular points (SPs) that are identified by specific local patterns of the fingerprint ridges, called cores and deltas. The challenge is to provide an automatic method capable to select the same PSP from different images of the same fingertip. In this paper, we propose a technique that estimates the position of all the singular points by processing the global structure of the ridges and extracting a specific set of features. The selection of the reference point from the candidate list is then obtained by processing the extracted features with computational intelligence classification techniques. Experiments show that the method is accurate and it can be applied on contact and contact-less image types.

Measurement of the principal singular point in contact and contactless fingerprint images by using computational intelligence techniques / R. Donida Labati, A. Genovese, V. Piuri, F. Scotti - In: CIMSA[s.l] : Institute of Electrical and Electronics Engineers (IEEE), 2010 Sep. - ISBN 9781424472284. - pp. 18-23 (( convegno International Conference on Computational Intelligence for Measurement Systems and Applications tenutosi a Taranto nel 2010 [10.1109/CIMSA.2010.5611769].

Measurement of the principal singular point in contact and contactless fingerprint images by using computational intelligence techniques

R. Donida Labati;A. Genovese;V. Piuri;F. Scotti
2010-09

Abstract

Biometric systems identify individuals by comparison of the individual biometric traits, such as the fingerprint patterns. In the literature, many relevant methods are based on the localization of a reference “pivot” point of the fingerprint, called principal singular point (PSP). Most of the time, the PSP is selected from the list of the estimated singular points (SPs) that are identified by specific local patterns of the fingerprint ridges, called cores and deltas. The challenge is to provide an automatic method capable to select the same PSP from different images of the same fingertip. In this paper, we propose a technique that estimates the position of all the singular points by processing the global structure of the ridges and extracting a specific set of features. The selection of the reference point from the candidate list is then obtained by processing the extracted features with computational intelligence classification techniques. Experiments show that the method is accurate and it can be applied on contact and contact-less image types.
artificial intelligence; feature extraction; fingerprint identification
Settore INF/01 - Informatica
Institute of Electrical and Electronic Engineers (IEEE)
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/148697
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