Automated Border Control (ABC) systems are technologies designed to increase the speed and accuracy of the identity verifications performed at international borders. A great number of ABCs deployed in different countries use fingerprint recognition techniques because of their high accuracy and user acceptability. However, the accuracy of fingerprint recognition methods can drastically decrease in this application context due to user-sensor interaction factors. This paper presents two main contributions. The first of them consists in an experimental evaluation performed to search the main negative aspects that could affect the usability and accuracy in ABCs based on fingerprint biometrics. The mainly considered aspects consists in the presence of luggage and cleanness of the finger skin. The second contribution consists in a novel approach for automatically identifying the type of user-sensor interaction that caused quality degradations in fingerprint samples. This method uses a specific feature set and computational intelligence techniques to detect non-idealities in the acquisition process and to suggest corrective actions to travelers and border guards. To the best of our knowledge, this is the first method in the literature designed to detect problems in user-sensor interaction different from improper pressures on the acquisition surface. We validated the proposed approach using a dataset of 2880 images simulating different scenarios typical of ABCs. Results shown that the proposed approach is feasible and can obtain satisfactory performance, with a classification error of 0.098.

Automatic classification of acquisition problems affecting fingerprint images in automated border controls / R. Donida Labati, A. Genovese, E. Munoz Ballester, V. Piuri, F. Scotti, G. Sforza - In: Computational Intelligence, 2015 IEEE Symposium Series on[s.l] : IEEE, 2015 Dec. - ISBN 9781479975600. - pp. 354-361 (( convegno Symposium Series on Computational Intelligence tenutosi a Cape Town nel 2015 [10.1109/SSCI.2015.60].

Automatic classification of acquisition problems affecting fingerprint images in automated border controls

R. Donida Labati;A. Genovese;E. Munoz Ballester;V. Piuri;F. Scotti;G. Sforza
2015-12

Abstract

Automated Border Control (ABC) systems are technologies designed to increase the speed and accuracy of the identity verifications performed at international borders. A great number of ABCs deployed in different countries use fingerprint recognition techniques because of their high accuracy and user acceptability. However, the accuracy of fingerprint recognition methods can drastically decrease in this application context due to user-sensor interaction factors. This paper presents two main contributions. The first of them consists in an experimental evaluation performed to search the main negative aspects that could affect the usability and accuracy in ABCs based on fingerprint biometrics. The mainly considered aspects consists in the presence of luggage and cleanness of the finger skin. The second contribution consists in a novel approach for automatically identifying the type of user-sensor interaction that caused quality degradations in fingerprint samples. This method uses a specific feature set and computational intelligence techniques to detect non-idealities in the acquisition process and to suggest corrective actions to travelers and border guards. To the best of our knowledge, this is the first method in the literature designed to detect problems in user-sensor interaction different from improper pressures on the acquisition surface. We validated the proposed approach using a dataset of 2880 images simulating different scenarios typical of ABCs. Results shown that the proposed approach is feasible and can obtain satisfactory performance, with a classification error of 0.098.
Settore INF/01 - Informatica
Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni
Enforceable Security in the Cloud to Uphold Data Ownership
I
Book Part (author)
File in questo prodotto:
File Dimensione Formato  
cibim_15.pdf

accesso aperto

Descrizione: Articolo principale
Tipologia: Post-print, accepted manuscript ecc. (versione accettata dall'editore)
Dimensione 1.03 MB
Formato Adobe PDF
1.03 MB Adobe PDF Visualizza/Apri
Automatic_Classification_of_Acquisition_Problems_Affecting_Fingerprint_Images_in_Automated_Border_Controls.pdf

non disponibili

Tipologia: Publisher's version/PDF
Dimensione 600.61 kB
Formato Adobe PDF
600.61 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/355445
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 11
  • ???jsp.display-item.citation.isi??? 7
social impact