Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Small fingerprint scanners used in mobile devices: the impact on biometric performance

© The Institution of Engineering and Technology
Received 14/04/2015, Accepted 18/12/2015, Revised 18/12/2015, Published 01/03/2016

Biometrics has burst into mobile technology. Fingerprint scanners are being embedded in smartphones and tablets supplying these devices with the security and usability provided by biometric authentication mechanisms. However, performance results obtained by biometric systems cannot be extrapolated to mobile devices. The conditions change, especially at capture process, due to the reduced sensing area of the scanners used. The impact of small fingerprint scanners on the quality and biometric performance of the system is studied. A database using three different fingerprint scanners has been collected and reduced-size images (i.e. 12 × 12 mm2, 10 × 10 mm2 and 8 × 8 mm2) have been modelled by cropping the original ones. Performance testing has been conducted using one public and one commercial algorithm, and considering two application scenarios. One scenario in which enrolment and authentication are executed using the same small sensor included in the mobile device (i.e. cropped image against cropped image) and a second scenario in which enrolment is executed using an external larger sensor and authentication is done using the mobile device sensor (i.e. full image against cropped image). Results show the gradual worsening of quality and error rates as the size of the fingerprint scanner is reduced revealing a significant difference between the application scenarios analysed.

Inspec keywords: fingerprint identification; sensors; mobile computing; optical scanners

Other keywords: mobile device sensor; fingerprint scanners; biometric authentication mechanisms

Subjects: Computer vision and image processing techniques; Image recognition; Data security; Mobile, ubiquitous and pervasive computing

References

    1. 1)
      • 7. ‘Samsumg Knox 2.0’. Available at http://www.samsung.com/global/business/mobile/platform/mobile-platform/knox/, accessed 30 March 2015.
    2. 2)
      • 6. ‘LassPass Password Manager Premium’. Available at http://www.androidcentral.com/app/lastpass-password-manager-premium, accessed 30 March 2015.
    3. 3)
      • 15. International Organization for Standardization: ‘ISO/IEC 19795-1, information technology – biometric performance testing and reporting – part 1: principles and framework’, ISO/IEC 19795-1:2006.
    4. 4)
      • 1. ‘Apple – iphone 6 – Touch ID’. Available at https://www.apple.com/iphone-6/touch-id/, accessed 30 March 2015.
    5. 5)
      • 16. FIPS Publication 202, personal identity verification (PIV) of federal employees and contractors, National Institute of Standards and Technology (NIST), August, 2013.
    6. 6)
      • 10. Watson, C., Wilson, C.: ‘Effect of image size and compression on one-to-one fingerprint matching’. National Institute of Standards and Technology (NIST), NISTIR 7201, 2005.
    7. 7)
      • 14. Modi, S., Mohan, A., Senjaya, B., et al: ‘Fingerprint recognition performance evaluation for mobile ID applications’. Proc. of Int. Carnahan Conf. on Security Technology (ICCST), San Jose, California, USA, 5–8 October 2010, pp. 243–249.
    8. 8)
      • 18. Tabassi, E., Wilson, C.L., Watson, C.I.: ‘Fingerprint image quality’. National Institute of Standards and Technology (NIST), NIST IR 7152, 2004.
    9. 9)
      • 11. Orandi, S., McCabe, R.M.: ‘Mobile ID device best practice recommendation varsion 1.0’. National Institute of Standards and Technology (NIST), NIST Special Publication 500–280, 2009.
    10. 10)
    11. 11)
      • 4. ‘Paypal – Samsumg Pay simply and more securely’. Available at https://www.paypal-pages.com/samsunggalaxys5/us/index.html, accessed 30 March 2015.
    12. 12)
      • 13. Schneider, J., Richardson, C.E., Kiefer, F.W., et al: ‘On the correlation of image size to system accuracy in automatic fingerprint identification systems’. Audio-and Video-Based Biometrie Person Authentication, Guildford, UK, 2003 (LNCS, 2688), pp. 895–902.
    13. 13)
      • 17. Watson, C.I., Garris, M., Tabassi, E., et al: ‘User's guide to NIST biometric image software (NBIS),’. National Institute of Standards and Technology (NIST), NIST IR 7392, January 2007, http://www.nist.gov/customcf/get_pdf.cfm?pub_id=51097, accessed 30 March 2015.
    14. 14)
      • 19. The BioSecure Reference and Evaluation Framework, biosecure tool, performance evaluation of a biometric verification system. Available at http://svnext.it-sudparis.eu/svnview2-eph/ref_syst//Tools/PerformanceEvaluation/, accessed 30 March 2015.
    15. 15)
      • 8. Sanchez-Reillo, R., Sierra-Ramos, D., Estrada-Casarrubios, R., et al: ‘Strengths, weaknesses and recommendations in implementing biometrics in mobile devices’. Proc. of Int. Carnahan Conf. on Security Technology (ICCST), Rome, Italy, 13–16 October 2014, pp. 39–44.
    16. 16)
      • 2. ‘Samsung – Your finger is your key’. Available at http://www.samsung.com/global/microsite/galaxys5/features.html, accessed 30 March 2015.
    17. 17)
      • 3. ‘htc – one – max, super simple accesibility’. Available at http://www.htc.com/us/smartphones/htc-one-max/#/, accessed 30 March 2015.
    18. 18)
      • 12. Orandi, S., Ko, K., Wood, S., et al: ‘Examination of the impact of fingerprint spatial area loss on matcher performance in varios mobile identification scenarios’. National Institute of Standards and Technology (NIST), NISTIR 7950, 2014.
    19. 19)
      • 5. ‘Use Touch ID on iPhone and iPad – Apple Support’. Available at https://support.apple.com/en-is/HT201371, accessed 30 March 2015.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-bmt.2015.0018
Loading

Related content

content/journals/10.1049/iet-bmt.2015.0018
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address