Konferenzbeitrag
Improved Fingerphoto Verification System Using Multi-scale Second Order Local Structures
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Dokumententyp
Text/Conference Paper
Datum
2018
Zeitschriftentitel
ISSN der Zeitschrift
Bandtitel
Quelle
BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group
Verlag
Köllen Druck+Verlag GmbH
Zusammenfassung
Today’s high-end smartphones are embedded with advanced fingerprint biometric recognition
systems that require dedicated sensors to capture the fingerprint data. The inclusion of such
sensors helps in achieving better biometric performance and hence can enable various applications
that demand reliable identity verification. However, fingerphoto recognition systems have some inherent
advantages over fingerprint recognition such as no latent fingerprints, and it enables the possibility
to capture multiple samples at once from a biometric instance with minimal user interaction.
Thus, user authentication based on fingerphotos could be a useful alternative as we can re-use the
smartphone camera to capture the fingerphotos. On the other hand, such an approach introduces
different challenges; for example illumination, orientation, background variation, and focus resulting
in lower biometric performance. In this research, we propose a novel verification framework
based on the feature extracted from the eigenvalues of convolved images using multi-scale second
order Gaussian derivatives. The proposed framework is used to authenticate individuals based on images/
videos of their fingers captured using the built-in smartphone cameras. When combining with
the commercial off the shelf (COTS) system, the proposed feature extraction technique has achieved
the improved verification performance with an equal error rate of 2:76%.