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What can a single minutia tell about gender?

: Terhörst, Philipp; Damer, Naser; Braun, Andreas; Kuijper, Arjan

Postprint urn:nbn:de:0011-n-5065901 (796 KByte PDF)
MD5 Fingerprint: f32085dd6ab81411de30c9e84d2a024f
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Erstellt am: 18.8.2018

Institute of Electrical and Electronics Engineers -IEEE-:
IWBF 2018, 6th International Workshop on Biometrics and Forensics. Proceedings : 7-8 June 2018, Sassari, Italy
Piscataway, NJ: IEEE, 2018
ISBN: 978-1-5386-1366-5
ISBN: 978-1-5386-1367-2
7 S.
International Workshop on Biometrics and Forensics (IWBF) <6, 2018, Sassari>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IGD ()
Guiding Theme: Smart City; Guiding Theme: Visual Computing as a Service; Research Area: Computer vision (CV); Research Area: Human computer interaction (HCI); biometric; image classification; object class detection; CRISP

Since fingerprints are one of the most widely deployed biometrics, several applications can benefit from an accurate fingerprint gender estimation. Previous work mainly tackled the task of gender estimation based on complete fingerprints. However, partial fingerprint captures are frequently occurring in many applications including forensics and consumer electronics, with the considered ratio of the fingerprint is variable. Therefore, this work investigates gender estimation on a small, detectable, and well-defined partition of a fingerprint. It investigates gender estimation on the level of a single minutia. Working on this level, we propose a feature extraction process that is able to deal with the rotation and translation invariance problems of fingerprints. This is evaluated on a publicly available database and with five different binary classifiers. As a result, the information of a single minutia achieves a comparable accuracy on the gender classification task as previous work using quarters of aligned fingerprints with an average of more than 25 minutiae.