Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/48807
Title: Study of long-term quality of online signature verification systems
Authors: Kutzner, Tobias
Bönninger, Ingrid
Travieso, Carlos M. 
Dutta, Malay Kishore
Singh, Anushikha
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Online Handwrting
Signatur
Writer Verification
Sessions
Data Mining
Mobile Devices
Artificial Intelligence
Issue Date: 2017
Journal: 2nd International Conference on Communication, Control and Intelligent Systems, CCIS 2016
Conference: 2nd International Conference on Communication, Control and Intelligent Systems, CCIS 2016 
Abstract: Real handwriting authentication systems need a robust writer identification over a long time period. The paper analyzes signature sessions of the ATV-Signature Long Term Database (ATV-SLT DB). The database contains 6 sessions generated by 27 users over 15 month. The quality change of the verification results over a period of 15 month is examined. 64static and dynamic biometric features from the ATV-SLT DB sessions are extracted and 3 different classifiers are used. For the impostor test a 7th session is added, the impostor session, with 6 signatures for each user. The best result of 99.17% success rate for a correct classification is reached with the k-Nearest Neighbor classifier. The best result of 2.47% false accepted rate is reached with Naïve Bayes classifier.
URI: http://hdl.handle.net/10553/48807
ISBN: 9781509032105
DOI: 10.1109/CCIntelS.2016.7878206
Source: 2nd International Conference on Communication, Control and Intelligent Systems, CCIS 2016 (7878206), p. 85-88
Appears in Collections:Actas de congresos
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