Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/42440
Title: Online handwriting verification with safe password and increasing number of features
Authors: Kutzner, Tobias
Dietze, Mario
Bönninger, Ingrid
Travieso-González, Carlos M. 
Dutta, Malay Kishore
Singh, Anushikha
UNESCO Clasification: 33 Ciencias tecnológicas
Keywords: Data mining
Handwriting
Safe password
Verification
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Conference: 3rd International Conference on Signal Processing and Integrated Networks, SPIN 2016 
Abstract: In this Article we present a solution to verify user with safe handwritten password. To achieve the best possible results we use 39 parameters beside some statistical parameters we use primarily time, speed and relation parameter. For the tests a database with 32 users was provided. Each user wrote safe password in one session 12 times. For the FAR (false acceptance rate) test we work with 3 forgeries per user. The best result of 100% success rate for a correct classification, we reached with the Bayes Net classifier. The best result of 3.13% false accepted rate is reached with Bayes Net classifier too.
URI: http://hdl.handle.net/10553/42440
ISBN: 978-1-4673-9197-9
DOI: 10.1109/SPIN.2016.7566777
Source: 3rd International Conference on Signal Processing and Integrated Networks, SPIN 2016 (7566777), p. 650-655
Appears in Collections:Actas de congresos
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