Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/42440
Título: Online handwriting verification with safe password and increasing number of features
Autores/as: Kutzner, Tobias
Dietze, Mario
Bönninger, Ingrid
Travieso-González, Carlos M. 
Dutta, Malay Kishore
Singh, Anushikha
Clasificación UNESCO: 33 Ciencias tecnológicas
Palabras clave: Data mining
Handwriting
Safe password
Verification
Fecha de publicación: 2016
Editor/a: Institute of Electrical and Electronics Engineers (IEEE) 
Conferencia: 3rd International Conference on Signal Processing and Integrated Networks, SPIN 2016 
Resumen: 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
Fuente: 3rd International Conference on Signal Processing and Integrated Networks, SPIN 2016 (7566777), p. 650-655
Colección:Actas de congresos
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