DocumentCode
1638255
Title
Improving the Enrollment in Dynamic Signature Verfication with Synthetic Samples
Author
Galbally, Javier ; Fierrez, Julian ; Martinez-Diaz, Marcos ; Ortega-Garcia, Javier
Author_Institution
Biometric Recognition Group, Univ. Autonoma de Madrid, Madrid, Spain
fYear
2009
Firstpage
1295
Lastpage
1299
Abstract
A novel scheme to generate multiple synthetic samples from a real on-line handwritten signature is proposed. The algorithm models a transmission channel which introduces a certain distortion into the real signature to produce the different synthetic samples. The method is used to increase the amount of data of the clients enrolling on a state-of-the-art HMM-based signature verification system. The enhanced enrollment results in performance improve up to70% between the case in which only one real sample of the user was available for the training, and the case where the proposed algorithm was used to generate additional synthetic training data.
Keywords
handwriting recognition; hidden Markov models; dynamic signature verification; hidden Markov model; online handwritten signature; synthetic samples; Attenuation; Bioinformatics; Biometrics; Fingerprint recognition; Handwriting recognition; Hidden Markov models; Iris; Speech synthesis; Text analysis; Training data; On-line signature verification; enrollment; synthetic generation;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on
Conference_Location
Barcelona
ISSN
1520-5363
Print_ISBN
978-1-4244-4500-4
Electronic_ISBN
1520-5363
Type
conf
DOI
10.1109/ICDAR.2009.38
Filename
5277701
Link To Document