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 :
بازگشت