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Author Eskander, G.S. ♦ Sabourin, R. ♦ Granger, E.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2012
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Other branches of engineering
Subject Keyword Handwriting recognition ♦ boosting feature selection ♦ Offline signature verification ♦ writer-dependent ♦ writer-independent ♦ writer-adaptation ♦ dissimilarity representation
Abstract Although writer-independent offline signature verification (WI-SV) systems may provide a high level of accuracy, they are not secure due to the need to store user templates for authentication. Moreover, state-of-the-art writer-dependent (WD) and writer-independent (WI) systems provide enhanced accuracy through information fusion at either feature, score or decision levels, but they increase computational complexity. In this paper, a method for adapting WI-SV systems to different users is proposed, leading to secure and compact WD-SV systems. Feature representations embedded within WI classifiers are extracted and tuned to each enrolled user while building a user-specific classifier. Simulation results on the Brazilian signature database indicate that the proposed method yields WD classifiers that provide the same level of accuracy as that of the baseline WI classifiers (AER of about 5.38), while reducing complexity by about 99.5%.
ISBN 9781467322621
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2012-09-18
Publisher Place Italy
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 419.42 kB
Page Count 6
Starting Page 434
Ending Page 439

Source: IEEE Xplore Digital Library