On-line signature verification with hidden Markov models

J.G.A. Dolfing, E.H.L. Aarts, J.J.G.M. Oosterhout, van

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

This paper addresses the problem of online signature verification based on hidden Markov models (HMM). We use a novel type of digitizer tablet and pay special attention to the use of pen-tilt. We investigate the verification reliability based on different forgery types. We compare the discriminative value of the different features based on a linear discriminant analysis (LDA) and show that pen-tilt is important. On the basis of home-improved, over-the-shoulder and professional forgeries, we show that the amount of dynamic information available to an imposter is important and that forgeries based on paper copies are easier to detect. The results obtained with a database of almost 5000 signatures of 51 persons with highly skilled forgeries include equal-error rates between 1% and 1.9%.
Original languageEnglish
Title of host publication14th International Conference on Pattern Recognition (Brisbane, Queensland, Australia, August 16-20, 1998)
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages1309-1312
ISBN (Print)0-8186-8512-3
DOIs
Publication statusPublished - 1998

Fingerprint Dive into the research topics of 'On-line signature verification with hidden Markov models'. Together they form a unique fingerprint.

Cite this