Offline signature verification through biometric strengthening

Shin Yin Ooi; Andrew Beng Jin Teoh; Thian Song Ong

doi:10.1109/AUTOID.2007.380624

Offline signature verification through biometric strengthening

Shin Yin Ooi, Andrew Beng Jin Teoh, Thian Song Ong

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

The offline signature verification rests on the hypothesis that each writer has similarity among signature samples, with small distortion and scale variability, In this paper we propose a novel method to increase the accuracy in biometric matching which we term biometric strengthening. We reported 1.1% equal error rate (EER) over the independent database on random forgery, while casual forgery on EER 1.2% and lastly skilled forgery on EER 2.1 % along the paper. Our experiments show that biometric strengthening reduces the false acceptance rate (FAR) and false rejection rate (FRR) by increasing the disparity between the features of the two persons, which tends to tolerate more intrapersonal variance which can reduce the FRR without increasing the probability of false accepts.

Original language	English
Title of host publication	2007 IEEE Workshop on Automatic Identification Advanced Technologies - Proceedings
Pages	226-231
Number of pages	6
DOIs	https://doi.org/10.1109/AUTOID.2007.380624
Publication status	Published - 2007
Event	2007 IEEE Workshop on Automatic Identification Advanced Technologies, AUTOID 2007 - Alghero, Italy Duration: 2007 Jun 7 → 2007 Jun 8

Publication series

Name	2007 IEEE Workshop on Automatic Identification Advanced Technologies - Proceedings

Other

Other	2007 IEEE Workshop on Automatic Identification Advanced Technologies, AUTOID 2007
Country	Italy
City	Alghero
Period	07/6/7 → 07/6/8

All Science Journal Classification (ASJC) codes

Computer Science(all)

Access to Document

10.1109/AUTOID.2007.380624

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title = "Offline signature verification through biometric strengthening",

abstract = "The offline signature verification rests on the hypothesis that each writer has similarity among signature samples, with small distortion and scale variability, In this paper we propose a novel method to increase the accuracy in biometric matching which we term biometric strengthening. We reported 1.1% equal error rate (EER) over the independent database on random forgery, while casual forgery on EER 1.2% and lastly skilled forgery on EER 2.1 % along the paper. Our experiments show that biometric strengthening reduces the false acceptance rate (FAR) and false rejection rate (FRR) by increasing the disparity between the features of the two persons, which tends to tolerate more intrapersonal variance which can reduce the FRR without increasing the probability of false accepts.",

author = "Ooi, {Shin Yin} and Teoh, {Andrew Beng Jin} and Ong, {Thian Song}",

note = "Copyright: Copyright 2008 Elsevier B.V., All rights reserved.; 2007 IEEE Workshop on Automatic Identification Advanced Technologies, AUTOID 2007 ; Conference date: 07-06-2007 Through 08-06-2007",

year = "2007",

doi = "10.1109/AUTOID.2007.380624",

language = "English",

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series = "2007 IEEE Workshop on Automatic Identification Advanced Technologies - Proceedings",

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booktitle = "2007 IEEE Workshop on Automatic Identification Advanced Technologies - Proceedings",

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Ooi, SY, Teoh, ABJ & Ong, TS 2007, Offline signature verification through biometric strengthening. in 2007 IEEE Workshop on Automatic Identification Advanced Technologies - Proceedings., 4263245, 2007 IEEE Workshop on Automatic Identification Advanced Technologies - Proceedings, pp. 226-231, 2007 IEEE Workshop on Automatic Identification Advanced Technologies, AUTOID 2007, Alghero, Italy, 07/6/7. https://doi.org/10.1109/AUTOID.2007.380624

Offline signature verification through biometric strengthening. / Ooi, Shin Yin; Teoh, Andrew Beng Jin; Ong, Thian Song.

2007 IEEE Workshop on Automatic Identification Advanced Technologies - Proceedings. 2007. p. 226-231 4263245 (2007 IEEE Workshop on Automatic Identification Advanced Technologies - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - The offline signature verification rests on the hypothesis that each writer has similarity among signature samples, with small distortion and scale variability, In this paper we propose a novel method to increase the accuracy in biometric matching which we term biometric strengthening. We reported 1.1% equal error rate (EER) over the independent database on random forgery, while casual forgery on EER 1.2% and lastly skilled forgery on EER 2.1 % along the paper. Our experiments show that biometric strengthening reduces the false acceptance rate (FAR) and false rejection rate (FRR) by increasing the disparity between the features of the two persons, which tends to tolerate more intrapersonal variance which can reduce the FRR without increasing the probability of false accepts.

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