Markov model-based handwritten signature verification

McCabe, Alan, and Trevathan, Jarrod (2008) Markov model-based handwritten signature verification. In: Proceedings of the 5th International Conference on Embedded and Ubiquitous Computing (2), pp. 173-179. From: 5th International Conference on Embedded and Ubiquitous Computing, 17-20 December 2008, Shanghai, China.

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Abstract

Biometric security devices are now permeating all facets of modern society. All manner of items including passports, driver's licences and laptops now incorporate some form of biometric data and/or authentication device. As handwritten signatures have long been considered the most natural method of verifying one's identity, it makes sense that pervasive computing environments try to capitalise on the use of automated Handwritten Signature Verification systems (HSV). This paper presents a HSV system that is based on a Hidden Markov Model (HMM) approach to representing and verifying the hand signature data. HMMs are naturally suited to modelling flowing entities such as signatures and speech. The resulting HSV system performs reasonably well with an overall error rate of 3.5% being reported in the best case experimental analysis.

Item ID: 7765
Item Type: Conference Item (Refereed Research Paper - E1)
Keywords: biometrics; neural networks; prediction; type 1 and type 2 error; Artificial Intelligence; security
ISBN: 978-0-7695-3492-3
Date Deposited: 19 Jul 2010 23:21
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0804 Data Format > 080499 Data Format not elsewhere classified @ 100%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified @ 100%
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