Dynamic Signature Verification System Using Statistics Analysis
Journal Title: International Journal on Computer Science and Engineering - Year 2010, Vol 2, Issue 7
Abstract
In this paper, a new technique for dynamic signature modeling and classification framework is proposed. Raw dynamic data obtained from a digitizer are analyzed using statistic tools. The variation within the same person signatures is obtained for effective signature training and accurate classification of genuine signature against all kind of forgeries. The proposed system is robust enough to prevent forgery of dynamic ignatures. It has False Rejection Rate (FRR) of 0.2% for genuine signatures and False Acceptance Rate (FAR) of 0.25%, 0% and 0% for skilled, simple and random forgeries respectively. These results are better in comparison with the results obtained from previous systems.
Authors and Affiliations
Dr. S. A Daramola. , Prof. T. S Ibiyemi
Keywords
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