Probabilistic Model for Dynamic Signature Verification System

Abstract

This study has proposed the algorithm for signature verification system using dynamic parameters of the signature: pen pressure, velocity and position. The system is proposed to read, analyze and verify the signatures from the SUSig online database. Firstly, the testing and reference samples will have to be normalized, re-sampled and smoothed through pre-processing stage. In verification stage, the difference between reference and testing signatures will be calculated based on the proposed thresholded standard deviation method. A probabilistic acceptance model has been designed to enhance the performance of the verification system. The proposed algorithm has reported False Rejection Rate (FRR) of 14.8% and False Acceptance Rate (FAR) of 2.64%. Meanwhile, the classification rate of the system is around 97%.