On-line and off-line signature verification using relative slope algorithm

Abstract

The paper presents a novel relative slope based algorithm for an on-line and off-line signature verification system capable of effectively establishing an individual's identify based solely on their handwriting characteristics. Current technologies in signature verification systems use various algorithms for feature point extraction, regression approach, Markov method, split and merge and genetic algorithms. We propose a slope based model, in which the input signature is divided into many segments using an optimized HMM method; then, the slope of every segment is calculated with respect to its previous segment, obtained after normalization of the signature. This feature of each segment is stored along with the two tier time metric information, which ensures lesser overhead with better performance while processing.