OFFLINE TRACING AND REPRESENTATION OF SIGNATURES

A new approach to the representation of signatures in an offline environment is presented. The approach makes a tracing of a signature similar to the way a human normally does and incorporates the dynamic information of the tracing sequence into the representation of the signature. Tracing involves hierarchical decision-making for stroke identification and ordering based on a set of heuristic rules. These heuristic rules work as operators that transform a two-dimensional (2-D) spatial pattern into a one-dimensional (1-D) temporal pattern, thus making it possible to extract the dynamic features of a signature. Following the stroke sequence of a signature identified by the tracing, a multiresolution critical-point segmentation method is proposed to extract local feature points, at varying degrees of scale and coarseness, for representation. Finally, to make the representation translation-, rotation-, and scaling-invariant, a critical-point normalization method is introduced. Experimental results are shown.