Stroke-morphology analysis using super-imposed writing movements

Abstract

Handwritten signatures play an important role in daily life. Consequently, there is a strong need for objective signature evaluation. This paper focuses on a new computational method for discovering and evaluating ink-trace characteristics related to the writing process. It aims (i) to provide a scientific basis for procedures applied in forensic casework and (ii) to derive advanced computational methods for the analysis of signature-stroke morphology. It work towards methods for inferring writer-specific behaviors from the residual ink trace. The respective micro-patterns, caused by biomechanical writing and physical ink-deposition processes, provide important clues for the analysis. These inner ink-trace characteristics of signatures, which are determined by the individual movements of a person, will be studied in depth, taking into account the effects of writing materials, such as the type of pen used. By means of recorded and super-imposed writing movements, ink traces are sampled, and local ink-trace characteristics are encoded in one feature vector per sample record. These data establish a sequence which faithfully reflects the spatial distribution of ink-trace characteristics and solves problems of methods previously available. © 2008 Springer-Verlag Berlin Heidelberg.