Off-line Identification With Handwritten Signature Images: Survey and Perspectives

The first part of this paper presents a survey of the literature on automatic handwritten signature verification systems using binary or gray-level images, and focuses primarily on preprocessing techniques, feature or primitive extraction methods, comparison processes, and performance evaluation. With these previous studies in mind, we propose, in the second part of this paper, an image-understanding system based on the extraction of a novel representation of handwritten signature images. This approach is text insensitive. A structural match between a reference primitive set Pr and a test primitive set Pt takes into account the geometric shape and spatial relations between primitives. Finally, the local comparison of gray levels between pairs of primitives next to each node of the static solution path N results in a pseudodynamic similarity measure ϑ _d (Pr, Pt). This scheme allows the elimination, with a certain degree of success, of skilled forgeries such as tracings and photocopies, showing marked gray-level dissimilarity along the signature line.