Logo PTI
Polish Information Processing Society
Logo FedCSIS

Annals of Computer Science and Information Systems, Volume 2

Proceedings of the 2014 Federated Conference on Computer Science and Information Systems

Handwritten Signature Verification with 2D Color Barcodes

, , ,

DOI: http://dx.doi.org/10.15439/2014F59

Citation: Proceedings of the 2014 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 2, pages 701708 ()

Full text

Abstract. Handwritten Signature Verification (HSV) systems have been introduced to automatically verify the authenticity of a user signature. In offline systems, the handwritten signature (represented as an image) is taken from a scanned document, while in online systems, pen tablets are used to register signature dynamics (e.g, its position, pressure and velocity). In online HSV systems, signatures (including the signature dynamics) may be embedded into digital documents. Unfortunately, during their lifetime documents may be repeatedly printed and scanned (or faxed), and digital to paper conversions may result in loosing the signature dynamics. The main contribution of this work is a new HSV system for document signing and authentication. First, we illustrate how to verify handwritten signatures so that signature dynamics can be processed during verification of every type of document (both paper and digital documents). Secondly, we show how to embed features extracted from handwritten signatures within the documents themselves (by means of 2D barcodes), so that no remote signature database is needed. Thirdly, we propose a method for the verification of signature dynamics which is compatible to a wide range of mobile devices (in terms of computational overhead and verification accuracy) so that no special hardware is needed. We address the trade-off between discrimination capabilities of the system and the storage size of the signature model. Towards this end, we report the results of an experimental evaluation of our system on different handwritten signature datasets.