Handwritten signature is one of the most natural biometrics, the study of human physiological and behavioral patterns. Behavioral biometrics includes signatures that may be different due to its owner gender or age because of intrinsic or extrinsic factors. This paper presents the results of the author’s research on age and gender influence on verification factors. The experiments in this research were conducted using a database that contains signatures and their associated metadata. The used algorithm is based on the universal forgery feature idea, where the global classifier is able to classify a signature as a genuine one or, as a forgery, without the actual knowledge of the signature template and its owner. Additionally, the reduction of the dimensionality with the MRMR method is discussed.

Date Published: 25 November 2014
PDF: 15 pages
Proc. SPIE 9290, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2014, 929021 (25 November 2014); doi: 10.1117/12.2075160

Published in SPIE Proceedings Vol. 9290:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2014
Ryszard S. Romaniuk, Editor(s)