Nguyen, Vu

Blumenstein, Michael

Leedham, Graham

2009

Global features based on the boundary of a signature and its projections are described for enhancing the process of automated signature verification. The first global feature is derived from the total 'energy' a writer uses to create their signature. The second feature employs information from the vertical and horizontal projections of a signature, focusing on the proportion of the distance between key strokes in the image, and the height/width of the signature. The combination of these features with the Modified Direction Feature (MDF) and the ratio feature showed promising results for the off-line signature verification problem. When being trained using 12 genuine specimens and 400 random forgeries taken from a publicly available database, the Support Vector Machine (SVM) classifier obtained an average error rate (AER) of 17.25%. The false acceptance rate (FAR) for random forgeries was also kept as low as 0.08%.

Proceedings of the 10th International Conference on Document Analysis and Recognition, p. 1300-1304

9781424445004

9780769537252

1520-5363

https://hdl.handle.net/1959.11/9753

en

Institute of Electrical and Electronics Engineers (IEEE)

Global Features for the Off-Line Signature Verification Problem

Conference Publication

Publication