Offline Biometric Signature Verification Using Geometric and Colour Features

Offline signature verification is undeniably a prominent aspect of the biometric research. It has many applications, including banking and forensics. Signature verification task involves a comparison of questioned signature with a set of one or more reference signatures. The questioned signature may be genuine (written by the authentic writer), a forgery (written by a different person) or a disguise (written by the authentic writer with some modifications with the intent of a later denial). Signature verification generally encompasses the two main steps: feature extraction and classification. The system performance is primarily dependent on the feature extraction step because the characterising features distinguish between genuine, disguised and forged signatures. In this study, we propose several geometric and colour features to characterise the signatures. The features are combined using random forests, logistic regression and generalised linear models. The results are reported on the datasets of several competitions, including ICDAR 2009, ICFHR 2010, ICDAR 2011 and ICFHR 2012 signature verification competitions. The proposed method generally outperforms the other participating methods.