Forgery Detection in Offline Handwritten Signature using Global and Geometric Features

Signature authentication is the most widely used method of verifying a person’s identity. Verification can be performed either Offline or Online based on the application. Features discussed in this paper are Global and Geometric features. Before extracting the features, pre-processing of a scanned image is necessary to isolate the region of interest part of a signature and to remove any spurious noise present. The system is initially trained using a database of signatures obtained from those individuals whose signatures are to be authenticated by the system. All the features are computed for training samples of signature. There are some variation itself in features of genuine set of signatures. By computing Euclidian distance between mean signature and all training set of signature, acceptance range is set. If a query signature is in the acceptance range then it is an authenticated signature else, it is a forged signature.