Offline Signature Verification using Euclidian Distance

Signature authentication is the most widely used method of verifying a person’s identity. The texture and topological features are the static features of a signature image. Baseline slant angle, aspect ratio, normalized area, center of gravity of the whole signature image and the slope of the line joining the center of gravities of two halves of a signature image are used as the texture and topological features of the signature. The system is initially trained using a set of original signatures obtained from individuals whose signatures have to be authenticated by the system. The mean values and standard deviations of all the original signature features are computed. This mean signature features acts as the template for verification against a claimed test signature. Euclidian distance in the feature space between the claimed signature and the template serves as a measure of similarity between the two. If this distance is less than a pre-defined threshold, the test signature is verified to be that of the original signature otherwise detected as a forgery. The system gives the result to classify original and forgery signature with accuracy up to 100%. Keywords— Signature verification, Euclidian distance, Signature recognition, Feature extraction, Biometric.