The fact that the signature is widely used as a means of personal verification emphasizes the need for an automatic verification system. Verification can be performed either Offline or Online based on the application. Online systems use dynamic information of a signature captured at the time the signature is made. Offline systems work on the scanned signature. We have worked on the Offline Verification of signatures using a set of shape-based geometric features. The features that are used are Baseline Slant Angle, Aspect Ratio, Normalized Area, Center of Gravity, number of edge points, number of cross points, and the Slope of the line joining the Centers of Gravity of two halves of a signature image. Before extracting the features, preprocessing of a scanned image is necessary to isolate the signature part and to remove any spurious noise present. The system is initially trained using a database of signatures obtained from those individuals whose signatures have to be authenticated by the system. For each subject, a mean signature is obtained integrating the above features derived from a set of his/her genuine sample signatures. This mean signature act as the template for verification against a claimed test signature. Euclidian distance in the feature space between the two. If this distance is less than a pre-defined threshold(corresponding to a minimum acceptable degree of similarity), the signature is verified to be that of the claimed subject else detected as a forgery. The details of preprocessing as well as the features depicted above are described in the report along with the implementation details and simulation results.