Signing documents is something that most everyone is familiar. The verification of handwritten signatures is one of the oldest and the most popular biometric authentication methods in our society. As technology improved, the different ways of comparing and analyzing signatures became more and more sophisticated. Since the early seventies, people have been exploring how computers may aid and –may be one day –fully take over the task of signature verification. Based on the acquisition process, the field is divided into online and offline parts. In online signature verification, the whole process of signing is captured using some kind of an acquisition device, while the offline approach relies merely on the scanned images of signatures. Feature extraction stage is the most vital and difficult stage of any offline signature verification system. The accuracy of the system depends mainly on the effectiveness of the signature features use in the system. Inability to extract robust features from a static image of signature has been contributing to higher verification error-rates particularly for skilled forgeries. The proposed system has 1% error in rejecting skilled forgeries and 0.5% error in accepting genuine signatures. These results are better in comparison with the results obtained from previous systems