A Directional Feature with Energy based Offline Signature Verification
  Network
  Signature used as a biometric is implemented in various systems as well as
every signature signed by each person is distinct at the same time. So, it is
very important to have a computerized signature verification system. In offline
signature verification system dynamic features are not available obviously, but
one can use a signature as an image and apply image processing techniques to
make an effective offline signature verification system. Author proposes a
intelligent network used directional feature and energy density both as inputs
to the same network and classifies the signature. Neural network is used as a
classifier for this system. The results are compared with both the very basic
energy density method and a simple directional feature method of offline
signature verification system and this proposed new network is found very
effective as compared to the above two methods, specially for less number of
training samples, which can be implemented practically.
