An Empirical Study of Signature Recognition &Verification System Using Various Approaches
Sachin A. Murab1, Vaishali. M.Deshmukh2
1Mr. Sachin A. Murab, Information Technology Department, P.R.M.I.T & R, Badnera, Sant Gadge Baba Amravati University. Amravati, India.
2Prof Vaishali M. Deshmukh, Assistant Professor, CSE Department, P.R.M.I.T & R, Badnera, Sant Gadge Baba Amravati University. Amravti, India.
Manuscript received on November 21, 2012. | Revised Manuscript received on December 06, 2012. | Manuscript published on December 30, 2012. | PP: 260-263 | Volume-2, Issue-2, December 2012. | Retrieval Number: B0923112212 /2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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. In this paper, we present implementation of off-line signature recognition and verification system, which is based on moment invariant method, ANFIS, Pairwise distance (pdist) and Kmeans. The user introduces the scanned images into the computer, modifies their quality by image preprocessing followed by feature extraction, ANFIS training, pdist and kmeans.
Keywords: Component: Image preprocessing, Feature extraction, Moment Invariant method, ANFIS training, pdist & kmeans.