OFFLINE FORGERY DETECTION OF HANDWRITTEN SIGNATURE USING GAUSSIAN EMPIRICAL RULE
| Author(s) | : | G.Gowri Pushpa, G.Santoshi |
| Institution | : | Assistant Professor, Department of CSE, ANITS, Visakhapatnam |
| Published In | : | Vol. 5, Issue 4 — April 2018 |
| Page No. | : | 2023-2029 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Signature authentication is most widely used in verifying a person’s identity. In this paper Global andGeometric features are discussed. Before extracting the features, preprocessing of a scanned image is necessary toisolate the region of interest part of a signature and to remove any spurious noise present. The system is trained initiallywith the data-set of signatures obtained from those individuals whose signatures are to be authenticated by the system.All the features are computed for training samples of signature. There are some variation itself in features of genuine setof signatures. If testing signature sample satisfies the Gaussian empirical rule it is authenticated as original signatureotherwise a forged one.
G.Gowri Pushpa, G.Santoshi, “OFFLINE FORGERY DETECTION OF HANDWRITTEN SIGNATURE USING GAUSSIAN EMPIRICAL RULE”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 5, Issue 4, pp. 2023-2029, April 2018.
