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A static signature verification system based on a cooperating neural networks architecture
| Content Provider | Hyper Articles en Ligne (HAL) |
|---|---|
| Author | Cardot, Hubert Revenu, Marinette Victorri, B. Revillet, M.-J. |
| Copyright Year | 1994 |
| Abstract | We are applying neural networks to the problem of handwritten signature verification. Our system is working on checks, so we can only use the static information (the image). This static information is used in three representations: geometrical parameters, outline and image. Our system is composed of several neural networks which cooperate together during the learning and decision phases. The performances in generalization, obtained with a large-scale database of 6000 signatures from real checks on random forgeries, are False Acceptance Rate (FAR) = 2% and False Rejection Rate (FRR) = 4%. |
| Related Links | https://hal.science/hal-00829478/file/IJPRAI-1994.pdf |
| Issue Number | 3 |
| Volume Number | 8 |
| Journal | IJPRAI on Automatic Signature Verification |
| Language | English |
| Publisher | HAL CCSD |
| Publisher Date | 1994-01-01 |
| Access Restriction | Open |
| Subject Keyword | neural networks Handwritten signature verification static information |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science |
