A New Approach to Signature Verification: Digital Data Acquisition Pen

1. A New Approach to Signature Verification: Digital Data Acquisition Pen Ondřej Rohlík rohlik@kiv.zcu.cz Department of Computer Science and Engineering University of West Bohemia in Pilsen

2. Outline • pen – pictures, construction • signals – description • application areas • signature verification • author identification • results Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

3. The Pen The pen was designed and constructed at Fachhochschule Regensburg Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

4. Writing with the Pen Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

5. Signals Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

6. Signals Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

7. Application Areas • signature verification • authentic signature or fake • person identification • which of several people • character/text recognition • replacement of keyboards and/or scanners Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

8. Signature Verification – Problem • we have to classify into two classes • classes overlaps each other • we have no training data for “fakes” Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

9. Program Developed Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

10. Useable Features Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

11. Algorithms For each class C Training algorithm For each feature f For each pair of signatures Classes[C][i] and Classes[C][j] Compute the difference between Classes[C][i] and Classes[C][j] and add it to an extra variable Sum[f] Compute mean value mean[f] and variance var[f] of each feature over all pairs using the variable Sum[f] Compute critical cluster coefficient using variances var[f] and weights w[f] over all features f For class C to be verified Recognition algorithm For each pattern Classes[c][i] For each feature f Compute the difference and remember the least one over all patterns Sum up products of least differences and weights w[f] and compare the sum with Critical cluster coefficient Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

12. Signature Verification – Results Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

13. Author Identification – Problem • samples are classified into several classes – each corresponds to one author • the written word is not a name (signature) but any other word – we use the same word for all authors Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

14. Author Identification – Problem Graphologists use many signs to characterize the personality of the author – movement (expansion in height and in width, coordination, speed, pressure, stroke, tension, directional trend, rhythm) – form (style, letter shapes, loops, connective forms, rhythm) – arrangement (patterns, rhythm, line alignment, word interspaces, zonal proportions, slant, margins – top, left and right) – signature (convergence with text, emphasis on given name or family name, placement) Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

15. Author Identification – Solution • classification by neural network – two-layer perceptron network • trained using variant of back-propagation algorithm with momentum Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

16. Author Identification – Results Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

17. Conclusion and Future Work • twofold purpose of our research: • to improve reliability of signature verification • to make text recognition devices cheaper • result achieved so far are good but more tests must be done in order to prove that our pen and methods are useful • acceleration sensor is not suitable for text recognition – will be replaced by pressure sensors Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

18. Example of signature – “Rohlík“ Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001

19. Ondřej Rohlík, University of West Bohemia in Pilsen - SoftCOM 2001