Differentiation of Signature Traits $vis-\grave{a}-vis$ Mobile- and Table-Based Digitizers

  • Elliott, Stephen J. (Department of Industrial Technology, Purdue University)
  • 투고 : 2004.03.16
  • 발행 : 2004.12.31

초록

As the use of signatures for identification purposes is pervasive in society and has a long history in business, dynamic signature verification (DSV) could be an answer to authenticating a document signed electronically and establishing the identity of that document in a dispute. DSV has the advantage in that traits of the signature can be collected on a digitizer. The research question of this paper is to understand how the individual variables vary across devices. In applied applications, this is important because if the signature variables change across the digitizers this will impact performance and the ability to use those variable. Understanding which traits are consistent across devices will aid dynamic signature algorithm designers to create more robust algorithms.

키워드

참고문헌

  1. Proc. of the Fourth Int’l Conf. v.2 On-Line Signature Verification: Discrimination Emphasised, Document Analysis and Recognition Martens, R.;Claesen, L.
  2. Implementing a DSP Kernel for Online Dynamic Handwritten Signature Verification Using the TMS320DSP Family (SPRA304) Dullink, H.;van Daalen, B.;Nijhuis, J.;Spaanenburg, L.;Zuidhof, H.
  3. On-Line Signature Verification Greiss, F.D.
  4. A Performance Evaluation of Biometric Identification Devices, SANDIA91-0276 Holmes, J.P.
  5. Proc. of 6th Int’l Conf. on Neural Information Processing v.3 On-Line Pen Input Signature Verification PPI Komiya, Y.;Matsumoto, T.
  6. Automatic Signature Verification: The State of the Art-1989-1993, Progress in Automatic Signature Verification Leclerc, F.;Plamondon, R.
  7. Reliable On-Line Human Signature Verification Systems; IEEE Trans. on Pattern Analysis and Machine Intelligence Lee, L.;Berger, T.;Aviczer, E.
  8. 1998 Int’l Conf. on Image Processing Improved Segmentation through Dynamic Time Warping for Signature Verification Using a Neural Network Classifier Lee, W.S.;Mohankrishnan, N.;Paulik, M.
  9. Segmentation and Reconstruction of On-Line Handwritten Scr. Pattern Recognition Li, X.;Parizeau, M.;Plamondon, R.
  10. Wireless Electronic Commerce Security Ansano, H.;Sumi, A.;Ramzan, Z.;Zhu, I.
  11. Proc. of the IEEE Int’l Conf. on Multimedia Computing and Systems User Interface for a PCS Smart Phone Narayanaswamy, S.;Hu, J.;Kashi, R.
  12. Wacom Product Specification
  13. European Convention on Security and Detention Low Cost Dynamic Signature Verification System Hamilton, D.J.;Whelan, J.;McLaren, A.;MacIntyre, I.
  14. Proc. of the 1997 Document Analysis and Recognition Establishment of Personalized Templates for Automatic Signature Verification Schmidt, C.;Kraiss, K.F.
  15. CIFEr'O 1: Computational Intelligence in Financial Eng. Conf. Automatic On-Line Signature Verification Based on Multiple Models Mingming, M.;Wijesoma, W.
  16. Signature Verification from Position, Velocity and Acceleration Signals: A Comparative Study Plamondon, R.;Parizeau, M.
  17. E-Pad Data Sheet [Brochure] Interlink
  18. Facial Recognition Vendor Test 2000 Evaluation Report Blackburn, D.M.;Bone, M.;Grother, P.;Phillips, J.
  19. Biometric Product Testing Final Report, CESG Contract X92A/4009309 Mansfield, T.;Kelly, G.;Chandler, D.;Kane, J.