Skip to main content
SpringerLink
Log in

Stroke-Morphology Analysis Using Super-Imposed Writing Movements

  • Conference paper
Book cover Computational Forensics (IWCF 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5158))

Included in the following conference series:

Abstract

Handwritten signatures play an important role in daily life. Consequently, there is a strong need for objective signature evaluation. This paper focuses on a new computational method for discovering and evaluating ink-trace characteristics related to the writing process. It aims (i) to provide a scientific basis for procedures applied in forensic casework and (ii) to derive advanced computational methods for the analysis of signature-stroke morphology. It work towards methods for inferring writer-specific behaviors from the residual ink trace. The respective micro-patterns, caused by biomechanical writing and physical ink-deposition processes, provide important clues for the analysis. These inner ink-trace characteristics of signatures, which are determined by the individual movements of a person, will be studied in depth, taking into account the effects of writing materials, such as the type of pen used. By means of recorded and super-imposed writing movements, ink traces are sampled, and local ink-trace characteristics are encoded in one feature vector per sample record. These data establish a sequence which faithfully reflects the spatial distribution of ink-trace characteristics and solves problems of methods previously available.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Franke, K., Rose, S.: Ink-deposition model: The relation of writing and ink deposition processes. In: Proc. 9th International Workshop on Frontiers in Handwriting Recognition (IWFHR), Tokyo, Japan, pp. 173–178 (2004)

    Google Scholar 

  2. Hecker, M.: Forensische Handschriftenuntersuchung. Kriminalistik (in German) (1993)

    Google Scholar 

  3. Michel, L.: Gerichtliche Schriftvergleichung. De Gruyter (in German) (1982)

    Google Scholar 

  4. Leung, S., Cheng, Y., Fung, H., Poon, N.: Forgery I: Simulation. Journal of Forensic Sciences 38(2), 402–412 (1993)

    Google Scholar 

  5. Leung, S., Cheng, Y., Fung, H., Poon, N.: Forgery II: Tracing. Journal of Forensic Sciences 38(2), 413–424 (1993)

    Google Scholar 

  6. Schomaker, L., Plamondon, R.: The relation between pen force and pen point kinematics in handwriting. Biological Cybernetics 63, 277–289 (1990)

    Article  Google Scholar 

  7. van Gemmert, A.: The effects of mental load and stress on the dynamics of fine motor tasks. PhD thesis, Catholic University, Nijmegen, The Netherlands (1997)

    Google Scholar 

  8. Hilton, O.: Scientific Examination of Questioned Documents (revised edition) edn. CRC Serie in Forensic and Police Science. CRC Press, Boca Raton (1993)

    Google Scholar 

  9. Abuhaiba, I., Ahmed, P.: Restoration of temporal information in off-line arabic handwriting. Pattern Recognition 26(7), 1009–1017 (1993)

    Article  Google Scholar 

  10. Boccigone, G., Chianese, A., Cordella, L., Marcelli, A.: Recovering dynamic information from static handwriting. Pattern Recognition 26(3), 409–419 (1993)

    Article  Google Scholar 

  11. Jäger, S.: Recovering Dynamic Information from Static, Handwritten Word Images. PhD thesis, Albert-Ludwigs-Universität, Freiburg im Breisgrau (1998)

    Google Scholar 

  12. Lallican, P.: Reconnaissance de l’Ecriture Manuscrite Hors-ligne: Utilisation de la Chronologie Restaurée du Tracé. PhD thesis, IRESTE, Universite de Nantes, Nantes (1999)

    Google Scholar 

  13. Plamondon, R.: The origin of 2/3 power law. In: Proc. 8th Conference of the International Graphonomics Society (IGS), Genova, Italy, pp. 17–18 (1997)

    Google Scholar 

  14. Plamondon, R., Privitera, C.: The segmentation of cursive handwriting: An approach based on off-line recovery of the motor-temporal information. IEEE Transactions on Image Processing 8(1), 80–91 (1999)

    Article  Google Scholar 

  15. Ammar, M., Yoshida, Y., Fukumura, T.: A new effective approach for off-line verification of signatures by using pressure features. In: Proc. 8th International Conference on Pattern Recognition, Paris, France, pp. 566–569 (1986)

    Google Scholar 

  16. Doermann, D., Rosenfeld, A.: Recovery of temporal information from static images of handwriting. International Journal of Computer Vision 15, 143–164 (1995)

    Article  Google Scholar 

  17. Sabourin, R., Plamondon, R., Lorette, G.: Off-line identification with handwritten signature images: Survey and perspectives. In: Baird, H., Bunke, H., Yamamoto, K. (eds.) Structured Document Image Analysis, pp. 219–234. Springer, Heidelberg (1992)

    Google Scholar 

  18. Wirotius, M., Vincent, N.: Stroke inner strukture invariance in handwriting. In: Teulings, H., van Gemmert, A. (eds.) Proc. 11th Conference of the International Graphonomics Society (IGS), Scottsdale, Arizona, USA (2003)

    Google Scholar 

  19. Viard-Gaudin, C., Lallican, P., Knerr, S., Binter, P.: The IRESTE On/Off (IRONOFF) dual handwriting database. In: Proc. International Conference on Document Analysis and Recognition (ICDAR), Bangalore, India, pp. 455–458 (1999)

    Google Scholar 

  20. Nel, E., du Preez, J., Herbst, B.: Estimating the pen trajectories of static signutres using hidden markov models. IEEE Transaction on Pattern Analysis and Machine Intelligence (PAMI) 27(11), 1733–1746 (2005)

    Article  Google Scholar 

  21. Guo, J., Doermann, D., Rosenfeld, A.: Forgery detection by local correspondence. International Journal of Pattern Recognition and Artificial Intelligence 15(4), 579–641 (2001)

    Article  Google Scholar 

  22. Franke, K., Grube, G., Schmidt, C.: Assistance system for the analysis of ink deposit. In: Proc. 4th International Congress of the Gesellschaft für Forensische Schriftenuntersuchung (GFS), Hamburg, Germany (1999)

    Google Scholar 

  23. Franke, K., Schomaker, L.: Robotic writing trace synthesis and its application in the study of signature line quality. Journal of Forensic Document Examination 16(3), 119–146 (2004)

    Google Scholar 

  24. Franke, K., Köppen, M.: A computer-based system to support forensic studies on handwritten documents. International Journal on Document Analysis and Recognition 3(4), 218–231 (2001)

    Article  Google Scholar 

  25. Franke, K.: Capturing reliable data for computer-based forensic handwriting analysis. In: IEEE Three-Rivers Workshop on Soft Computing in Industrial Applications (SMCia), Passau, Germany, pp. 115–120 (2007)

    Google Scholar 

  26. Doermann, D., Intrator, N., Rivlin, E., Steinherz, T.: Hidden loop recovery for handwriting recognition. In: Proc. 8th International Workshop on Frontiers in Handwriting Recognition (IWFHR), Niagara-on-the-Lake, Canada, pp. 375–380 (2002)

    Google Scholar 

  27. Franke, K., Bünnemeyer, O., Sy, T.: Writer identification using ink texure analysis. In: Proc. 8th International Workshop on Frontiers in Handwriting Recognition (IWFHR), Niagara-on-the-Lake, Canada, pp. 268–273 (2002)

    Google Scholar 

  28. Dolfing, H.: Handwriting Recognition and Verification: A Hidden Markov Approach. PhD thesis, Eindhoven University of Technology, Eindhoven, The Netherlands (1998)

    Google Scholar 

  29. Gupta, G., McCabe, A.: A review of dynamic handwritten signature verification. Technical report, James Cook University, Townsville, Australia (1997)

    Google Scholar 

  30. Leclerc, F., Plamondon, R.: Automatic signature verification: the state of the art 1989-1993. International Journal of Pattern Recognition and Artificial Intelligence 8, 643–660 (1994)

    Article  Google Scholar 

  31. Plamondon, R., Lorette, G.: Automatic signature verification and writer identification - the state of the art. Pattern Recognition 22, 107–131 (1989)

    Article  Google Scholar 

  32. Schmidt, C.: On-line Unterschriftenanalyse zur Benutzerverifikation. PhD thesis, RWTH Aachen University (in German) (1998)

    Google Scholar 

  33. Wirtz, B.: Segmentorientierte Analyse und nichtlineare Auswertung für die dynamische Unterschriftsverifikation. PhD thesis, Technische Universität München (in German) (1998)

    Google Scholar 

  34. Franke, K., Zhang, Y., Köppen, M.: Static signature verification employing a Kosko-Neuro-Fuzzy approach. In: Pal, N., Sugeno, M. (eds.) AFSS 2002. LNCS (LNAI), vol. 2275, pp. 185–190. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  35. Velek, O., Liu, C.L., Nakagawa, M.: Generating realistic kanji character images from on-line patterns. In: Proc. 6th International Conference on Document Analysis and Recognition (ICDAR), Seattle, Washington, pp. 556–560 (2001)

    Google Scholar 

  36. Gonzalez, R., Woods, R.: Digital image processing. Addison Wessley Publishing Company (1992)

    Google Scholar 

  37. Grube, W.: Zur Feststellung der Schrifturheberschaft bei Unterschriften mit Hilfe densitrometrischer Verfahren. Master’s thesis, Humboldt-Universität Berlin (in German) (1977)

    Google Scholar 

  38. Grube, W.: Densitrometrische Schreibdruckanalyse - Ein Mittel im Identifizierungsprozeßauf dem Gebiet der kriminalistischen Handschriften- und Dokumentenuntersuchung. Forum der Kriminalistik 25, 41–44 (1989) (in German)

    Google Scholar 

  39. Otsu, N.: A threshold selection method from gray-scale histogram. IEEE Transactions on Systems, Man and Cybernetics (SMC) 8, 62–66 (1978)

    Article  Google Scholar 

  40. Cha, S.: Use of Distance Measures in Handwriting Analysis. PhD thesis, State University of New York, Buffalo (2001)

    Google Scholar 

  41. Srihari, S., Cha, S., Arora, H., Lee, S.: Individuality of handwriting. Journal of Forensic Sciences 47(4), 856–872 (2002)

    Google Scholar 

  42. Franke, K., Grube, G.: The automatic extraction of pseudodynamic information from static images of handwriting based on marked grayvalue segmentation (extended version). Journal of Forensic Document Examination 11(3), 17–38 (1998)

    Google Scholar 

  43. Franke, K.: The Influence of Physical and Biomechanical Processes on the Ink Trace - Methodological foundations for the forensic analysis of signatures. PhD thesis, Artifical Instelligence Institute, University of Groningen, The Netherlands (2005)

    Google Scholar 

  44. Sabourin, R., Genest, G., Preteux, F.: Off-line signature verification by local granulometric size distributions. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 19(9), 976–988 (1997)

    Article  Google Scholar 

  45. Franke, K., Schomaker, L., Penk, W.: On-line pen input and procedures for computer-assisted forensic handwriting examination. In: Teulings, H., van Gemmert, A. (eds.) Proc. 11th Conference of the International Graphonomics Society (IGS), Scottsdale, Arizona, USA, pp. 295–298 (2003)

    Google Scholar 

  46. Zimmer, A., Ling, L.: A hybrid on/off line handwritten signature verification system. In: Proc. International Conference on Document Analysis and Recognition (ICDAR), Edinburgh, Scotland (2003)

    Google Scholar 

  47. Doermann, D.: Document Image Understanding: Integration Recovery and Interpretation. PhD thesis, University of Maryland (1993)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Norwegian Information Security Laboratory, Gjøvik University College, Norway

    Katrin Franke

Authors
  1. Katrin Franke
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Sargur N. Srihari Katrin Franke

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Franke, K. (2008). Stroke-Morphology Analysis Using Super-Imposed Writing Movements. In: Srihari, S.N., Franke, K. (eds) Computational Forensics. IWCF 2008. Lecture Notes in Computer Science, vol 5158. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85303-9_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-85303-9_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85302-2

  • Online ISBN: 978-3-540-85303-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation