Skip to main content
SpringerLink
Log in
Book cover

Advances in Biometrics pp 247–264Cite as

Writer Identification and Verification

  • Chapter

The behavioral biometrics methods of writer identification and verification are currently enjoying renewed interest, with very promising results. This chapter presents a general background and basis for handwriting biometrics. A range of current methods and applications is given, also addressing the issue of performance evaluation. Results on a number of methods are summarized and a more in-depth example of two combined approaches is presented. By combining textural, allographic, and placement features, modern systems are starting to display useful performance levels. However, user acceptance will be largely determined by explainability of system results and the integration of system decisions within a Bayesian framework of reasoning that is currently becoming forensic practice.

This is a preview of subscription content, 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   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover 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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Agarwal, S., Graepel, T., Herbrich, R., Har-Peled, S., and Roth, D. Generalization bounds for the area under the ROC curve. Journal Machine Learning Research, 6:393-425, 2005.

    MATH  MathSciNet  Google Scholar 

  • Andrews, T. and Coppola, D. Idiosyncratic characteristics of saccadic eye movements when viewing different visual environments. Vision Research, 39:2947-2953, 1999.

    Article  Google Scholar 

  • Arazi, B. Handwriting identification by means of run-length measurements. IEEE Trans. Syst., Man and Cybernetics, SMC-7(12):878-881, 1977.

    Article  Google Scholar 

  • BenAbdelkader, C., Cutler, R., and Davis, L. Gait recognition using image self-similarity. EURASIP Journal on Applied Signal Processing, 2004(4): 572-585, 2004.

    Article  Google Scholar 

  • Bensefia, A., Paquet, T., and Heutte, L. Information retrieval-based writer identification. In 7th International Conference on Document Analysis and Recognition (ICDAR 2003), 3-6 August 2003, Edinburgh, Scotland, UK, pages 946-950. IEEE Computer Society, 2003.

    Google Scholar 

  • Bulacu, M. and Schomaker, L. Writer style from oriented edge fragments. In Proc. of the 10th Int. Conference on Computer Analysis of Images and Patterns, pages 460-469, 2003.

    Google Scholar 

  • Bulacu, M. and Schomaker, L. Combining multiple features for text-independent writer identification and verification. In Proc. of 10th Interna-tional Workshop on Frontiers in Handwriting Recognition (IWFHR 2006), pages 281-286, 2006. 23-26 October, La Baule, France.

    Google Scholar 

  • Bulacu, M. and Schomaker, L. Text-independent writer identification and verification using textural and allographic features. IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), 29(4):701-717, Special Issue -Biometrics: Progress and Directions, April 2007.

    Google Scholar 

  • Bulacu, M., Schomaker, L., and Vuurpijl, L. Writer identification using edgebased directional features. In Proc. of ICDAR 2003, pages 937-941. IEEE Computer Society, 2003.

    Google Scholar 

  • Daugman, J. The importance of being random: statistical principles of iris recognition. Pattern Recognition, 36(2):279-291, 2003.

    Article  Google Scholar 

  • Doermann, D. and Rosenfeld, A. Recovery of temporal information from static images of handwriting. In Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pages 162-168, 1992.

    Google Scholar 

  • Dooijes, E. Analysis of handwriting movements. Acta Psychologica, 54:99-114, 1983.

    Article  Google Scholar 

  • Francks, C., DeLisi, L., Fisher, S., Laval, S., Rue, J., Stein, J., and Monaco, A. Confirmatory evidence for linkage of relative hand skill to 2p12-q11. American Journal of Human Genetics, 72:499-502, 2003.

    Article  Google Scholar 

  • Franke, K. The influence of physical and biomechanical processes on the ink trace - Methodological foundations for the forensic analysis of signa-tures. PhD thesis, University of Groningen: Artificial Intelligence Institute, November 2005.

    Google Scholar 

  • Franke, K. and Grube, G. The automatic extraction of pseudo-dynamic information from static images of handwriting based on marked gray value segmentation. Journal of Forensic Document Examination, 11:17-38, 1998.

    Google Scholar 

  • Franke, K. and Rose, S. Ink-deposition model: The relation of writing and ink deposition processes. In IWFHR ’04: Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR’04), pages 173-178. IEEE Computer Society, 2004.

    Google Scholar 

  • Franke, K., Schomaker, L., Veenhuis, C., Taubenheim, C., Guyon, I., Vuurpijl, L., van Erp, M., and Zwarts, G. Wanda: A generic framework applied in forensic handwriting analysis and writer identification. In Proceedings of the 9th IWFHR, Tokyo, Japan. IEEE Computer Society, 2004.

    Google Scholar 

  • Gamboa, H. and Fred, A. A user authentication technic using a web interaction monitoring system. In Pattern Recognition and Image Analysis, LNCS, pages 246-254. Springer Verlag, Newyork, 2003.

    Google Scholar 

  • Gulcher, J., Jonsson, P., Kong, A.et al., and Mapping of a familial essential tremor gene, fet1, to chromosome 3q13. Nature Genetics, 17(1):84-87, 1997.

    Article  Google Scholar 

  • Gutiérrez, F., Lerma-Rascón, M., L.R., S.-G., and Cantu, F. Biometrics and data mining: Comparison of data mining-based keystroke dynamics methods for identity verification. In MICAI ’02: Proceedings of the Second Mexican International Conference on Artificial Intelligence, pages 460-469, London, UK, Springer-Verlag, Newyork, 2002.

    Google Scholar 

  • Jain, A., Griess, F., and Connell, S. On-line signature verification. Pattern Recognition, 35:2963-2972, Dec 2002.

    Article  MATH  Google Scholar 

  • Jain, A., Hong, L., and Pankanti, S. Biometric identification. Commun. ACM, 43(2):90-98, 2000.

    Article  Google Scholar 

  • Jean, G. Writing: The Story of Alphabets and Scripts. Thames and Hudson Ltd., London, 1997.

    Google Scholar 

  • Kasprowski, P. and Ober, J. Eye movements in biometrics. In European Conference on Computer Vision, LNCS, pages 248-258. Springer Verlag, New York, 2004.

    Google Scholar 

  • Kittler, J., Hatef, M., Duin, R., and Matas, J. On combining classifiers. IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), 20 (3):226-239, March 1998.

    Article  Google Scholar 

  • Maarse, F., Schomaker, L., and Teulings, H.-L. Automatic identification of writers. In G. van der Veer and G. Mulder, editors, Human-Computer Interaction: Psychonomic Aspects, pages 353-360. Springer, New York, 1988.

    Google Scholar 

  • Markowitz, J. Voice biometrics. Communications of the ACM, 43(9):66-73, 2000.

    Article  Google Scholar 

  • Marti, U., Messerli, R., and Bunke, H. Writer identification using text line based features. In Proc. 6th ICDAR, pages 101-105. IEEE Computer Society, 2001.

    Google Scholar 

  • McMenamin, G. Style markers in authorship studies. Forensic Linguistics, 8 (2):93-97, 2001.

    Article  Google Scholar 

  • Moritz, E. Replicator-based knowledge representation and spread dynamics. In IEEE International Conference on Systems, Man, and Cybernetics, pages 256-259. The Institution of Electrical Engineers, 1990.

    Google Scholar 

  • Niels, R., Vuurpijl, L., and Schomaker, L. Automatic allograph matching in forensic writer identification. Int. Journal of Pattern Recognition and Artificial Intelligence, 21(1), pp. 61-81, 2007.

    Article  Google Scholar 

  • Plamondon, R. and Guerfali, W. The generation of handwriting with deltalognormal synergies. Biological Cybernetics, 78:119-132, 1998.

    Article  MATH  Google Scholar 

  • Plamondon, R., and Maarse, F. An evaluation of motor models of handwriting. IEEE Trans. Syst. Man Cybern, 19:1060-1072, 1989.

    Article  Google Scholar 

  • Ratha, N., Senior, A., and Bolle, R. Automated biometrics. In ICAPR ’01: Proceedings of the Second International Conference on Advances in Pattern Recognition, pages 445-474, London, UK, Springer Verlag, New York, 2001.

    Google Scholar 

  • Said, H., Peake, G., Tan, T., and Baker, K. Writer identification from non-uniformly skewed handwriting images. In British Machine Vision Conference, pages 478-487, 1998.

    Google Scholar 

  • Schlapbach, A. and Bunke, H. Using HMM based recognizers for writer identification and verification. In IWFHR ’04: Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR’04), pages 167-172, Washington, DC, IEEE Computer Society, 2004.

    Google Scholar 

  • Schlapbach, A. and Bunke, H. Off-line writer identification using gaussian mixture models. In ICPR ’06: Proceedings of the 18th International Con-ference on Pattern Recognition (ICPR’06), pages 992-995, Washington, DC, IEEE Computer Society, 2006.

    Google Scholar 

  • Schmidt, R. A schema theory of discrete motor skill learning. Psychological Review, 82:225-260, 1975.

    Article  Google Scholar 

  • Schomaker, L. Simulation and recognition of handwriting movements: A vertical approach to modeling human motor behavior. PhD thesis, University of Nijmegen, NICI, The Netherlands, 1991.

    Google Scholar 

  • Schomaker, L. From handwriting analysis to pen-computer applications. IEE Electronics Communication Engineering Journal, 10(3):93-102, 1998.

    Article  Google Scholar 

  • Schomaker, L. and Bulacu, M. Automatic writer identification using connected-component contours and edge-based features of upper-case western script. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(6):787-798, 2004.

    Article  Google Scholar 

  • Schomaker, L., Bulacu, M., and Franke, K. Automatic writer identification using fragmented connected-component contours. In Proceedings of the 9th IWFHR, Tokyo, Japan, pages 185-190. IEEE Computer Society, 2004.

    Google Scholar 

  • Schomaker, L., Bulacu, M., and Van Erp, M. Sparse-parametric writer identification using heterogeneous feature groups. In IEEE International Conference on Image Processing, Vol 1, pp. 545-548, 2003.

    Google Scholar 

  • Schomaker, L., Thomassen, A., and Teulings, H.-L. A computational model of cursive handwriting. In M.S.R. Plamondon, C.Y. Suen, editor,Computer Recognition and Human Production of Handwriting, pages 153-177. World Scientific, Singapore, 1989.

    Google Scholar 

  • Schomaker, L.R.B. and Plamondon, R. The relation between pen force and pen-point kinematics in handwriting. Biological Cybernetics, 63:277-289, 1990.

    Article  Google Scholar 

  • Srihari, S. and Shi, Z. Forensic handwritten document retrieval system. In Proc. of the First International Workshop on Document Image Analysis for Libraries (DIAL’04), page 188, Washington, DC, IEEE Computer Society, 2004.

    Google Scholar 

  • Srihari, S., Cha, S., Arora, H., and Lee, S. Individuality of handwriting. Journal of Forensic Sciences, 47(4):1-17, July 2002.

    Google Scholar 

  • U.S. Supreme Court. Daubert v. Merrell Dow Pharmaceuticals, 509 U.S. 579. 125 L.Ed.2d 469, 1993.

    Google Scholar 

  • Van Galen, G., Van Doorn, R., and Schomaker, L. Effects of motor programming on the power spectral density function of writing movements. Journal of Experimental Psychology, 16:755-765, 1989.

    Google Scholar 

  • Van Galen, G. P., Portier, J., Smits-Engelsman, B. C. M., and Schomaker, L. Neuromotor noise and poor handwriting in children. Acta Psychologica, 82: 161-178, 1993.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Artificial Intelligence, University of Groningen, Grote Kruisstr. 2/1, 9712 TS, Groningen, The Netherlands

    Lambert Schomaker

Authors
  1. Lambert Schomaker
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. IBM Thomas J. Watson Research Center, Hawthorne, NY, USA

    Nalini K. Ratha BTech, MTech, PhD

  2. Department of Computer Science and Engineering, University of Buffalo, NY, USA

    Venu Govindaraju BTech, MS, PhD

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag London Limited

About this chapter

Cite this chapter

Schomaker, L. (2008). Writer Identification and Verification. In: Ratha, N.K., Govindaraju, V. (eds) Advances in Biometrics. Springer, London. https://doi.org/10.1007/978-1-84628-921-7_13

Download citation

  • DOI: https://doi.org/10.1007/978-1-84628-921-7_13

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84628-920-0

  • Online ISBN: 978-1-84628-921-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation