Automatic Verification of Properly Signed Multi-page Document Images

  • Marçal RusiñolEmail author
  • Dimosthenis Karatzas
  • Josep Lladós
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9475)


In this paper we present an industrial application for the automatic screening of incoming multi-page documents in a banking workflow aimed at determining whether these documents are properly signed or not. The proposed method is divided in three main steps. First individual pages are classified in order to identify the pages that should contain a signature. In a second step, we segment within those key pages the location where the signatures should appear. The last step checks whether the signatures are present or not. Our method is tested in a real large-scale environment and we report the results when checking two different types of real multi-page contracts, having in total more than 14,500 pages.


Document Image Manual Inspection Signature Verification Rejection Criterion Document Flow 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Plamondon, R., Lorette, G.: Automatic signature verification and writer identification - the state of the art. Pattern Recogn. 22, 107–131 (1989)CrossRefGoogle Scholar
  2. 2.
    Leclerc, F., Plamondon, R.: Automatic signature verification: the state of the art 1989–1993. Int. J. Pattern Recogn. Artif. Intell. 8, 643–659 (1994)CrossRefGoogle Scholar
  3. 3.
    Hou, W., Ye, X., Wang, K.: A survey of off-line signature verification. In: Proceedings of the International Conference on Intelligent Mechatronics and Automation, pp. 536–541 (2004)Google Scholar
  4. 4.
    Zhu, G., Zheng, Y., Doermann, D.: Signature-based document image retrieval. In: Proceedings of the Tenth European Conference on Computer Vision, pp. 752–765 (2008)Google Scholar
  5. 5.
    Zhu, G., Zheng, Y., Doermann, D., Jaeger, S.: Signature detection and matching for document image retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 31, 2015–2031 (2009)CrossRefGoogle Scholar
  6. 6.
    Ahmed, S., Malik, M., Liwicki, M., Dengel, A.: Signature segmentation from document images. In: Proceedings of the, pp. 425–429 (2012)Google Scholar
  7. 7.
    Mandal, R., Roy, P., Pal, U.: Signature segmentation from machine printed documents using contextual information. Int. J. Pattern Recogn. Artif. Intell. 26 (2012)Google Scholar
  8. 8.
    Doermann, D.: The indexing and retrieval of document images: A survey. Comput. Vis. Image Underst. 70, 287–298 (1998)CrossRefGoogle Scholar
  9. 9.
    Chen, N., Blostein, D.: A survey of document image classification: problem statement, classifier architecture and performance evaluation. Int. J. Doc. Anal. Recogn. 10, 1–16 (2006)CrossRefGoogle Scholar
  10. 10.
    Frasconi, P., Soda, G., Vullo, A.: Hidden Markov models for text categorization in multi-page documents. J. Intell. Inform. Syst. 18, 195–217 (2002)CrossRefGoogle Scholar
  11. 11.
    Gordo, A., Perronnin, F.: A bag-of-pages approach to unordered multi-page document classification. In: Proceedings of the International Conference on Pattern Recognition, pp. 1920–1923 (2010)Google Scholar
  12. 12.
    Rusiñol, M., Karatzas, D., Bagdanov, A., Lladós, J.: Multipage document retrieval by textual and visual representations. In: Proceedings of the International Conference on Pattern Recognition (2012)Google Scholar
  13. 13.
    Rusiñol, M., Frinken, V., Karatzas, D., Bagdanov, A., Lladós, J.: Multimodal page classification in administrative document image streams. Int. J. Doc. Anal. Recogn. 17, 331–341 (2014)CrossRefGoogle Scholar
  14. 14.
    Héroux, P., Diana, S., Ribert, A., Trupin, E.: Classification method study for automatic form class identification. In: Proceedings of the Fourteenth International Conference on Pattern Recognition, pp. 926–928 (1998)Google Scholar
  15. 15.
    Likforman-Sulem, L., Zahour, A., Taconet, B.: Text line segmentation of historical documents: A survey. Int. J. Doc. Anal. Recogn. 9, 123–138 (2007)CrossRefGoogle Scholar
  16. 16.
    Lewis, J.: Fast normalized cross-correlation. Vis. Interface 10, 120–123 (1995)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Marçal Rusiñol
    • 1
    Email author
  • Dimosthenis Karatzas
    • 1
  • Josep Lladós
    • 1
  1. 1.Computer Vision Center, Department Ciències de la ComputacióEdifici O, University Autònoma de BarcelonaBarcelonaSpain

Personalised recommendations