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Introduction

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Abstract

This first chapter puts in context the symbol spotting problem. By giving a general overview of the Document Image Analysis and Recognition field and, in particular, of the Graphics Recognition research topic, we present the motivations for the present study. We summarize the objectives and contributions of this book as well as the contents of each chapter.

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References

  1. Bertolami, R., Bunke, H.: Hidden Markov model-based ensemble methods for offline handwritten text line recognition. Pattern Recognition 41(11), 3452–3460 (2008)

    Article  MATH  Google Scholar 

  2. Bulacu, M., van Koert, R., Shomaker, L., van der Zant, T.: Layout analysis of handwritten historical documents for searching the archive of the cabinet of the dutch queen. In: Proceedings of the Ninth International Conference on Document Analysis and Recognition, pp. 357–361. IEEE Computer Society, Los Alamitos (2007)

    Chapter  Google Scholar 

  3. Coüasnon, B., Camillerapp, J., Leplumey, I.: Access by content to handwritten archive documents: Generic document recognition method and platform for annotations. International Journal on Document Analysis and Recognition 9(2–4), 223–242 (2007)

    Google Scholar 

  4. Esposito, F., Ferilli, S., Mauro, N.D., Basile, T.: Incremental learning of first order logic theories for the automatic annotations of web documents. In: Proceedings of the Ninth International Conference on Document Analysis and Recognition, pp. 1093–1097. IEEE Computer Society, Los Alamitos (2007)

    Chapter  Google Scholar 

  5. Gish, H., Ng, K.: A segmental speech model with applications to word spotting. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 447–450. IEEE Computer Society, Los Alamitos (1993)

    Chapter  Google Scholar 

  6. Jones, G., Foote, J., Jones, K., Young, S.: Video mail retrieval: The effect of word spotting accuracy on precision. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 309–312. IEEE Computer Society, Los Alamitos (1995)

    Google Scholar 

  7. Joty, S., Sadid-Al-Hasan, S.: Advances in focused retrieval: A general review. In: Proceedings of the Tenth International Conference on Computer and Information Technology, pp. 1–5. IEEE Computer Society, Los Alamitos (2007)

    Chapter  Google Scholar 

  8. Liu, X., Doerman, D.: Mobile retriever: Access to digital documents from their physical source. International Journal on Document Analysis and Recognition 11(1), 19–27 (2008)

    Article  Google Scholar 

  9. Rath, T., Manmatha, R.: Features for word spotting in historical manuscripts. In: Proceedings of the Seventh International Conference on Document Analysis and Recognition, pp. 218–222. IEEE Computer Society, Los Alamitos (2003)

    Chapter  Google Scholar 

  10. Rohlicek, J., Jeanrenaud, P., Ng, K., Gish, H., Musicus, B., Siu, M.: Phonetic training and language modeling for word spotting. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 459–462. IEEE Computer Society, Los Alamitos (1993)

    Chapter  Google Scholar 

  11. Saldarriaga, S., Morin, E., Viard-Gaudin, C.: Categorization of on-line handwritten documents. In: Proceedings of the Eighth IAPR International Workshop on Document Analysis Systems, pp. 95–102. IEEE Computer Society, Los Alamitos (2008)

    Chapter  Google Scholar 

  12. Sayre, K.: Machine recognition of handwritten words: A project report. Pattern Recognition 5(3), 213–228 (1973)

    Article  Google Scholar 

  13. Tombre, K., Lamiroy, B.: Graphics recognition—from re-engineering to retrieval. In: Proceedings of the Seventh International Conference on Document Analysis and Recognition, pp. 148–155. IEEE Computer Society, Los Alamitos (2003)

    Chapter  Google Scholar 

  14. Tombre, K., Lamiroy, B.: Pattern recognition methods for querying and browsing technical documentation. In: Progress in Pattern Recognition, Image Analysis and Applications, Lecture Notes on Computer Science, vol. 5197, pp. 504–518. Springer, Berlin (2008)

    Chapter  Google Scholar 

  15. Viola, P., Rinker, J., Law, M.: Automatic fax routing. In: Document Analysis Systems VI, Lecture Notes on Computer Science, vol. 3163, pp. 484–495. Springer, Berlin (2004)

    Google Scholar 

  16. Wiener, E., Pedersen, J., Weigend, A.: A neural network approach to topic spotting. In: Proceedings of the Fourth Annual Symposium on Document Analysis and Information Retrieval, pp. 317–332 (1995)

    Google Scholar 

  17. Yoshida, M., Nakagawa, H.: Web document parsing: A new approach to modeling layout–language relations. In: Proceedings of the Ninth International Conference on Document Analysis and Recognition, pp. 203–207. IEEE Computer Society, Los Alamitos (2007)

    Chapter  Google Scholar 

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Correspondence to Marçal Rusiñol .

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Rusiñol, M., Lladós, J. (2010). Introduction. In: Symbol Spotting in Digital Libraries. Springer, London. https://doi.org/10.1007/978-1-84996-208-7_1

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  • DOI: https://doi.org/10.1007/978-1-84996-208-7_1

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84996-207-0

  • Online ISBN: 978-1-84996-208-7

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