Abstract
Handwritten text is generally captured through two main modalities: off-line and on-line. Each modality has advantages and disadvantages, but it seems clear that smart approaches to handwritten text recognition (HTR) should make use of both modalities in order to take advantage of the positive aspects of each one. A particularly interesting case where the need of this bi-modal processing arises is when an off-line text, written by some writer, is considered along with the on-line modality of the same text written by another writer. This happens, for example, in computer-assisted transcription of old documents, where on-line text can be used to interactively correct errors made by a main off-line HTR system.
In order to develop adequate techniques to deal with this challenging bi-modal HTR recognition task, a suitable corpus is needed. We have collected such a corpus using data (word segments) from the publicly available off-line and on-line IAM data sets.
In order to provide the Community with an useful corpus to make easy tests, and to establish baseline performance figures, we have proposed this handwritten bi-modal contest.
Here is reported the results of the contest with two participants, one of them achieved a 0% classification error rate, whilst the other participant achieved an interesting 1.5%.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Toselli, A.H., Juan, A., Vidal, E.: Spontaneous handwriting recognition and classification. In: International Conference on Pattern Recognition, pp. 433–436 (August 2004)
España-Boquera, S., Castro-Bleda, M., Gorbe-Moya, J., Zamora-Martínez, F.: Improving Offline Handwritten Text Recognition with Hybrid HMM/ANN Models. IEEE Trans. Pattern Anal. Mach. Intell. (accepted for publication, 2010)
Gorbe-Moya, J., España-Boquera, S., Zamora-Martínez, F., Castro-Bleda, M.J.: Handwritten Text Normalization by using Local Extrema Classification. In: Proc. 8th International Workshop on Pattern Recognition in Information Systems, Barcelona, Spain, pp. 164–172 (2008)
Liwicki, M., Bunke, H.: Iam-ondb - an on-line english sentence database acquired from handwritten text on a whiteboard. In: 8th Intl. Conf. on Document Analysis and Recognition, vol. 2, pp. 956–961 (2005)
Marcus Liwicki, M., Bunke, H.: Combining on-line and off-line bidirectional long short-term memory networks for handwritten text line recognition. In: Proceedings of the 11th Int. Conference on Frontiers in Handwriting Recognition, pp. 31–36 (2008)
Marti, U., Bunke, H.: A full english sentence database for off-line handwriting recognition. In: Proc. of the 5th Int. Conf. on Document Analysis and Recognition, pp. 705–708 (1999)
Pastor, M., Toselli, A.H., Casacuberta, F., Vidal, E.: A bi-modal handwritten text corpus: baseline results. In: Ünay, D., Çataltepe, Z., Aksoy, S. (eds.) ICPR 2010. LNCS, vol. 6388, pp. 1–13. Springer, Heidelberg (2010)
Pastor, M., Toselli, A.H., Vidal, E.: Writing Speed Normalization for On-Line Handwritten Text Recognition. In: Proc. of the Eighth International Conference on Document Analysis and Recognition (ICDAR 2005), Seoul, Korea, pp. 1131–1135 (August 2005)
Johansson, G.L.S., Goodluck, H.: Manual of information to accompany the lancaster-oslo/bergen corpus of british english, for use with digital computers (1978)
Toselli, A.H., Romero, V., Rodríguez, L., Vidal, E.: Computer Assisted Transcription of Handwritten Text. In: International Conference on Document Analysis and Recognition, pp. 944–948 (2007)
Toselli, A.H., Romero, V., Vidal, E.: Computer assisted transcription of text images and multimodal interaction. In: Popescu-Belis, A., Stiefelhagen, R. (eds.) MLMI 2008. LNCS, vol. 5237, pp. 296–308. Springer, Heidelberg (2008)
Viard-Gaudin, C., Lallican, P., Knerr, S., Binter, P.: The ireste on/off (ironoff) dual handwriting database. In: International Conference on Document Analysis and Recognition, pp. 455–458 (1999)
Vinciarelli, A., Perrone, M.: Combining online and offline handwriting recognition. In: International Conference on Document Analysis and Recognition, p. 844 (2003)
Young, S., Odell, J., Ollason, D., Valtchev, V., Woodland, P.: The HTK Book: Hidden Markov Models Toolkit V2.1. Cambridge Research Laboratory Ltd. (March 1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pastor, M., Paredes, R. (2010). Bi-modal Handwritten Text Recognition (BiHTR) ICPR 2010 Contest Report. In: Ünay, D., Çataltepe, Z., Aksoy, S. (eds) Recognizing Patterns in Signals, Speech, Images and Videos. ICPR 2010. Lecture Notes in Computer Science, vol 6388. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17711-8_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-17711-8_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17710-1
Online ISBN: 978-3-642-17711-8
eBook Packages: Computer ScienceComputer Science (R0)