Abstract
This paper introduces a general methodology for detecting and reducing the errors in a handwriting recognition task. The methodology is based on confidence modeling and its main difference is the use of two parallel classifiers for error assessment. The experimental benchmark associated with this approach is described as well as exhaustive results are provided for two real world recognizers on a large database.
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
Zimmermann, M., Bertolami, R., Bunke, H.: Rejection strategies for off-line handwritten sentence recognition. In: Proceedings of the 17th international conference on pattern recognition (ICPR’04), pp. 550–553 (2004)
Kittler, J., Hatef, M., Duin, R.P.W., Matas, J.: On combining classifiers. IEEE Transactions on Pattern Analysis and Machine Intelligence 20, 226–239 (1998)
Pitrelli, J.F., Subrahmonia, J., Perrone, M.P.: Confidence modeling for handwriting recognition: algorithms and applications. International Journal on Document Analysis and Recognition 8(1), 35–46 (2006)
Pitrelli, J.F., Perrone, M.P.: Confidence modelling for verification post-processing for handwriting recognition. In: Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR’02), p. 30 (2002)
Brakensiek, A., Rottland, J., Rigoll, G.: Confidence measures for an address reading system. In: Proceedings of the seventh international conference on document analysis and recognition (ICDAR’03), p. 294 (2003)
Arlandis, J., Perez-Cortes, J., Cano, J.: Rejection strategies and confidence measures for a k-NN classifier in an OCR task. In: Proceedings of the 16th International Conference on Pattern Recognition, pp. 576–579 (2002)
Aksela, M., Laaksonen, J., Oja, E., Kangas, J.: Rejection methods for an adaptive commitee classifier. In: Proceedings of the Sixth International Conference on Document Analysis and Recognition (ICDAR’01), pp. 982–986 (2001)
Gader, P.D., Mohamed, M.A., Keller, J.M.: Fusion of handwritten word classifiers. Pattern Recognition Letters 17, 577–584 (1996)
Rahman, A.F.R., Fairhurst, M.C.: Introducing new multiple expert decision combination topologies: A case study using recognition of handwritten characters. In: Proceedings of the 4th International Conference on Document Analysis and Recognition (ICDAR’97), p. 886 (1997)
Guyon, I., Schomaker, L., Plamondon, R., Liberman, M., Janet, S.M.: Unipen project of on-line data exchange and recognizer benchmarks. In: Proceedings of the 12th International Conference on Pattern Recognition (ICPR’94), pp. 29–33 (1994)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Rodríguez, J.A., Sánchez, G., Lladós, J. (2007). Rejection Strategies Involving Classifier Combination for Handwriting Recognition. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72849-8_13
Download citation
DOI: https://doi.org/10.1007/978-3-540-72849-8_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72848-1
Online ISBN: 978-3-540-72849-8
eBook Packages: Computer ScienceComputer Science (R0)