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A Neural Cursive Character Recognizer

  • Conference paper
Neural Nets WIRN Vietri-01

Part of the book series: Perspectives in Neural Computing ((PERSPECT.NEURAL))

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Abstract

This paper presents a cursive character recognizer embedded in an offline cursive script recognition system. The recognizer is composed of two modules: the first one is a feature extractor, the second one an LVQ. Experiments are reported on a database of about 58000 isolated characters.

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References

  1. G. Kim, V. Govindaraju, A lexicon driven approach to handwritten word recognition for real time applications, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, No. 4, 366–379, 1997.

    Article  Google Scholar 

  2. A.W. Senior, A.J. Robinson, An Off-Line Cursive Handwriting Recognition System, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No. 3, 309–321, 1998.

    Article  Google Scholar 

  3. T. Steinherz, E. Rivlin, N. Intrator, Off-Line Cursive Script Word Recognition - A Survey, International Journal of Document Analysis and Recognition, Vol. 2, No. 2, 1–33, 1999.

    Google Scholar 

  4. R.E. Bellman, S.E. Dreyfus, Applied Dynamic Programming, Princeton University Press, 1962.

    MATH  Google Scholar 

  5. F. Camastra, A. Vinciarelli, Cursive character recognition by Learning Vector Quantization, Pattern Recognition Letters, Vol. 22, No. 6–7, 625–629, 2001.

    Article  MATH  Google Scholar 

  6. J.J. Hull, A Database for Handwritten Text Recognition Research, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 16, No. 5, 550–554, 1994.

    Article  Google Scholar 

  7. G. Nicchiotti, C. Scagliola, Generalised Projections: a Tool for Cursive Character Normalization, Proceedings of 5th International Conference on Document Analysis and Recognition, 729–732, 1999.

    Google Scholar 

  8. T. Kohonen, Self-Organizing Maps, Springer Verlag, Berlin, 1997.

    MATH  Google Scholar 

  9. T. Martinetz, S. Berkovich, K. Schulten, “Neural Gas” network for vector quantization and its application to time-series prediction, IEEE Transactions on Neural Networks, Vol. 4, No. 4, 558–569, 1993.

    Article  Google Scholar 

  10. M. Stone, Cross-validatory choice and assessment of statistical prediction, Journal of the Royal Statistical Society, Vol. 36, No. 1, 111–147, 1974.

    MATH  Google Scholar 

  11. H. Yarnada, Y. Nakano, Cursive handwritten word recognition using multiple segmentation determined by contour analysis, IEICE Transactions on Informations and Systems, Vol. 79, No. 5, 111–147464–470, 1996.

    Google Scholar 

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Author information

Authors and Affiliations

  1. INFM-Computer Science Department (DISI), University of Genoa, Via Dodecaneso 35, 16146, Genova, Italy

    Francesco Camastra

Authors
  1. Francesco Camastra
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  2. Alessandro Vinciarelli
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Editor information

Editors and Affiliations

  1. DMI, Università di Salerno, 84081, Baronissi (SA), Italy

    Roberto Tagliaferri (Associate Professor of Computer Science and Neural Nets DMI) (Associate Professor of Computer Science and Neural Nets DMI)

  2. Dipartimento di Scienze Fisiche „E.R. Caianiello“, Università di Salerno, 84081, Baronissi (SA), Italy

    Maria Marinaro (Full Professor in Theoretical Physics) (Full Professor in Theoretical Physics)

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© 2002 Springer-Verlag London Limited

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Camastra, F., Vinciarelli, A. (2002). A Neural Cursive Character Recognizer. In: Tagliaferri, R., Marinaro, M. (eds) Neural Nets WIRN Vietri-01. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-0219-9_17

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  • DOI: https://doi.org/10.1007/978-1-4471-0219-9_17

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-85233-505-2

  • Online ISBN: 978-1-4471-0219-9

  • eBook Packages: Springer Book Archive

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