Optimising Handwritten-Character Recognition with Logic Neural Networks

  • G. Tambouratzis


This article studies the implementation of a handwritten character recognition task using neural networks. Two logic neural network models axe employed to classify the Essex dataset, which comprises real-world hand-written characters. To reduce the underlying dataset variation, several pre-processing approaches are investigated. This allows the comparison of the network models on the basis of their classification accuracy for datasets with different characteristics.


Recognition Rate Training Pattern Handwritten Character Binary Pixel Logic Neural Network 
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.


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  1. [1]
    I. Aleksander and H. Morton. An Introduction to Neural Computing. Chapman and Hall, 1990.Google Scholar
  2. [2]
    I. Aleksander, W. V. Thomas, and P. A. Bowden. Wisard: A radical step forward in image recognition. Sensor Review, pages 120–124, July 1984.Google Scholar
  3. [3]
    A. Amiri, A. C. Downton, S. J. Hanlon, C. G. Leedham, S. M. Lucas, and D. Monger. Oscar: A visual programming toolkit for off-line hand-written form recognition. In Proceedings of the 4th International Workshop on Frontiers in Handwriting Recognition, pages 441–448. Taipei, Taiwan, December 1994.Google Scholar
  4. [4]
    S. Lucas and A. Amiri. Statistical syntactic methods for high-performance ocr. IEE Proceedings on Vision, Image and Signal Processing, 143(1):23–30, 1996.Google Scholar
  5. [5]
    G. Tambouratzis. Applying logic neural networks to hand-written character recognition tasks. In Proceedings of the ICTAI’96 Conference, pages 268–271. Toulouse, France, IEEE Press, 16–19 November 1996.Google Scholar
  6. [6]
    G. Tambouratzis and T. J. Stonham. Evaluating the topology-preservation capabilities of a self-organising logical neural network. Pattern Recognition Letters, 14(11):927–934, 1993.MATHCrossRefGoogle Scholar
  7. [7]
    G. Tambouratzis and D. Tambouratzis. Self-Organisation in Complex Pattern Spaces Using a Logic Neural Network, Network: Computation in Neural Systems, volume 5, pages 599–617. 1994.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Wien 1998

Authors and Affiliations

  • G. Tambouratzis
    • 1
  1. 1.Institute for Language and Speech ProcessingAthensGreece

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