Writer adaptation of online handwriting models

@article{Connell1999WriterAO,
  title={Writer adaptation of online handwriting models},
  author={Scott D. Connell and Anil K. Jain},
  journal={Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318)},
  year={1999},
  pages={434-437}
}
Writer adaptation is the process of converting a writer-independent handwriting recognition system, which models the characteristics of a large group of writers, into a writer-dependent system, which is tuned for a particular writer. Adaptation has the potential of increasing recognition accuracies, provided adequate models can be constructed for a particular writer. The limited amount of data that a writer typically provides makes the role of writer-independent models crucial in the adaptation… CONTINUE READING

Results and Topics from this paper.

Key Quantitative Results

  • Our results show an average reduction in error rate of 16.3% for lowercase characters as compared against representing each of the writer's character classes with a single model.

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References

Publications referenced by this paper.
SHOWING 1-10 OF 10 REFERENCES

and M

J. Subrahmonia, K. Nathan
  • Perrone, \Writer Dependent Recognition of On-line Unconstrained Handwriting," Proceedings of ICASSP'96, Atlanta, GA., vol. 6, pp. 3478-3481
  • 1996
VIEW 1 EXCERPT

and H

K. S. Nathan, H.S.M. Beigi, H. Subrahmonia, G. J. Clary
  • Maruyama, \Real-Time On-Line Unconstrained Handwriting Recognition Using Statistical Methods," ICASSP'95, vol. 4, pp. 2619-2623
  • 1995
VIEW 1 EXCERPT

A connectionist recognizer for on-line cursive handwriting recognition

  • Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing
  • 1994
VIEW 1 EXCERPT

Evaluation of Motor Models of Handwriting,

R. Plamondon, F. J. Maarse, An
  • IEEE Trans. Systems, Man, and Cybernetics,
  • 1989
VIEW 1 EXCERPT

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