On-line handwritten alphanumeric character recognition using feature sequences

  • Xiaolin Li
  • Dit-Yan Yeung
Session IA1c — Document Processing & Character Recognition
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1024)


In this paper we present an approach in which an on-line handwritten character is characterized by a sequence of dominant points in strokes and a sequence of writing directions between consecutive dominant points. The directional information is used for character preclassification and the positional information is used for fine classification. Doth preclassification and fine classification are based on dynamic programming matching. A recognition experiment has been conducted with 62 character classes of different writing styles and 21 people as data contributors. The recognition rate of this experiment is 91%, with 7.9% substitution rate and 1.1% rejection rate. The average processing time is 0.35 second per character on a 486 50MHz personal computer.


Recognition Rate Local Extremum Fine Classification Lowercase Letter Matching Graph 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Xiaolin Li
    • 1
  • Dit-Yan Yeung
    • 1
  1. 1.Department of Computer ScienceHong Kong University of Science and TechnologyKowloonHong Kong

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