On-Line Handwritten Alphanumeric Character Recognition Using Feature Sequences

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 preclas-siication and the positional information is used for ne classiication. Both preclassiication and ne classiication are based on dynamic programming matching. A recognition experiment has been conducted with 62 character classes of diierent 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.