On-line handwritten alphanumeric character recognition using dominant points in strokes

摘要

All alphanumeric characters can be written in certain styles with strokes of different shapes and positions. An on-line handwritten character written on a digitizing tablet is represented as a sequence of strokes, which are the loci of the pen tip from its pen-down to pen-up positions. In this paper, we present an approach to on-line handwritten alphanumeric character recognition based on sequential handwriting signals. In our approach, 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 of the dominant points is used for character pre-classification and the positional information is used for fine classification. Both pre-classification and fine classification are based on dynamic programming matching using the idea of band-limited time warping. These techniques are elastic, in that they can tolerate local variation and deformation. The issue of reference (or template) set evolution is also addressed. A recognition experiment has been conducted with 62 character classes (0–9, A–Z, a–z) of different writing styles (Italian manuscript style and some other 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 s per character on a 486 50 MHz personal computer.