On-Line Handwriting Character Recognition Using Stroke Information

Abstract

For the purpose of improvement in computational time and recognition accuracy in the framework of stroke order- and number-free on-line handwriting character recognition, we performed structural analysis of the style of stroke order and stroke connection. From the real handwritten characters, chosen from among 2965 Chinese characters, we investigated the information on stroke order and connection, using the automatic stroke correspondence system. It was proved that the majority of real characters are written in fixed stroke order, and stroke order is predominantly in the standard stroke order; about 98.1 % of characters were located nearly in the standard order. Almost all stroke connections occur in the standard order (92.8 %), whereas 2 stroke connections occurred often, and stroke connections in nonstandard order occurred very rarely. In a comparison of our findings with the expected stroke connections, very few connections were found to actually occur. Moreover, we show the methods for incorporating the information on the completely stroke order- and number-free framework. The large improvement on both computational time and recognition accuracy are demonstrated by experiments.