Online Handwritten Japanese Character String Recognition Incorporating Geometric Context

Abstract

This paper describes an online handwritten Japanese character string recognition system integrating scores of geometric context, character recognition, and linguistic context. We give a string evaluation criterion for better integrating the multiple scores while overcoming the effect of string length variability. For measuring geometric context, we propose a statistical method for modeling both single- character and between-character plausibility. Our experimental results on TUAT HANDS databases show that the geometric context improves the character segmentation accuracy remarkably.