Pen-coordinate information modeling by SCPR-based HMM for on-line Japanese handwriting recognition

This paper describes stochastic modeling of pen-coordinate information in HMMs with structured character pattern representation (SCPR) for on-line Japanese handwriting recognition. SUR allows HMMs for Kanji character patterns to share common subpatterns. Although SCPR-based HMMs have been successfully applied to Kanji character recognition, the pen-coordinate feature has not been modeled since it is unique feature in each character pattern. In this paper, we employ mapping from a common subpattern to each occurrence in Kanji patterns and adaptation of state parameters to each character pattern in generating character HMMs by composing SCPR-based HMMs. Experimental results show that the pen-coordinate feature modeled in the SCPR-based HMM effects significantly.