Abstract: Proposed in the paper here is a new post processing method integrating the rulebased grammar and the Markov language model for online handwritten Chinese character recognition. The Markov language model and the quantification rules model are bound to a linguistic decoder by word lattice. The post processing kernel engine consists of three stages: word lattice formation, linguistic decoder,and cache\|based self\|learning mechanism. The linguistic decoder adopts Viterbi search algorithm to search the best sentence hypothesis. The introduced technique has been applied to HPCs online handwritten Chinese character recognition,with a recognition accuracy rate of 91.3% achieved.