Abstract

In this paper, we propose a novel postprocessing approach for on-line handwriting recognition. Differing from the existing linguistic knowledge-based methods, we make use of domain specific knowledge to improve the performance of recognition. Our system recognizes doctor’s handwriting which often poses great challenges in readability, and then enhances the quality of recognized text by analyzing and restoring the text with a medical knowledge model. We show experiments with this approach on a set of medical handwriting data provided by the doctor, and the results are promising. 1.

Citations