Segmentation and Recognition of Continuous Handwriting Chinese Text

Abstract

This article introduces the basic segmentation problems in Chinese handwriting and also several prior work to solve these problems. A new segmentation method is proposed, which is applicable to both on-line and off-line systems for free-format handwritten Chinese character sentences. This method performs basic segmentation and fine segmentation based on the varying spacing thresholds and the minimum variance criteria. The five most probable ways of segmentation are derived from this stage and all the possible segments are extracted and recognized. A lattice is created from all the segments and searched using a viterbi based algorithm to find the most likely character sequence. The algorithm presented in this paper provides large flexibility and robustness to handle free-format continuous Chinese handwriting and is a promising solution for a natural and fast Chinese pen input system. The character accuracy is 85.0% for on-line and 77.4% for the off-line test data.