Recognition of on-line cursive Korean characters combining statistical and structural methods

Abstract

In this paper, we propose a hybrid recognition method, and show its usefulness in recognizing online cursive Korean characters. A finite state network is constructed to represent the rules of character composition from graphemes. In the network, each are and node expands into statistical and structural recognizers, respectively. The statistical recognizer produces intermediate recognition results in traditional hidden Markov modeling, then the structural recognizer analyzes them. The results from two recognizers are combined in a probabilistic framework complementing the Markov assumption of hidden Markov modeling. The experimental results showed significant performance improvements in error reduction and computation time as compared to the statistical approach alone. (C) 1997 Pattern Recognition Society. Published by Elsevier Science Ltd.