On-line recognition of cursive Korean characters using graph representation

The automatic recognition of cursive Korean characters is a difficult problem, not only due to the multiple possible variations involved in the shapes of characters. but also because of the interconnections of neighboring graphemes within an individual character. This paper proposes a recognition method for Korean characters using graph representation. This method uses a time-delay neural network (TDNN) and graph-algorithmic post-processor for grapheme recognition and character composition, respectively. The proposed method was evaluated using multi-writer cursive characters in a boxed input mode. For a test data set containing 26,500 hand-written cursive characters, a 92.3% recognition rate was obtained. (C) 2000 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.