Substroke Matching by Segmenting and Merging for Online Korean Cursive Character Recognition

Chang-Soo Kim, Missouri University of Science and Technology
Kang Ryoung Park
Byung Hwan Jun
Jaihie Kim

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The Korean character is composed of several alphabets in two-dimensional formation and the total number of Korean characters exceeds eleven thousand. Therefore, the previous approaches to Korean cursive characters pay most of their attention to segmenting a character into alphabets accurately. However, it is difficult because the boundaries of alphabets are not apparent in most cases. We propose an alphabet-based method without assuming accurate alphabet segmentation. In the proposed method, a cursive character is segmented into substrokes by a set of segmenting conditions. Then it is matched with the reference substrokes generated from alphabet models and ligatures by segmenting and merging in the process of recognition. Among substrokes, a certain substroke can be either an alphabet itself a part of alphabet or a composite of the alphabet and ligature. We applied the proposed method to 5000 Korean characters and got the result of 83.4% for the first rank and 89.2% for the top 5 result candidates with the speed of 0.17 seconds on average per character on a PC which uses Intel Pentium 90 Mhz CPU.