A Structural Method on Grapheme Segmentation of Hangul Characters for OCR

In this paper, we propose Hangul grapheme segmentation method by structural approach, which is developed on the machine printed characters with the widely known fonts such as Myunjo, Gulim and Gothic and applied to much more deformed fonts. The process is composed of two steps. One is a structural grapheme segmentation to the characters classified into 20 types, more a reasonable classification than 6 types in that the algorithm of the grapheme segmentation can be simpler and more effective by the intensified common features of 20 types. Furthermore, it is quite easy for 20 type classified characters to be postprocessed using the connected components separated by the boundary information. With the proposed method, we got 99% correct segmentation rate with very high execution speed.