𝔖 Bobbio Scriptorium
✦   LIBER   ✦

On-line recognition of cursive Korean characters using graph representation

✍ Scribed by Keechul Jung; Hang Joon Kim


Publisher
Elsevier Science
Year
2000
Tongue
English
Weight
1021 KB
Volume
33
Category
Article
ISSN
0031-3203

No coin nor oath required. For personal study only.

✦ Synopsis


The automatic recognition of cursive Korean characters is a di$cult 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.


πŸ“œ SIMILAR VOLUMES


On-line recognition of Korean characters
✍ Sang Kyoon Kim; Se Myung Park; Jong Kook Lee; Hang Joon Kim πŸ“‚ Article πŸ“… 1998 πŸ› Elsevier Science 🌐 English βš– 861 KB

This paper proposes an efficient method for on-line recognition of cursive Korean characters. The recognition of cursive strokes and the representation of a large character set are important determinants in the recognition rate of Korean characters. To deal with cursive strokes, we classify them aut

Off-line cursive handwriting recognition
✍ Simon GΓΌnter; Horst Bunke πŸ“‚ Article πŸ“… 2005 πŸ› Elsevier Science 🌐 English βš– 281 KB

Unconstrained handwritten text recognition is one of the most difficult problems in the field of pattern recognition. Recently, a number of classifier creation and combination methods, known as ensemble methods, have been proposed in the field of machine learning. They have shown improved recognitio