WORD-LEVEL OPTICAL FONT RECOGNITION USING TYPOGRAPHICAL FEATURES
SOO H. KIM, H.K. Kwag, Ching Y. Suen · International Journal of Pattern Recognition and Artificial Intelligence · 2004
Previous research efforts on optical font recognition have mostly limited applications since they deal with only a few types of font attributes and estimate them from a line or block of text. This paper proposes a word-level optical font recognition system for printed Korean and English documents. At the word-level, it has the advantages of obtaining more detailed font attributes including the following: script (Korean and English), font style (regular, bold, italic, and underlined), typeface (Myung-jo and Gothic), point size (10, 12, 14 pts), and word length (2, 3, 4, 5 for Korean, and 4 to 10 for English). A hierarchical classifier and several typographical features have been devised for the system, and their effectiveness are proven by an experiment with a database of 100 sets of 264 font categories.