JOURNAL ARTICLE

WORD-LEVEL OPTICAL FONT RECOGNITION USING TYPOGRAPHICAL FEATURES

Soo Hyun KimH.K. KwagChing Y. Suen

Year: 2004 Journal:   International Journal of Pattern Recognition and Artificial Intelligence Vol: 18 (04)Pages: 541-561   Publisher: World Scientific

Abstract

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.

Keywords:
Font Typeface Computer science Natural language processing Optical character recognition Artificial intelligence Word (group theory) Point (geometry) Classifier (UML) Speech recognition Linguistics Mathematics

Metrics

5
Cited By
0.26
FWCI (Field Weighted Citation Impact)
16
Refs
0.57
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Handwritten Text Recognition Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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