Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICPR.2004.1333902
Title: Italic font recognition using stroke pattern analysis on wavelet decomposed word images
Authors: Zhang, L. 
Lu, Y. 
Tan, C.L. 
Issue Date: 2004
Source: Zhang, L.,Lu, Y.,Tan, C.L. (2004). Italic font recognition using stroke pattern analysis on wavelet decomposed word images. Proceedings - International Conference on Pattern Recognition 4 : 835-838. ScholarBank@NUS Repository. https://doi.org/10.1109/ICPR.2004.1333902
Abstract: This paper describes an italic font recognition method using stroke pattern analysis on wavelet decomposed word images. The word images are extracted from scanned text documents containing word objects in various fonts and styles. Earlier font recognition methods mainly focus on slanted texture or pattern analysis on single character or large text blocks, which are sensitive to noise and subject to font and style variations such as size, serifness, boldness, etc. Our method takes advantage of 2-D wavelet decomposition on each word image and performs statistical analysis on stroke patterns obtained from wavelet decomposed sub-images. Experiments are carried out with 22,384 frequently used word images in both normal and italic styles of four different fonts. On average, a recognition accuracy of 95.76% for normal style and 96.49% for italic style is achieved. Experiments conducted on word images extracted from scanned documents with scattered italic words also show an encouraging result.
Source Title: Proceedings - International Conference on Pattern Recognition
URI: http://scholarbank.nus.edu.sg/handle/10635/40287
ISBN: 0769521282
ISSN: 10514651
DOI: 10.1109/ICPR.2004.1333902
Appears in Collections:Staff Publications

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