Chinese text detection and location for images in multimedia messaging service

Yan, J; Tao, D; Tian, C; Gao, X; Li, X

Chinese text detection and location for images in multimedia messaging service

Yan, J Tao, D

Tian, C Gao, X Li, X

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Publication Type:: Conference Proceeding
Citation:: Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 2010, pp. 3896 - 3901
Issue Date:: 2010-12-01

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Field	Value	Language
dc.contributor.author	Yan, J	en_US
dc.contributor.author	Tao, D https://orcid.org/0000-0001-7225-5449	en_US
dc.contributor.author	Tian, C	en_US
dc.contributor.author	Gao, X	en_US
dc.contributor.author	Li, X	en_US
dc.date.issued	2010-12-01	en_US
dc.identifier.citation	Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 2010, pp. 3896 - 3901	en_US
dc.identifier.isbn	9781424465880	en_US
dc.identifier.issn	1062-922X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/17290
dc.description.abstract	Text detection and recognition for images in multimedia messaging service is a very important task. Since Chinese characters are composed of four kinds of strokes, i.e., horizontal line, top-down vertical line, left-downward slope line and short pausing stroke, we present Gabor filters with scale and direction varied to describe the strokes of Chinese characters for candidate text area extraction. By establishing four sub-neural networks to learn the texture of text area, the learnt classifiers are used to detect candidate text areas. Experimental results show that the proposed approach can improve the accuracy of text detection and the recognition rate of images in multimedia messaging service. ©2010 IEEE.	en_US
dc.relation.ispartof	Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics	en_US
dc.relation.isbasedon	10.1109/ICSMC.2010.5641748	en_US
dc.title	Chinese text detection and location for images in multimedia messaging service	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Istanbul, Turkey	en_US
dc.location.activity	University of Melbourne
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Text detection and recognition for images in multimedia messaging service is a very important task. Since Chinese characters are composed of four kinds of strokes, i.e., horizontal line, top-down vertical line, left-downward slope line and short pausing stroke, we present Gabor filters with scale and direction varied to describe the strokes of Chinese characters for candidate text area extraction. By establishing four sub-neural networks to learn the texture of text area, the learnt classifiers are used to detect candidate text areas. Experimental results show that the proposed approach can improve the accuracy of text detection and the recognition rate of images in multimedia messaging service. ©2010 IEEE.

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http://hdl.handle.net/10453/17290