Graph-based text segmentation using a selected channel image

Zeng, C; Jia, W; He, X; Yang, J

Graph-based text segmentation using a selected channel image

Zeng, C Jia, W

He, X

Yang, J

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010, 2010, pp. 535 - 539
Issue Date:: 2010-12-01

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Field	Value	Language
dc.contributor.author	Zeng, C	en_US
dc.contributor.author	Jia, W https://orcid.org/0000-0002-0940-3338	en_US
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.contributor.author	Yang, J	en_US
dc.date.issued	2010-12-01	en_US
dc.identifier.citation	Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010, 2010, pp. 535 - 539	en_US
dc.identifier.isbn	9780769542713	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16104
dc.description.abstract	This paper proposes a graph-based method for segmentation of a text image using a selected colour-channel image. The text colour information usually presents a two-polarity trend. According to the observation that the histogram distributions of the respective colour channel images are usually different from each other, we select the colour channel image with the histogram having the biggest distance between the two main peaks, which represents the main foreground colour strength and background colour strength respectively. The peak distance is estimated by the mean-shift procedure performed on each individual channel image. Then, a graph model is constructed on a selected channel image to segment the text image into foreground and background. The proposed method is tested on a public database, and its effectiveness is demonstrated by the experimental results. © 2010 IEEE.	en_US
dc.relation.ispartof	Proceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010	en_US
dc.relation.isbasedon	10.1109/DICTA.2010.95	en_US
dc.title	Graph-based text segmentation using a selected channel image	en_US
dc.type	Conference Proceeding
utslib.for	080109 Pattern Recognition and Data Mining	en_US
utslib.for	080106 Image Processing	en_US
utslib.for	080104 Computer Vision	en_US
dc.location.activity	Sydney, Australia	en_US
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
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

This paper proposes a graph-based method for segmentation of a text image using a selected colour-channel image. The text colour information usually presents a two-polarity trend. According to the observation that the histogram distributions of the respective colour channel images are usually different from each other, we select the colour channel image with the histogram having the biggest distance between the two main peaks, which represents the main foreground colour strength and background colour strength respectively. The peak distance is estimated by the mean-shift procedure performed on each individual channel image. Then, a graph model is constructed on a selected channel image to segment the text image into foreground and background. The proposed method is tested on a public database, and its effectiveness is demonstrated by the experimental results. © 2010 IEEE.

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http://hdl.handle.net/10453/16104