Binarization of old halftone text documents

Adak, C; Maitra, P; Chaudhuri, BB; Blumenstein, M

Binarization of old halftone text documents

Adak, C

Maitra, P Chaudhuri, BB Blumenstein, M

Permalink

Publication Type:: Conference Proceeding
Citation:: IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2016, 2016-January
Issue Date:: 2016-01-05

Closed Access

	Filename	Description	Size
	07372982.pdf	Published version	3.01 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Adak, C https://orcid.org/0000-0002-9085-2770	en_US
dc.contributor.author	Maitra, P	en_US
dc.contributor.author	Chaudhuri, BB	en_US
dc.contributor.author	Blumenstein, M https://orcid.org/0000-0002-9908-3744	en_US
dc.date.issued	2016-01-05	en_US
dc.identifier.citation	IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2016, 2016-January	en_US
dc.identifier.isbn	9781479986415	en_US
dc.identifier.issn	2159-3442	en_US
dc.identifier.uri	http://hdl.handle.net/10453/98391
dc.description.abstract	© 2015 IEEE. A degraded document image should be cleaned before subjecting to Optical Character Recognition (OCR), otherwise the result may be erroneous. Though major studies have been conducted on degraded document image cleaning, halftone documents received less attention. Since halftone documents contain halftone dot patterns, classical binarization techniques do not produce proper output for feeding into the OCR engine. In this paper, old halftone documents are considered for text area cleaning and binarization. At the beginning, the zone of interest (text area) is found using local binary pattern and contour analysis. Reasonably smaller zones are filtered out as noise. Then the foreground pixels are separated using background estimation. After this, an automated spatial smoothing technique is employed on the foreground. At last, a local binarization technique is used to produce the binary image. The proposed method is tested on various old and degraded halftone documents, which has produced fairly good results.	en_US
dc.relation.ispartof	IEEE Region 10 Annual International Conference, Proceedings/TENCON	en_US
dc.relation.isbasedon	10.1109/TENCON.2015.7372982	en_US
dc.title	Binarization of old halftone text documents	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2016-January	en_US
utslib.for	0803 Computer Software	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 Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Strength - QSI - Centre for Quantum Software and Information
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	2016-January	en_US

Abstract:

© 2015 IEEE. A degraded document image should be cleaned before subjecting to Optical Character Recognition (OCR), otherwise the result may be erroneous. Though major studies have been conducted on degraded document image cleaning, halftone documents received less attention. Since halftone documents contain halftone dot patterns, classical binarization techniques do not produce proper output for feeding into the OCR engine. In this paper, old halftone documents are considered for text area cleaning and binarization. At the beginning, the zone of interest (text area) is found using local binary pattern and contour analysis. Reasonably smaller zones are filtered out as noise. Then the foreground pixels are separated using background estimation. After this, an automated spatial smoothing technique is employed on the foreground. At last, a local binarization technique is used to produce the binary image. The proposed method is tested on various old and degraded halftone documents, which has produced fairly good results.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/98391