An Algorithm for Colour-based Natural Scene Text Segmentation

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dc.contributor.author Zeng, C
dc.contributor.author Jia, W
dc.contributor.author He, S
dc.contributor.editor Iwamura, M
dc.contributor.editor Shafait, F
dc.date.accessioned 2014-04-03T01:05:40Z
dc.date.issued 2012-01
dc.identifier.citation Lecture Notes in Computer Science, 2012, 7139, 7139 pp. 58 - 68
dc.identifier.issn 0302-9743
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/22204
dc.description.abstract Before the step for text recognition, a text image needs to be segmented into foreground containing only the text area and background. In this paper, a method is proposed for segmenting colour natural scene texts which suffer from a wide range of degradations with complex background. A text image is firstly processed by two 3-means clustering operations with different distance measurements. Then, a modified connected component (CC)-based validation method is used to obtain the text area after clustering. Thirdly, a proposed objective segmentation evaluation method is utilised to choose the final segmentation result from the two segmented text images. The proposed method is compared with other existing methods based on the ICDAR2003 public database. Experimental results show the effectiveness of the proposed method.
dc.format Ryan Stoker
dc.language English
dc.publisher Springer Heidelberg Dordrecht London NewYork
dc.relation.isbasedon 10.1007/978-3-642-29364-1_5
dc.title An Algorithm for Colour-based Natural Scene Text Segmentation
dc.type Journal Article
dc.parent Lecture Notes in Computer Science
dc.journal.volume 7139
dc.journal.number en_US
dc.publocation Beijing, China, en_US
dc.identifier.startpage 58 en_US
dc.identifier.endpage 68 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 990421
dc.personcode 044299
dc.personcode 10828832
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition 7139 en_US
dc.edition 7139
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords natural scene text segmentation, k-means clustering, connected component analysis (CCA), segmentation evaluation.
pubs.embargo.period Not known
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 Computing and Communications
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
pubs.consider-herdc true
utslib.collection.history Closed (ID: 3)


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