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Unsupervised colour image segmentation using dual-tree complex wavelet transform

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Çelik, Turgay and Tjahjadi, Tardi (2010) Unsupervised colour image segmentation using dual-tree complex wavelet transform. Computer Vision and Image Understanding, Vol.114 (No.7). pp. 813-826. doi:10.1016/j.cviu.2010.03.002 ISSN 1077-3142.

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Official URL: http://dx.doi.org/10.1016/j.cviu.2010.03.002

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Abstract

In this paper we present an effective unsupervised colour image segmentation algorithm which uses multiscale edge information and spatial colour content. The multiscale edge information is extracted using the dual-tree complex wavelet transform. Binary morphological operators are applied to the edge information to detect seed regions which are large enough to exclude boundary-only regions. The segmentation of homogeneous regions is obtained using region growing followed by region merging in the CIE L*a*b* colour space. We also present an edge preserving smoothing filter as a pre-process for the algorithm. We compare our algorithm with state-of-the-art algorithms and show its superior performance.

Item Type: Journal Article
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science, Engineering and Medicine > Engineering > Engineering
Library of Congress Subject Headings (LCSH): Image processing -- Digital techniques, Wavelets (Mathematics)
Journal or Publication Title: Computer Vision and Image Understanding
Publisher: Elsevier Science Inc.
ISSN: 1077-3142
Official Date: July 2010
Dates:
DateEvent
July 2010Published
Volume: Vol.114
Number: No.7
Number of Pages: 14
Page Range: pp. 813-826
DOI: 10.1016/j.cviu.2010.03.002
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 3 December 2015
Date of first compliant Open Access: 3 December 2015
Funder: University of Warwick Vice Chancellor Scholarship

Data sourced from Thomson Reuters' Web of Knowledge

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