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Multiscale texture classification and retrieval based on magnitude and phase features of complex wavelet subbands

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Çelik, Turgay and Tjahjadi, Tardi (2011) Multiscale texture classification and retrieval based on magnitude and phase features of complex wavelet subbands. Computers & Electrical Engineering, Vol.37 (No.5). pp. 729-743. doi:10.1016/j.compeleceng.2011.06.008 ISSN 0045-7906.

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Official URL: http://dx.doi.org/10.1016/j.compeleceng.2011.06.00...

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Abstract

This paper proposes a multiscale texture classifier which uses features extracted from both magnitude and phase responses of subbands at different resolutions of the dual-tree complex wavelet transform decomposition of a texture image. The mean and entropy in the transform domain are used to form a feature vector. The proposed method can achieve a high texture classification rate even for small number of samples used in training stage. This makes it suitable for applications where the number of texture samples used in training is very limited. The superior performance and robustness of the proposed classifier is shown for classifying and retrieving texture images from image databases.

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): Texture mapping, Wavelets (Mathematics), Content-based image retrieval
Journal or Publication Title: Computers & Electrical Engineering
Publisher: Pergamon
ISSN: 0045-7906
Official Date: September 2011
Dates:
DateEvent
September 2011Published
Volume: Vol.37
Number: No.5
Number of Pages: 15
Page Range: pp. 729-743
DOI: 10.1016/j.compeleceng.2011.06.008
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 19 December 2015
Date of first compliant Open Access: 19 December 2015
Funder: University of Warwick Vice Chancellor Scholarship

Data sourced from Thomson Reuters' Web of Knowledge

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