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dc.contributor.authorLee, KLen_US
dc.contributor.authorChen, LHen_US
dc.date.accessioned2014-12-08T15:19:13Z-
dc.date.available2014-12-08T15:19:13Z-
dc.date.issued2005-05-01en_US
dc.identifier.issn0262-8856en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.imavis.2004.12.002en_US
dc.identifier.urihttp://hdl.handle.net/11536/13765-
dc.description.abstractIn this paper, an efficient computation method for computing the texture browsing descriptor of MPEG-7 is provided. Texture browsing descriptor is used to characterize a texture's regularity, directionality and coarseness. To compute the regularity of textures, Fourier transform is first performed. To get more discriminative features for regularity computation, the Fourier spectrum is treated as an image and the Fourier transform is performed again to produce an enhanced Fourier spectrum. A regularity measure based on the variance of the radial wedge distribution is then calculated to determine the regularity of textures. For regular textures, the texture primitives are assumed to be parallelograms, the two dominant directions are extracted by Hough transform. A scale computation method is then provided to determine the scales corresponding to the two dominant directions. In addition, principal component analysis is provided to detect textures with only one dominant direction. Experiments of texture browsing, coarse classification of textures and similarity-based image-to-image matching are performed on the texture images of Brodatz album and Corel Gallery image database to demonstrate the efficiency and effectiveness of the proposed method. The proposed method can be used in the applications of texture browsing and texture retrieval. (c) 2005 Elsevier B.V. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectimage retrievalen_US
dc.subjecttexture browsingen_US
dc.subjectMPEG-7en_US
dc.subjectdigital libraryen_US
dc.titleAn efficient computation method for the texture browsing descriptor of MPEG-7en_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.imavis.2004.12.002en_US
dc.identifier.journalIMAGE AND VISION COMPUTINGen_US
dc.citation.volume23en_US
dc.citation.issue5en_US
dc.citation.spage479en_US
dc.citation.epage489en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000228501300003-
dc.citation.woscount11-
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