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Multiresolution analysis of connectivity

Sajjanhar, Atul, Lu, Guojun, Zhang, Dengsheng and Qi, Tian 2005, Multiresolution analysis of connectivity, Lecture notes in computer science, vol. 3578, pp. 56-62, doi: 10.1007/11508069_8.

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Title Multiresolution analysis of connectivity
Author(s) Sajjanhar, AtulORCID iD for Sajjanhar, Atul
Lu, Guojun
Zhang, Dengsheng
Qi, Tian
Journal name Lecture notes in computer science
Volume number 3578
Start page 56
End page 62
Publisher Springer-Verlag
Place of publication Heidelberg, Germany
Publication date 2005
ISSN 1611-3349
Summary Multiresolution histograms have been used for indexing and retrieval of images. Multiresolution histograms used traditionally are 2d-histograms which encode pixel intensities. Earlier we proposed a method for decomposing images by connectivity. In this paper, we propose to encode centroidal distances of an image in multiresolution histograms; the image is decomposed a priori, by connectivity. Multiresolution histograms thus obtained are 3d-histograms which encode connectivity and centroidal distances. The statistical technique of Principal Component Analysis is applied to multiresolution 3d-histograms and the resulting data is used to index images. Distance between two images is computed as the L2-difference of their principal components. Experiments are performed on Item S8 within the MPEG-7 image dataset. We also analyse the effect of pixel intensity thresholding on multiresolution images.
Language eng
DOI 10.1007/11508069_8
Field of Research 080106 Image Processing
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2005, Springer-Verlag
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Document type: Journal Article
Collection: School of Information Technology
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