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Multiresolution analysis of connectivity

journal contribution
posted on 2005-01-01, 00:00 authored by Atul SajjanharAtul Sajjanhar, G Lu, D Zhang, T Qi
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.

History

Journal

Lecture notes in computer science

Volume

3578

Pagination

56 - 62

Publisher

Springer-Verlag

Location

Heidelberg, Germany

ISSN

1611-3349

eISSN

0302-9743

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2005, Springer-Verlag

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