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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Sajjanhar, A., Lu, G., Zhang, D., & Qi, T. (2005). Multiresolution analysis of connectivity. In Lecture Notes in Computer Science (Vol. 3578, pp. 56–62). Springer Verlag. https://doi.org/10.1007/11508069_8
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