Abstract
This paper deals with the problem of low level representation of 3D image contents. The presented solution makes use of multiresolution techniques to recover the so-called visual patterns or integral features that form images. It consists of decomposing the image into a set of elementary image features, representing frequency channels, using a filter bank, and grouping them by means of clustering analysis. The method introduces a novel design of the bank of oriented scaled filters. In addition, a new measure of dissimilarity between pairs of features is applied to the hierarchical clustering technique.
The authors desire to acknowledge the Xunta de Galicia for their financial support of this work by means of the research project PGIDT01TIC20601PN.
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© 2004 Springer-Verlag Berlin Heidelberg
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Dosil, R., Fdez-Vidal, X.R., Pardo, X.M. (2004). Multiresolution Approach to “Visual Pattern” Partitioning of 3D Images. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30125-7_81
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DOI: https://doi.org/10.1007/978-3-540-30125-7_81
Publisher Name: Springer, Berlin, Heidelberg
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