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Distances between frequency features for 3D visual pattern partitioning
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DOI：10.1016/j.patrec.2005.12.006.png)
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Abstract
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In this paper we propose a technique for the decomposition of a 3D image into a set of low level patterns associated to phase congruency, which we call visual patterns. Those patterns have frequency components in a wide range of bands that are aligned in phase. The method involves clustering of the band-pass filtered versions of the image according to a measure of congruence in phase or, what is equivalent, alignment in the filter's responses energy maxima. This is achieved by defining a distance between the responses of pairs of filters and applying a hierarchical clustering analysis to the resulting distance matrix. To measure the degree of maxima alignment we propose a set of alternative distances and study their suitability. From this study we conclude that a measure of linear dependence between the local energy of filters' responses is more appropriate than a more general measure of dependence. (c) 2006 Elsevier B.V. All rights reserved.
Keywords:
low level feature extraction
visual pattern partitioning
multiresolution analysis
image dissimilarity estimation
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