Search results for key=MoS2013b :
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Refereed full papers (journals, book chapters, international conferences)
2013
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Nabeel Mohammed and David McG. Squire,
Efficient and Accurate Independent Component Filter-based
Features for Texture Similarity,
In Proceedings of the 20th IEEE International Conference on Image Processing (ICIP),
Melbourne, Australia, pp. 2887-2891, September 15-18 2013.
This paper evaluates the accuracy and efficiency of
collection-specific texture features for Content-Based Image Retrieval.
Independent Component Analysis is used to extract Independent Component
Filters (ICF) from an image set. As these ICF are learned from the
image set, the hypothesis is that they should provide texture features
that are more effective than those extracted using generic filter
banks. We describe a method for extracting candidate ICF from an image
set, and choosing a representative subset from them. These are then
used to extract image features. A simple CBIR system has been developed
to evaluate the performance of these features on two standard texture
image collections, compared with features extracted using multiple
banks of Gabor filters. The results indicate that ICF-based features
perform better than Gabor-based features, even when a much smaller
number of ICF features is used than Gabor features. The ICF features
are thus more accurate, and more efficient.
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