Search results for key=MoS2013b : 1 match found.

2013

• @inproceedings{MoS2013b,
  	vgclass =	{refpap},
  	author =	{Nabeel Mohammed and Squire, David McG.},
  	title =	{Efficient and Accurate Independent Component Filter-based
  	Features for Texture Similarity},
  	booktitle =	{Proceedings of the 20th IEEE International Conference on Image Processing (ICIP)},
  	address =	{Melbourne, Australia},
  	pages =	{2887--2891},
  	month =	{September~15--18},
  	year =	{2013},
  	doi =	{https://doi.org/10.1109/ICIP.2013.6738594},
  	abstract =	{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.},
  }