Refereed full papers (journals, book chapters, international conferences)

2001

@article{ZaI2001,
	vgclass =	{refpap},
	author =	{John Zachary and S. S. Iyengar},
	title =	{Information theoretic similarity measures for content
	based image retrieval},
	journal =	{Journal of the American Society for Information Science and Technology (JASIST)},
	volume =	{52},
	number =	{10},
	pages =	{856--867},
	year =	{2001},
	url =	{http://dx.doi.org/10.1002/asi.1139},
	abstract =	{Content-based image retrieval is based on the idea of
	extracting visual features from image and using them to index images in
	a database. The comparisons that determine similarity between images
	depend on the representations of the features and the definition of
	appropriate distance function. Most of the research literature uses
	vectors as the predominate representation given the rich theory of
	vector spaces. While vectors are an extremely useful representation,
	their use in large databases may be prohibitive given their usually
	large dimensions and similarity functions. In this paper, we propose
	similarity measures and an indexing algorithm based on information
	theory that permits an image to be represented as a single number. When
	use in conjunction with vectors, our method displays improved
	efficiency when querying large databases.},
}