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

2001

@article{AkH2001,
	vgclass =	{refpap},
	author =	{Selim Aksoy and Robert M. Haralick},
	title =	{Feature normalization and likelihood-based similarity
	measures for image retrieval},
	journal =	{Pattern Recognition Letters},
	volume =	{22},
	number =	{5},
	pages =	{563--582},
	month =	{April},
	year =	{2001},
	url =	{http://dx.doi.org/10.1016/S0167-8655(00)00112-4},
	abstract =	{Distance measures like the Euclidean distance are used to
	measure similarity between images in content-based image retrieval.
	Such geometric measures implicitly assign more weighting to features
	with large ranges than those with small ranges. This paper discusses
	the effects of five feature normalization methods on retrieval
	performance. We also describe two likelihood ratio-based similarity
	measures that perform significantly better than the commonly used
	geometric approaches like the $L_p$ metrics.},
}