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

1999

@inproceedings{PHS1999,
	vgclass =	{refpap},
	vgproject =	{cbir},
	author =	{Payne, Janet S. and Hepplewhite, Lee and Stonham, T. John},
	title =	{Evaluating content-based image retrieval techniques using
	perceptually based metrics},
	editor =	{Nasser M. Nasrabadi and Aggelos K. Katsaggelos},
	booktitle =	{Applications of Artificial Neural Networks in Image
	Processing IV},
	volume =	{3647},
	series =	{SPIE Proceedings},
	month =	{March},
	year =	{1999},
	url =	{http://www.brunel.ac.uk/\~{}eesrllh/papers/1999/tr-696.pdf},
	abstract =	{Content-based Image Retrieval is an area of growing
	interest. Various approaches exist which use color, texture, and shape
	for retrieving 'similar' images from a database. However, what do we
	mean by 'similar'. Traditionally, similarity is interpreted as distance
	in feature space. But this does not necessarily match the human users'
	expectations. We report on two human studies, which asked volunteers to
	select which imags they considered to be 'most like' each image from
	the Brodatz dataset. Although the images from the Brodatz set have the
	advantage of being an agreed standard in texture analysis, Brodatz
	certainly did not select his images with this in mind. The results from
	this study provide a justification for selecting a subset of the
	Brodatz data set for use in evaluating texture-based retrieval
	techniques. Images which humans have difficulty in agreeing which other
	images are 'most like' are also poor choices for comparison. Our result
	indicate which images are most likely to be classified as 'similar' by
	individual humans and that can also serve to evaluate computer-based
	retrieval techniques.},
}