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

1999

@article{APV1999,
	vgclass =	{refpap},
	vgproject =	{cbir},
	author =	{Dimitrios Androutsos and Kostas N. Plataniotis and
	Anastasios N. Venetsanopoulos},
	title =	{A Novel Vector-Based Approach to Color Image Retrieval
	Using a Vector Angular-Based Distance Measure},
	journal =	{Computer Vision and Image Understanding (special issue on content-based access for image
	and video libraries)},
	volume =	{75},
	number =	{1/2},
	pages =	{46--58},
	month =	{July/August},
	year =	{1999},
	abstract =	{Color is the characteristic which is most used for image
	indexing and retrieval. Due to its simplicity, the color histogram
	remains the most commonly used method for this task. However, the lack
	of good perceptual histogram similarity measures, the global color
	content of histograms, and the erroneous retrieval results due to gamma
	nonlinearity, call for improved methods. We present a new scheme which
	implements a recursive HSV-space segmentation technique to identify
	perceptually prominent color areas. The average color vector of these
	extracted areas are then used to build the image indices, requiring
	very little storage. Our retrieval is performed by implementing a
	combination distance measure, based on the vector angle between two
	vectors. Our system provides accurate retrieval results and high
	retrieval rate. It allows for queries based on single or multiple
	colors and, in addition, it allows for certain colors to be excluded in
	the query. This flexibility is due to our distance measure and the
	multidimensional query space in which the retrieval ranking of the
	database images is determined. Furthermore, our scheme proves to be
	very resistant to gamma nonlinearity providing robust retrieval results
	for a wide range of gamma nonlinearity values, which proves to be of
	great importance since, in general, the image acquisition source is
	unknown.},
}