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

1996

@inproceedings{MAK1996,
	vgclass =	{refpap},
	vgproject =	{cbir},
	author =	{Farzin Mokhtarian and Sadegh Abbasi and Josef Kittler},
	title =	{Efficient and Robust Retrieval by Shape Content through
	Curvature Scale Space},
	booktitle =	{Image Databases and Multi-Media Search},
	address =	{Amsterdam, The Netherlands},
	pages =	{35--42},
	month =	{August},
	year =	{1996},
	abstract =	{We introduce a very fast and reliable method for shape
	similarity retrieval in large image databases which is robust with
	respect to noise, scale and orientation changes of the objects. The
	maxima of curvature zero-crossing contours of Curvature Scale Space
	(CSS) image are used to represent the shapes of object boundary
	contours. While a complex boundary is represented by about five pairs
	of integer values, and effective indexing method based on the aspect
	ratio of the CSS image, eccentricity and circularity is used to narrow
	down the range of searching.  Since the matching algorithm has been
	designed to use global information, it is sensitive to major occlusion,
	but some minor occlusion will not cause any problems.

	We have tested and evaluated our method on a prototype database of 450
	images of marine animals with a vast variety of shapes with very good
	results. The method can either be used in real applications or produce
	a reliable shape description for more complicated images when other
	features such as color and texture should also be considered.

	Since shape similarity is a subjective issue, in order to evaluate the
	method, we asked a number of volunteers to perform similarity retrieval
	based on shape on a randomly selected small database. We then compared
	the results of this experiment to the outputs of our system to the same
	queries and on the same database. The comparison indicated a promising
	performance of the system.},
}