Data and Model-Driven Selection Using Color Regions

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/5994

Full metadata record

DC Field	Value	Language
dc.creator	Syeda-Mahmood, Tanveer Fathima	-
dc.date	2004-10-04T14:25:38Z	-
dc.date	2004-10-04T14:25:38Z	-
dc.date	1992-02-01	-
dc.date.accessioned	2013-10-09T02:42:20Z	-
dc.date.available	2013-10-09T02:42:20Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AIM-1270	-
dc.identifier	http://hdl.handle.net/1721.1/5994	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	A key problem in model-based object recognition is selection, namely, the problem of determining which regions in the image are likely to come from a single object. In this paper we present an approach that extracts and uses color region information to perform selection either based solely on image- data (data-driven), or based on the knowledge of the color description of the model (model -driven). The paper presents a method of perceptual color specification by color categories to extract perceptual color regions. It also discusses the utility of color-based selection in reducing the search involved in recognition.	-
dc.format	29 p.	-
dc.format	4497036 bytes	-
dc.format	1782485 bytes	-
dc.format	application/postscript	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AIM-1270	-
dc.subject	selection	-
dc.subject	color	-
dc.subject	recognition	-
dc.subject	saliency	-
dc.subject	visual attention	-
dc.subject	sregion segmentation	-
dc.title	Data and Model-Driven Selection Using Color Regions	-
Appears in Collections:	MIT Items

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