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Data and Model-Driven Selection Using Color Regions

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.

Identiferoai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/5994
Date01 February 1992
CreatorsSyeda-Mahmood, Tanveer Fathima
Source SetsM.I.T. Theses and Dissertation
Languageen_US
Detected LanguageEnglish
Format29 p., 4497036 bytes, 1782485 bytes, application/postscript, application/pdf
RelationAIM-1270

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