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...

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Bibliographic Details
Main Author: Syeda-Mahmood, Tanveer Fathima
Language:en_US
Published: 2004
Subjects:
Online Access:http://hdl.handle.net/1721.1/5994
Description
Summary: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.