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.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/5994 |
| Date | 01 February 1992 |
| Creators | Syeda-Mahmood, Tanveer Fathima |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | en_US |
| Detected Language | English |
| Format | 29 p., 4497036 bytes, 1782485 bytes, application/postscript, application/pdf |
| Relation | AIM-1270 |
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