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Proceedings Paper

Locating Objects In A Complex Image
Author(s): Ben Dawson; George Treese
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Paper Abstract

A vision machine must locate possible objects before it can identify them. In simple images, where the objects and illumination are known, locating possible objects can be part of, and secondary to, identification. In complex, natural images it is more efficient to use a quick and simple method to locate possible objects first, and then to selectively identify them. This parallels the strategy normally used by the human visual system. We present a theory for how possible objects, called "blobs", will be represented in an image, and explore some measures of importance for these candidate objects. An example algorithm based on this theory can quickly generate a list of possible object locations for the identification computation. We discuss the implementation of this example algorithm on a standard image processing system.

Paper Details

Date Published: 11 July 1985
PDF: 8 pages
Proc. SPIE 0534, Architectures and Algorithms for Digital Image Processing II, (11 July 1985); doi: 10.1117/12.946579
Show Author Affiliations
Ben Dawson, Massachusetts Institute of Technology (United States)
George Treese, Massachusetts Institute of Technology (United States)


Published in SPIE Proceedings Vol. 0534:
Architectures and Algorithms for Digital Image Processing II
Francis J. Corbett, Editor(s)

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