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Proceedings Paper

A Simple Tunable Interest Operator and Some Applications
Author(s): Daryl T. Lawton; Michael Callahan
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Paper Abstract

The extraction and classification of significant points along a contour is fundamental to many image processing tasks. In this paper, we present a simple process for extracting such points with several appealing properties: the operation is developed in terms of contours which are represented discretely; it is completely local and hence suitable for real time operation in vector or parallel processors; and it is tunable to extract significant points at different resolutions of orientation change along a contour. We also describe its use in linear feature extraction and processing restricted cases of environmental motion where the interest operator associates parameterized attributes with extracted image points. Matching features using these attributes allows for significant computational reductions over schemes based upon correlation matching without any loss of robustness, especially for such cases of restricted motion.

Paper Details

Date Published: 5 April 1985
PDF: 8 pages
Proc. SPIE 0548, Applications of Artificial Intelligence II, (5 April 1985); doi: 10.1117/12.948426
Show Author Affiliations
Daryl T. Lawton, Advanced Information & Decision Systems (United States)
Michael Callahan, University of Massachusetts (United States)


Published in SPIE Proceedings Vol. 0548:
Applications of Artificial Intelligence II
John F. Gilmore, Editor(s)

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