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Proceedings Paper

Object detection using scale space
Author(s): V. A. Topkar; Bradley Pryor Kjell; Arun K. Sood
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Paper Abstract

Scale-space representation is a topic of active research in computer vision. Most of the work so far has concentrated on image reconstruction from the scale-space representation. In this paper we discuss the use of scale- space representation for object detection. We have proposed a model based approach and developed an algorithm to implement it. Channel integration is the heart of the algorithm and there are a number of unresolved issues in it. Object detection is possible only if the objects of interest are different from the noise and clutter in certain features. We have used two different images, one with good signal to noise ratio and the other with poor signal to noise ratio In the first image the distinguishing feature of the object is its signal strength and in the second image it is its size. Accordingly we have studied two approaches to the channel integration : (i) based on the contrast value and (ii) based on edge focusing and splitting. The results of both approaches are presented and discussed.

Paper Details

Date Published: 1 January 1990
PDF: 12 pages
Proc. SPIE 1293, Applications of Artificial Intelligence VIII, (1 January 1990); doi: 10.1117/12.21047
Show Author Affiliations
V. A. Topkar, George Mason Univ. (United States)
Bradley Pryor Kjell, George Mason Univ. (United States)
Arun K. Sood, George Mason Univ. (United States)

Published in SPIE Proceedings Vol. 1293:
Applications of Artificial Intelligence VIII
Mohan M. Trivedi, Editor(s)

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