Object detection using scale space

V. A. Topkar; Bradley Pryor Kjell; Arun K. Sood

doi:10.1117/12.21047

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1 January 1990 Object detection using scale space

V. A. Topkar; Bradley Pryor Kjell; Arun K. Sood

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Proceedings Volume 1293, Applications of Artificial Intelligence VIII; (1990) https://doi.org/10.1117/12.21047
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

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.

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V. A. Topkar, Bradley Pryor Kjell, and Arun K. Sood "Object detection using scale space", Proc. SPIE 1293, Applications of Artificial Intelligence VIII, (1 January 1990); https://doi.org/10.1117/12.21047

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KEYWORDS

Algorithm development

Reconstruction algorithms

Signal to noise ratio

Computer vision technology

Heart

Image restoration

Machine vision

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