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1 January 1990 Object detection using scale space
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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.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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