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Proceedings Paper

Support vector machine application on vehicles
Author(s): Michael Del Rose; Jack Reed
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Paper Abstract

In this paper, methods of choosing a vehicle out of an image are explored. Digital images are taken from a monocular camera. Image processing techniques are applied to each single frame picture to create the feature vector. Finally the resulting features are used to classify whether there is a car in the picture or not using support vector machines. The results are compared to those obtained using a neural network. A discussion on techniques to enhance the feature vector and the results from both learning machines will be included.

Paper Details

Date Published: 14 November 2001
PDF: 6 pages
Proc. SPIE 4479, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation IV, (14 November 2001); doi: 10.1117/12.448342
Show Author Affiliations
Michael Del Rose, U.S. Army Tank-Automotive and Armaments Command (United States)
Jack Reed, U.S. Army Tank-Automotive and Armaments Command (United States)


Published in SPIE Proceedings Vol. 4479:
Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation IV
Bruno Bosacchi; David B. Fogel; James C. Bezdek, Editor(s)

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