Abstract
The National Optics Institute is currently carrying out a project in automatic target recognition in order to locate, recognize, and track potential targets (e.g. tanks or troop carriers) monitored in real time by an infrared camera. In this paper, we present an algorithm based on the Distance Classifier Correlation Filter (DCCF), a subclass of the Synthetic Discriminant Functions family which are often used to solve the target recognition problem. We describe the general approach of DCCF-based template matching and the algorithms used. The effect of the training set on the discrimination performance, the optical implementation, and a few practical results are also presented. For a three-class recognition, only 3 misclassifications have been reported on a data bank of more than 200 images.
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© 1996 Springer-Verlag Berlin Heidelberg
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Gauvin, J., Doucet, M., Gingras, D., Chevrette, P. (1996). Coding of image data via correlation filters for invariant pattern recognition: Some practical results. In: Chouinard, JY., Fortier, P., Gulliver, T.A. (eds) Information Theory and Applications II. CWIT 1995. Lecture Notes in Computer Science, vol 1133. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0025149
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DOI: https://doi.org/10.1007/BFb0025149
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