An investigation into the feasibility of applying pattern recognition concepts to the classification of metallic objects by their electromagnetic response was performed. The effect on the response of various factors such as object shape and orientation was examined and a pattern recognition scheme was proposed based on these results. Implementation of the proposal involved the development of a novel extension to the nearest mean vector type of classifier in which the class "centroid" was generalized to be a curve in the feature space rather than a point.
The resultant pattern recognition scheme was tested on a representative test set which included 815 signatures of objects, corresponding to 104 variations in object and orientation. A success rate of greater than 98 percent was achieved. It is noted that the classifier extension developed provides a viable approach to classification of response signatures that vary continuously with respect to any single parameter. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate
|Creators||Chesney, Robert Harvey|
|Source Sets||University of British Columbia|
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