Identification of Metallic Spheroids by Classification of Their Electromagnetic Induction Responses

Abstract

An investigation into the feasibility of applying pattern recognition concepts to the classification of metallic objects by their electromagnetic induction responses was performed. The effect on the response of a limited set of steel spheroids due to various factors such as object shape, size, and orientation was examined and a pattern recognition scheme based on these results was proposed. Implementation of the scheme involved the development of a novel extension to the nearest mean vector type of classifier in which the concept of the class mean as a point in feature space was generalized to be a curve. The resultant pattern recognition scheme was tested on a representative test set which included 815 responses, corresponding to 104 variations in object and orientation. A success rate of greater than 96 percent was achieved. It is noted that the classifier extension developed provides a viable approach to classification of responses that very continuously with respect to a single parameter.