Two-dimensional object recognition using multiresolution non-information-preserving shape features

Abstract The performance of any classification method relies on the quality of the measurement provided. One way to improve the classification is by extending the feature set and selecting the best features out of this set. In this paper a set of non-information-preserving features based on a multiresolution curve analysis which makes shape features explicit at multiple scales is proposed. An automatic procedure is designed to construct a binary tree which is used to classify the unknown objects.

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