Pattern Recognition and feature extraction: a comparative study
نویسنده
چکیده
The selection of features for classifying a pattern by means a fuzzy reasoning, is fundamental in order to obtain a reliable and significative response. The scope of this work is to compare three methods specialized for the extraction of features from images and, consequently, to study the ability of classification performed by applying a fuzzy inference system. The methods to be compared were: Fourier descriptors, Zernike moments and Wavelet coefficients. The best result, in terms of the best performances obtained both as classification reliability and computational time, was represented by the application of wavelet transform. Key-words: Fuzzy logic, Image analysis, Pattern recognition, Feature selection, Fourier descriptors, Zernike moments, Wavelet coefficients.
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