On Image Analysis by the Methods of Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fundamentals of digital image processing
Fundamentals of digital image processing
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vector quantization and signal compression
Vector quantization and signal compression
Ten lectures on wavelets
Recognizing Planar Objects Using Invariant Image Features
Recognizing Planar Objects Using Invariant Image Features
A Survey of Gesture RecognitionTechniques.
A Survey of Gesture RecognitionTechniques.
Fourier Preprocessing for Hand Print Character Recognition
IEEE Transactions on Computers
Online PCA with adaptive subspace method for real-time hand gesture learning and recognition
WSEAS Transactions on Computers
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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.