Home // International Journal On Advances in Intelligent Systems, volume 13, numbers 1 and 2, 2020 // View article

A Feature Selection and Extraction Method from Time-Frequency Images

Authors:
Dorel Aiordachioaie
Theodor Dan Popescu
Bogdan Dumitrascu

Keywords: signal; image; time-frequency transform; signal processing; feature selection; classification

Abstract:
Time-frequency image processing is considered in the context of change detection and diagnosis purposes based on signal processing paradigm. A method for selection and extraction of features from time-frequency is considered and evaluated. New images are obtained by applying a criterion based on the contours generated by the main components of the analyzed time-frequency image. The transformed images are less complex and could be white and black only. Features based on statistical moments are considered, selected and used to define discriminant functions, in order to improve the results of the classification. The features include the number of the contours, the average area defined by the contours, the variance of the areas and the Renyi entropies. As case study, signals coming from vibration generated by faults in bearings are considered. The main output of the paper is the method of the feature selection and extraction from time-frequency images.

Pages: 119 to 128

Copyright: Copyright (c) to authors, 2020. Used with permission.

Publication date: June 30, 2020

Published in: journal

ISSN: 1942-2679