Abstract

This paper introduces entropy as a feature for 1D signals. We propose as entropy measure the ratio between the signal’s perturbation (i.e. its part within minimum and maximum grey level) and the total energy of the signal. A linear transformation of 2D signals into 1D signals is also illustrated together with the results concerning natural scene, texture and medical images from a large mammograms database. The aim of this paper is to verify if the entropy variations for a closed system can be a discriminant feature to select homogenous regions.

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