The paper introduces entropy as a measure for 1D signals. We propose an entropy measure of the relationship between the crest of the signal (i.e. its portion contained between the absolute minimum and maximum) and the energy of the signal. A linear transformation of 2D signals into 1D signals is also illustrated. The experimental results are compared to several fuzzy entropy measures and other well-known methods in literature. Experiments have been carried out on medical images from a large mammograms database; this choice is due to the high-degree of complexity of this kind of images and the strong interest in the scientific community on medical images. The capability of the methods was tested in order to discriminate between benignant and malignant microcalcifications.

Entropy Measure in Image Classification

CASANOVA, ANDREA;
2010

Abstract

The paper introduces entropy as a measure for 1D signals. We propose an entropy measure of the relationship between the crest of the signal (i.e. its portion contained between the absolute minimum and maximum) and the energy of the signal. A linear transformation of 2D signals into 1D signals is also illustrated. The experimental results are compared to several fuzzy entropy measures and other well-known methods in literature. Experiments have been carried out on medical images from a large mammograms database; this choice is due to the high-degree of complexity of this kind of images and the strong interest in the scientific community on medical images. The capability of the methods was tested in order to discriminate between benignant and malignant microcalcifications.
Entropy; image classification
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/24284
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