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The SARS-CoV-2 is quickly spreading worldwide resulting in millions of infection and death cases. As a consequence, it is increasingly important to diagnose the presence of COVID-19 infection regardless of the technique applied. To this end, this work deals with the problem of COVID-19 classication in order to dierentiate COVID-19 versus healthy Computed Tomography (CT) images. In particular, rst-order statistical measures as well as numerical quantities extracted from the autocorrelation function are investigated with the aim to provide an ecient classication process ensuring satisfactory performance results.