In this paper we describe a machine vision approach to recognize the denomination classes of the Mexican paper currency by extracting their color features. A banknote's color is characterized by summing all the color vectors of the image's pixels to obtain a resultant vector, the banknote's denomination is classified by knowing the orientation of the resulting vector within the RGB space. In order to obtain a more precise characterization of paper currency, the less discriminative colors of each denomination are eliminated from the images; the color selection is applied in the RGB and HSV spaces, separately. Experimental results with the current Mexican banknotes are presented.
['Farid García-Lamont', 'Jair Cervantes', 'Asdrúbal López', 'Lisbeth Ursula Oscuvilca Rodríguez']
Classification of Mexican Paper Currency Denomination by Extracting Their Discriminative Colors