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The use of a rapid and accurate method in diagnosis and classification ofspecies and/or cultivars of forage has practical relevance, scientific andtrade in various areas of study. Thus, leaf samples of fodder plant species\textit{Brachiaria} were previously identified, collected and scanned to betreated by means of artificial vision to make the database and be used insubsequent classifications. Forage crops used were: \textit{Brachiariadecumbens} cv. IPEAN; \textit{Brachiaria ruziziensis} Germain \& Evrard;\textit{Brachiaria Brizantha} (Hochst. ex. A. Rich.) Stapf; \textit{Brachiariaarrecta} (Hack.) Stent. and \textit{Brachiaria spp}. The images were analyzedby the fractal descriptors method, where a set of measures are obtained fromthe values of the fractal dimension at different scales. Therefore such valuesare used as inputs for a state-of-the-art classifier, the Support VectorMachine, which finally discriminates the images according to the respectivespecies.

Brachiaria species identification using imaging techniques based on fractal descriptors