Brachiaria species identification using imaging techniques based on fractal descriptors

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