Recognition of image patterns of oils, by characterization of color spaces with neuronal and bayesian classification

In this article, we present a methodology that allows from color change, as a basis for characterization and neural networks and Bayesian algorithms as classifiers, different types of commercial oil to determine the level of wear. For the implementation of the state of the oil in-situ, an analysis was made for samples of seven types of oils, each of which was taken thirty images.