Identification process of corn and barley kernels damages using neural image analysis

The subject of the study was to develop a neural model for the identification of mechanical damage in grain caryopses based on digital photographs. The authors has selected a set of universal features that distinguish between damaged and healthy caryopses. The study has produced an artificial neural network of a multilayer perceptron type whose identification capacity approximates that of a human.