Location of coffee beans using Hopfield-type neural network

In this paper, recurrent (Hopfield-type) neural network associative memories are synthesized, using the perceptron algorithm, in order to locate coffee beans on a tree branch, which is a very important task for harvest automation. The respective training is done on the basis of a set of pictures. The procedure is as follows: first the picture is enhanced in order to adequate the image for the learning process; then, the image is divided in sub-images, from where relevant information is selected as memory patterns. After the training is carried out, an evaluation is performed.