A New Solution for Automatic Microstructures Analysis from Images Based on a Backpropagation Artificial Neural Network

This paper presents a new solution to segment and quantify the microstructures from images of nodular, gray and malleable cast irons, based on an Artificial Neural Network. The neural network topology used is the multilayer perception, and the algorithm chosen for its training was the backpropagation. This solution was applied to 60 samples of cast iron images and results were very similar to the ones obtained by visual human tests. This was better than the information obtained from a commercial system that is very popular in this area. In fact, this solution segmented the images of microstructures materials more efficiently. Thus, we can conclude that it is a valid and adequate option for researchers, engineers, specialists and professionals from materials science field to realize a microstructure analysis from images faster and automatically.