Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.creatorVictor Hugo C. de Albuquerque
dc.creatorPaulo C. Cortez
dc.creatorAuzuir R. de Alexandria
dc.creatorJoão Manuel R. S. Tavares
dc.description.abstractThis article presents a new solution to segment and quantify the microstructures from images of nodular, grey, 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 realise a microstructure analysis from images faster and automatically.
dc.titleA New Solution for Automatic Microstructures Analysis from Images Based on a Backpropagation Artificial Neural Network
dc.typeArtigo em Revista Científica Internacional
dc.contributor.uportoFaculdade de Engenharia
Appears in Collections:FEUP - Artigo em Revista Científica Internacional

Files in This Item:
File Description SizeFormat 
  Restricted Access
895.25 kBAdobe PDF    Request a copy from the Author(s)

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.