Please use this identifier to cite or link to this item: http://hdl.handle.net/10216/56793
Author(s): Victor H. C. Albuquerque
Rodrigo Y. M. Nakamura
João P. Papa
Cleiton C. Silva
João Manuel R. S.Tavares
Title: Automatic segmentation of the secondary austenite-phase island precipitates in a superduplex stainless steel weld metal
Issue Date: 2011
Abstract: Duplex and superduplex stainless steels are class of materials of a high importance for engineering purposes, since they have good mechanical properties combination and also are very resistant to corrosion. It is known as well that the chemical composition of such steels is very important to maintain some desired properties.In the past years, some works have reported that gama 2 precipitation improves the toughness of such steels, and its quantification may reveals some important information about steel quality. Thus, we propose in this work the automatic segmentation of gama 2 precipitation using two pattern recognition techniques: Optimum-Path Forest (OPF) and a Bayesian classifier. To the best of our knowledge, this if the first time that machine learning techniques are applied into this area. The experimental results showed that both techniques achieved similar and good recognition rates.
Subject: Ciências Tecnológicas, Outras ciências da engenharia e tecnologias
URI: http://hdl.handle.net/10216/56793
Source: Computational Vision and Medical Image Processing: VipIMAGE 2011
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
License: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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