Automatic segmentation of the secondary austenite-phase island precipitates in a superduplex stainless steel weld metal

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2011

Autores

Victor H. C. Albuquerque (Autor) FEUP; Rodrigo Y. M. Nakamura (Autor) Outra; João P. Papa (Autor) Outra; Cleiton C. Silva (Autor) Outra; João Manuel R. S.Tavares (Autor) FEUP

Ata de Conferência Internacional

Título: Computational Vision and Medical Image Processing: VipIMAGE 2011

Páginas: 161-166

III ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing: VipIMAGE 2011

Olhão, Portugal, 14-14 October 2011

Indexação

ISI Web of Science

Scopus

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Outras ciências da engenharia e tecnologias

CORDIS: Ciências Tecnológicas

Outras Informações

Abstract (EN): 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6