Fast Automatic Microstructural Segmentation of Ferrous Alloy Samples Using Optimum-Path Forest

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2010

Autores

Papa, JP (Autor) Outra; de Albuquerque, VHC (Autor) Outra; Falcao, AX (Autor) Outra; João Manuel R. S. Tavares (Autor) FEUP

Ata de Conferência Internacional

Título: Computational Modeling of Objects Represented in Images

Páginas: 210-220

International Symposium "Computational Modeling of Objects Represented in Images. Fundamentals, Methods and Applications'' - CompIMAGE 2010 Buffalo, NY, USA May 5-7, 2010

Buffalo, NY, USA, May 5-7, 2010

Indexação

ISI Web of Knowledge - 5 Citações

Scopus - 10 Citações

Outras Informações

ID Authenticus: P-007-T71

DOI: 10.1007/978-3-642-12712-0_19

Abstract (EN): In this work we propose a novel automatic cast iron segmentation approach based on the Optimum-Path Forest classifier (OPF). Microscopic images from nodular, gray and malleable cast irons are segmented using OPF, and Support Vector Machines (SVM) with Radial Basis Function and SVM without kernel mapping. Results show accurate and fast segmented images, in which OPF outperformed SVMs. Our work is the first into applying OPF for automatic cast iron segmentation.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11