Fast automatic microstructural segmentation of ferrous alloy samples using optimum-path forest

Authors:
João Paulo Papa;Victor Hugo C. de Albuquerque;Alexandre Xavier Falcão;João Manuel R. S. Tavares
Affiliations:
Computer Science Department, São Paulo State University, Bauru, Brazil;Technological Research Center, University of Fortaleza, Fortaleza, Brazil;Institute of Computing, University of Campinas, Campinas, Brazil;Faculty of Engineering, University of Porto, Porto, Portugal
Venue:
CompIMAGE'10 Proceedings of the Second international conference on Computational Modeling of Objects Represented in Images
Year:
2010

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Abstract

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.