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

• Type: Article in International Conference Proceedings Book
• Date: 2010

Authors

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

Conference proceedings International

Title: Computational Modeling of Objects Represented in Images

Pages: 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

Indexing

ISI Web of Knowledge - 5 Citations

Scopus - 10 Citations

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11