Journal
MICROSCOPY RESEARCH AND TECHNIQUE
Volume 74, Issue 1, Pages 36-46Publisher
WILEY
DOI: 10.1002/jemt.20870
Keywords
materials sciences; metallography; microstructural analysis; nickel alloy; secondary phase; precipitation; phase quantification; dissimilar metal weld; image segmentation; artificial neuronal network
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Funding
- National Council for Scientific and Technological Development (CNPq, Brazil)
- Research and Projects Financing (FINEP, Brazil)
- Coordination for the Improvement of People with Higher Education (CAPES, Brazil)
- Mechanical Testing Laboratory of the Federal Center for Technological Education in Ceara (Brazil)
- Welding Engineering Laboratory of the Federal University of Ceara (Brazil)
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Quantitative metallography is a technique to determine and correlate the microstructures of materials with their properties and behavior. Generic commercial image processing and analysis software packages have been used to quantify material phases from metallographic images. However, these all-purpose solutions also have some drawbacks, particularly when applied to segmentation of material phases. To overcome such limitations, this work presents a new solution to automatically segment and quantify material phases from SEM metallographic images. The solution is based on a neuronal network and in this work was used to identify the secondary phase precipitated in the gamma matrix of a Nickel base alloy. The results obtained by the new solution were validated by visual inspection and compared with the ones obtained by a commonly used commercial software. The conclusion is that the new solution is precise, reliable and more accurate and faster than the commercial software. Microsc. Res. Tech. 74:36-46, 2011. (C) 2010 Wiley-Liss, Inc.
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