Automatic Evaluation of Nickel Alloy Secondary Phases from SEM Images

• Type: Article in International Scientific Journal
• Date: 2011

Authors

Victor Hugo C. de Albuquerque (Author) FEUP; Cleiton Carvalho Silva (Author) Other; Thiago Ivo de S. Menezes (Author) Other; Jesualdo Pereira Farias (Author) Other; João Manuel R. S. Tavares (Author) FEUP

Journal

Title: Microscopy Research and Technique

Vol. 74 No. 1

Pages: 36-46

ISSN: 1059-910X

Publisher: Wiley-Blackwell

Indexing

ISI Web of Knowledge - 19 Citations

ISI Web of Science

Scopus - 31 Citations

Scientific classification

FOS: Engineering and technology > Mechanical engineering

CORDIS: Physical sciences > Computer science > Systems design > Neural networks

Other information

Authenticus ID: P-002-Z5F

DOI: 10.1002/jemt.20870

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11