Characterization of Flake Graphite Forms in Digital Microstructure Images of Gray Cast Iron using Digital Image Analysis Techniques
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Abstract
Microstructure analysis system has an important role to play in qualitative and quantitative analysis in the gray cast iron industry. It is used
to determine percent area of graphite inclusion in a given sample of gray cast iron. The ASTM A 247 standard has categorized graphite flake forms
into types A, B, C, D and E. A novel method for classification and quantification of the five types of graphite flakes (lamellar), namely, type A, B,
C, D and E in gray cast iron microstructure images, has been proposed. The four Haralic textural features, namely, contrast, correlation, energy and
homogeneity, are employed for characterization of different flake graphite in gray cast iron. An adaptive neuro-fuzzy inference system (ANFIS) is
developed for classification. The experimentation is done on actual gray cast iron microstructure images and the results are compared with the
manual estimation results. The comparison indicates good correlation between manual estimation and automated estimation. Microstructure images
of gray cast iron acquired from light microscope are used in the experimentation.
Keywords: ASTM A 247, gray cast iron, flake graphite, classification, Haralic texture features.
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