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1 November 1990 Application of mathematical morphology to the study of microstructural characteristics of metal matrix composites
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In the process of manufacturing silicon carbide reinforced aluminum metal matrix composites silicon carbide particles are mixed with aluminum powder and subjected to an extrusion process. The orientation of the silicon carbide particles in the resulting composite should be random for the stiffness of the material to be the same in the three orthogonal directions. Secondary electron images show that the orientation of the particles follow some pattern rather than being random. To determine stiffness it becomes necessary to study nondestructively the rnicrostructure characteristics such as the distribution of size orientation length and aspect ratio of the silicon carbide particles. In silicon carbide particles it was found that many of the silicon carbide particles appear connected. A new procedure has been developed that aims at separating these connected particles thereby making it possible to characterize the rnicrostructure. This procedure is an extension of the cluster fast segmentation algorithm (CFS) a morphological algorithm that can break the connectivity among particles that overlap. Seeds are generated for every individual particle it can identify. CFS fails when there is no constriction at the region of connection of the particles. Certain properties of the skeleton can then be used to generate markers for as many particles as possible. After partitioning is completed the markers are grown back using morphological rules.
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Mathew S. Chackalackal and John P. Basart "Application of mathematical morphology to the study of microstructural characteristics of metal matrix composites", Proc. SPIE 1350, Image Algebra and Morphological Image Processing, (1 November 1990);

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