Automatic image segmentation for material microstructure characterization by optical microscopy

Naim Ramou, Nabil Chetih, Yamina Boutiche, Rabah Abdelkader


This work shows the utility to have a microstructure characterization to analysis the properties of materials.  For this, digital image segmentation is used on microscopic images of materials to extract the number of phases and their proportion present in the material to obtain a quantitative description of material properties and to better control product quality. In this way, we present here an automated method for segmenting the phases present in microscopic scanning images of metallographic samples using a multiphase level set with Mumford Shah formulation. Experience shows that the proposed model successfully detects phase regions for a variety of real micrographic images and provides the required accuracy and robustness to the process..

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