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Automatic image segmentation for material microstructure characterization by optical microscopy
Informatica ( IF 3.3 ) Pub Date : 2020-09-15 , DOI: 10.31449/inf.v44i3.3034
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..

中文翻译:

通过光学显微镜进行材料微观结构表征的自动图像分割

这项工作显示了进行微观结构表征以分析材料特性的实用性。为此,在材料的显微图像上使用数字图像分割来提取材料中存在的相数及其比例,以获得材料特性的定量描述并更好地控制产品质量。通过这种方式,我们在此提出了一种使用具有 Mumford Shah 公式的多相水平集来分割金相样品显微扫描图像中存在的相的自动化方法。经验表明,所提出的模型成功地检测了各种真实显微图像的相位区域,并为该过程提供了所需的准确性和鲁棒性。
更新日期:2020-09-15
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