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AUTOMATED FIBER EXTRACTION FROM SEM IMAGES WITH APPLICATION TO QUALITY CONTROL OF FIBER-REINFORCED COMPOSITES MANUFACTURING

机译:SEM图像中的自动纤维提取及其在纤维增强复合材料制造质量控制中的应用

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The morphology of fibers (e.g., spatial uniformity and orientation) plays a decisive role in determining the material properties or fabrication quality of fiber-reinforced nanocomposites. The existing literature lacks a reliable and automatic fiber extraction method for morphology analysis based on the scanning electron microscope (SEM) images. This paper proposes four different methods, namely, the simple Hough Transform, opening method, partitioning Hough Transform and gradient based Hough Transform, to automatically identify the fibers from SEM images to expedite the morphology analysis. The performance of these methods are thoroughly evaluated and compared through simulation studies and real case studies.
机译:纤维的形态(例如空间均匀性和取向)在确定纤维增强的纳米复合材料的材料性能或制造质量中起决定性作用。现有文献缺乏基于扫描电子显微镜(SEM)图像的用于形态分析的可靠且自动的纤维提取方法。本文提出了四种不同的方法,分别是简单的霍夫变换,打开方法,分区霍夫变换和基于梯度的霍夫变换,以从SEM图像中自动识别纤维,以加快形态分析。通过模拟研究和实际案例研究,对这些方法的性能进行了全面评估和比较。

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