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Automated Grain Counting for the Microstructure of Mg Alloys Using an Image Processing Method

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Abstract

In this study, a practical and swift approach for calculating the number of grains in a microstructure and determining the ASTM grain size of Mg alloys was demonstrated using computer vision technology. In the experiments, Mg alloys were used as work materials. Microscopic images were taken by scanning electron microscopy (SEM) and were subjected to the image processing method. The grains in the microstructure were counted by the image processing method and manually. The experimental results were examined by comparing the manual and automated grain counting results. The standard deviation of the grain numbers was found to be 6% between the manual and automated counting methods. The success rate in the comparison of the grain numbers is approximately 94%. Moreover, ASTM grain sizes were calculated according to the number of grains determined in the SEM images, and a high success rate was achieved by equalizing the ASTM grain sizes of each alloy according to both methods.

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Acknowledgments

The authors would like to thank Bingol University, the Central Research Laboratory of Bingol University, and its workers for their support in the SEM analysis.

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  1. Department of Mechanical Engineering, Faculty of Engineering, Aydın Adnan Menderes University, Aydın, Turkey

    Fatih Akkoyun

  2. Department of Mechanical Engineering, Faculty of Engineering and Architecture, Bingol University, Bingol, Turkey

    Ali Ercetin

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Akkoyun, F., Ercetin, A. Automated Grain Counting for the Microstructure of Mg Alloys Using an Image Processing Method. J. of Materi Eng and Perform 31, 2870–2877 (2022). https://doi.org/10.1007/s11665-021-06436-2

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