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A novel approach toward microstructure evaluation of sintered ceramic materials through image processing techniques
Author(s) -
Chowdhury Sandipan,
Dhara Dipika,
Chowdhury Soumit,
Haldar Partha,
Chatterjee Kingshuk,
Bhattacharya Tapas Kumar
Publication year - 2021
Publication title -
international journal of applied ceramic technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.4
H-Index - 57
eISSN - 1744-7402
pISSN - 1546-542X
DOI - 10.1111/ijac.13716
Subject(s) - materials science , grain size , ceramic , grain boundary , microstructure , dilation (metric space) , particle size distribution , image processing , mineralogy , composite material , image (mathematics) , particle size , artificial intelligence , mathematics , geometry , computer science , chemical engineering , chemistry , engineering
In this paper, an image processing technique is introduced to measure the grain size and their distributions from the SEM image of copper oxide (CuO) and titanium dioxide (TiO 2 ) doped sintered alumina ceramics accurately. The noise present in SEM image is removed by applying low pass Gaussian filter followed by suppression of regional minima over a threshold. The clarity of individual grains and grain boundaries have been done by applying Watershed transform to this preprocessed SEM image. Morphological operations like dilation and erosion are used to make the grain‐boundary edges clear and continuous. The individual grain size in µm scale is measured from the pixel length of the rectangular bounding box drawn around the segmented grain. The normal Gaussian type distribution of grain size is observed in both CuO‐ and TiO 2 ‐doped grains in SEM image. The average grain size of CuO‐doped alumina grains (2.24 µm) is very close to G 50 value (2.17 µm), but G 50 value of TiO 2 ‐doped grains (8.59 µm) is slightly higher than its average grain size (7.96 µm). The proposed algorithm is compared with linear intercept method and the grain sizes obtained are very close to each other.