Abstract
Abstract This work intends to apprehend and emphasize the contribution of image-processing techniques and computer vision in the treatment of clay-based material known in Meknes region. One of the various characteristics used to describe clay in a qualitative manner is porosity, as it is considered one of the properties that with “kill or cure” effectiveness. For this purpose, we use scanning electron microscopy images, as they are considered the most powerful tool for characterising the quality of the microscopic pore structure of porous materials. We present various existing methods of segmentation, as we are interested only in pore regions. The results show good matching between physical estimation and Voronoi diagram-based porosity estimation.
Highlights
The structural ceramic tiles and clay materials industry is an important regional industrial segment consuming an important quantity of raw materials, especially clay
Pore diameter is considered one of the challenging tasks in material characterization. She et al [30] introduced a new parameter called effective pore diameter calculated from a scanning electron microscopy (SEM) image, the algorithm of which is based on Euclidean distance transform
We have presented different imaging methods for porosity estimation in clay-based bricks along with physical analysis
Summary
The structural ceramic tiles and clay materials industry is an important regional industrial segment consuming an important quantity of raw materials, especially clay. Porosity can be estimated by computing volumetric measurements of core samples, or from geophysical logs, which calculate a property of a rock and infer its porosity, or from petrographic image analysis, which evaluates the pore size of a small sample. Pore diameter is considered one of the challenging tasks in material characterization She et al [30] introduced a new parameter called effective pore diameter calculated from a scanning electron microscopy (SEM) image, the algorithm of which is based on Euclidean distance transform. We describe a non-destructive process using computer vision for porosity estimation This technique is basically used for characterizing materials such as ceramic. The scanning electron microscope used was FEI QUANTA 200 (FEI, Hillsboro, OR, USA)
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