3D surface reconstruction from multiple SEM images has been widely addressed in the scientific literature. Different approaches exist, most of them use variants of Digital Image Correlation (DIC) .
DIC methods perform well on textured areas of images but provide limited results on uniform or flat zones. Approaches using segmentation techniques, that match discernible regions of images, provide a solution to solve this problem on low-textured regions . However, these methods are more computationally expensive and are less accurate than DIC on textured areas. Our objective is therefore to combine these two methods. One preliminary step is to differentiate textured areas, where DIC can be used, from low-textured areas, where segmentation techniques are needed. This step will be addressed in this paper, and we propose a new approach using morphological operators to do that.
Our approach uses the watershed operator with morphological gradient and markers obtained with h-minima . On each region, average gradient value is computed. Automatic thresholding and post processing using opening by criteria  is then performed to differentiate textured areas from low-textured ones.
Comparison of our approach with more standard methods of texture detection such as local entropy of local variance calculations  will be presented.
A major benefit of our approach is that transition between textured areas and low-textured ones strongly follow real contours of flat zones, limiting interpolation problems between DIC and methods using segmentation techniques.
We will illustrate our texture detection algorithm by applying it on 3D surface reconstruction with SEM images of crystals of zeolites and catalyst with alumina supports.
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is that transition between textured areas and low-textured ones strongly follow
To cite this abstract:Sébastien Drouyer, Serge Beucher, Michel Bilodeau, Maxime Moreaud, Loïc Sorbier; A morphological approach for texture detection, application to SEM stereo reconstruction. The 16th European Microscopy Congress, Lyon, France. https://emc-proceedings.com/abstract/a-morphological-approach-for-texture-detection-application-to-sem-stereo-reconstruction/. Accessed: February 28, 2020
EMC Abstracts - https://emc-proceedings.com/abstract/a-morphological-approach-for-texture-detection-application-to-sem-stereo-reconstruction/