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. 2018 Feb 1;8:2078. doi: 10.1038/s41598-018-20438-6

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© The Author(s) 2018

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Examples of machine learning with Random Forest algorithm for automated pattern recognition in optical microscopy images of metallurgical samples. (a) The automated segmentation on single image is on the left. The small part of it and manual segmentation on this part are depicted in the right for comparison. (b) The application of the Random Forest Classifier on image stack or stitched image for accurate estimation of microstructure area/volume percentage from large imaging area.