Original paper
Image Processing and Machine Learning Approaches for Petrographic Thin Section Analysis
Published: Oct 16, 2017
Abstract
The article presents the methodology of petrographic thin section analysis, combining the algorithms of image processing and statistical learning. The methodology includes the structural description of thin sections and rock classification based on images obtained from polarized optical microscope. To evaluate the properties of structural objects in thin section (grain, cement, voids, cleavage), first they are segmented by watershed method with...
Paper Details
Title
Image Processing and Machine Learning Approaches for Petrographic Thin Section Analysis
Published Date
Oct 16, 2017
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