Article ID Journal Published Year Pages File Type
6923405 Computers & Geosciences 2012 10 Pages PDF
Abstract
► Thin section images are studied to identify 5 types of pore spaces automatically. ► A pattern recognition algorithm is followed to identify pore spaces. ► Image analysis and discriminant classifier are integrated to develop the model. ► The proposed model is a promising approach to study pore types in an accurate way.
Keywords
Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
Authors
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