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Meeting 2016 TMS Annual Meeting & Exhibition
Symposium ICME Infrastructure Development for Accelerated Materials Design: Data Repositories, Informatics, and Computational Tools
Presentation Title Evaluating Image Texture Recognition Algorithms for Generic Microstructure Characterization
Author(s) Brian L. DeCost, Long Qing Chen, Elizabeth A. Holm
On-Site Speaker (Planned) Brian L. DeCost
Abstract Scope Modern microstructure analytics methods are often limited to specific, well-defined classes of materials. We apply established texture recognition concepts from the field of computer vision to develop new quantitative microstructure descriptors that generalize across a wide variety of materials system, length scales, and imaging modes. These microstructure descriptors can be used to define objective classes of microstructures, and to quantitatively compare experimental and simulated microstructures from entirely disparate material systems. We introduce a synthetic microstructure dataset spanning a variety of materials systems and microstructure classes for evaluating the performance of prospective microstructure descriptors. We report the performance of several image texture representations in classification experiments on this dataset. Approaching microstructure image data with texture recognition methods opens the door to novel large-scale data mining approaches for automatically find relationships in large and diverse microstructural image data sets, such as the archives of a materials science journal.
Proceedings Inclusion? Planned: A print-only volume


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