EBSD image segmentation using a physics-based forward model
| Autor: | Marc De Graef, Dennis Wei, Alfred O. Hero, Se Un Park, Jeff Simmons, Megna Shah |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Diffraction
Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Image segmentation Physics based Euler angles symbols.namesake Robustness (computer science) Computer Science::Computer Vision and Pattern Recognition symbols Segmentation Computer vision Artificial intelligence business ComputingMethodologies_COMPUTERGRAPHICS Electron backscatter diffraction |
| Zdroj: | ICIP |
| DOI: | 10.1109/icip.2013.6738779 |
| Popis: | We propose a segmentation and anomaly detection method for electron backscatter diffraction (EBSD) images. In contrast to conventional methods that require Euler angles to be extracted from diffraction patterns, the proposed method operates on the patterns directly. We use a forward model implemented as a dictionary of diffraction patterns generated by a detailed physics-based simulation of EBSD. The combination of full diffraction patterns and a dictionary allows anomalies to be detected at the same time as grains are segmented, and also increases robustness to noise and instrument blur. The proposed method is demonstrated on a sample of the Ni-base alloy IN100. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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