AUTOMATIC MICROSTRUCTURE GRAIN COUNT USING SUPPORT VECTOR REGRESSION
Keywords:
Support Vector Regression, Microstructure, Grain count, Automatic thresholdingAbstract
Grain count determination is an important task in microstructural analysis, requires long time while performing manually. Nowadays, automatic techniques for the grain size determination are implemented. Although the automatic techniques are documented on the ASTM standards, the major drawback is the non availability of quality digital microstructural images. The quality of microstructure depends on various factors viz., illumination, noise, low contrast, poor boundary definition etc. The present work is focused on a novel methodology that enables a clear definition of the grain and its boundary for an accurate automatic grain count and size through pattern classification technique, employing support vector regression (SVR) method.
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