2020 Volume 60 Issue 5 Pages 954-959
We studied on automation of segmentation using deep learning, which has been remarkably developed in recent years.
For the microstructural image of ferrite-martensite dual phase steel, we tried to segment the ferrite phase, martensite phase, and ferrite grain boundary in different colors individually. We created two models, SegNet and U-Net that can perform segmentation with high accuracy and compared the accuracy with an existing method.
As a result, we demonstrated that models using deep leaning is more accurate than the existing method. In particular, U-Net model shows highly accuracy of segmentation for material microstructures.