Abstract:Observing and analyzing surface images is critical for studying the interaction between plasma and irradiated plasma-facing materials (PFMs). This paper presents a method for the automatic recognition of bubbles in transmission electron microscope (TEM) images of W nano-fuzz using image processing techniques and convolutional neural network (CNN). We employ a three-stage approach consisting of Otsu, local-threshold, and watershed segmentation to extract bubbles from noisy images. To address over-segmentation,… Show more
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