Hui Li1, Chengwei Pan2, 3, Ziyi Chen1, Aziguli Wulamu2, 3, *, Alan Yang4
CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 563-578, 2020, DOI:10.32604/cmc.2020.09806
Abstract Ore image segmentation is a key step in an ore grain size analysis based on
image processing. The traditional segmentation methods do not deal with ore textures and
shadows in ore images well Those methods often suffer from under-segmentation and
over-segmentation. In this article, in order to solve the problem, an ore image
segmentation method based on U-Net is proposed. We adjust the structure of U-Net to
speed up the processing, and we modify the loss function to enhance the generalization of
the model. After the collection of the ore image, we design the annotation standard and
train the network… More >
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