Image Process of Rock Size Distribution Using DexiNed-Based Neural Network

نویسندگان

چکیده

In an aggregate crushing plant, the crusher performances will be affected by variation from incoming feed size distribution. Collecting accurate measurements of distribution on conveyors can help both operators and control systems to make right decisions in order reduce overall power consumption avoid undesirable operating conditions. this work, a particle estimation method based DexiNed edge detection network, followed application contour optimization, is proposed. The proposed framework was carried out four main steps. first step, after image preprocessing, utilize modified convolutional neural network predict map rock image. Next, morphological transformation watershed OpenCV library were applied. Then, last mass estimated pixel area. accuracy efficiency demonstrated comparing it with ground-truth segmentation. PSD validated laboratory screened samples.

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ژورنال

عنوان ژورنال: Minerals

سال: 2021

ISSN: ['2075-163X']

DOI: https://doi.org/10.3390/min11070736