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Metal Surface Corrosion Grade Estimation from Single Image

机译:从单张图像估计金属表面腐蚀等级

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Metal corrosion can cause many problems, how to quickly and effectively assess the grade of metal corrosion and timely remediation is a very important issue. Typically, this is done by trained surveyors at great cost. Assisting them in the inspection process by computer vision and artificial intelligence would decrease the inspection cost. In this paper, we propose a dataset of metal surface correction used for computer vision detection and present a comparison between standard computer vision techniques by using OpenCV and deep learning method for automatic metal surface corrosion grade estimation from single image on this dataset. The test has been performed by classifying images and calculating the accuracy for the two different approaches.
机译:金属腐蚀会引起很多问题,如何快速有效地评估金属腐蚀的等级并及时进行补救是一个非常重要的问题。通常,这是由训练有素的验船师以高昂的代价完成的。通过计算机视觉和人工智能帮助他们进行检查过程将降低检查成本。在本文中,我们提出了用于计算机视觉检测的金属表面校正数据集,并提出了使用OpenCV与深度学习方法对标准计算机视觉技术进行比较的方法,该方法可从该数据集上的单个图像自动估计金属表面腐蚀等级。通过对图像进行分类并计算两种不同方法的准确性来执行该测试。

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