Paper
10 April 2018 Metal surface corrosion grade estimation from single image
Author Affiliations +
Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 106154Z (2018) https://doi.org/10.1117/12.2302776
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China
Abstract
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.
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Yijun Chen, Lin Qi, Huyuan Sun, Hao Fan, and Junyu Dong "Metal surface corrosion grade estimation from single image", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106154Z (10 April 2018); https://doi.org/10.1117/12.2302776
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KEYWORDS
Corrosion

Metals

Machine vision

Computer vision technology

Visual process modeling

RGB color model

Convolution

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