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Title: Corrosion Damage Identification and Lifetime Estimation of Ship Parts using Image Processing
Authors: Naladala, I.
Raju, A.
Aishwarya, C.
Koolagudi, S.G.
Issue Date: 2018
Citation: 2018 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2018, 2018, Vol., , pp.678-683
Abstract: Corrosion is a process that leads to early failure of ship parts, high maintenance costs and a shortened service life of the ship, as a whole. Human visual inspection is currently the most widely used method to assess corrosion. In this paper, we propose the use of image processing to determine the extent of corrosion and estimate the time period within which the ship parts have to be replaced. In the case of availability of pre-corrosion images, the histograms of the pre-corrosion and post-corrosion images are compared and their similarity is quantified as the Sum of Squared Distances (SSD) value. Our method then produces a numerical output which signifies the level of corrosion. We then correlate extent of damage and ship part replacement period. In the absence of pre-corrosion images, we classify superpixels in the post-corrosion image as undamaged or damaged with an accuracy of 92 per cent, using Random Forest classifier. We have also evaluated the performance of corrosion prevention measures such as galvanization, painting, etc on different parts of the ship, for example, parts exposed to only air and parts exposed to both saline water and air. � 2018 IEEE.
Appears in Collections:2. Conference Papers

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