Please use this identifier to cite or link to this item: http://idr.nitk.ac.in/jspui/handle/123456789/7565
Full metadata record
DC FieldValueLanguage
dc.contributor.authorNaladala, I.
dc.contributor.authorRaju, A.
dc.contributor.authorAishwarya, C.
dc.contributor.authorKoolagudi, S.G.
dc.date.accessioned2020-03-30T10:02:30Z-
dc.date.available2020-03-30T10:02:30Z-
dc.date.issued2018
dc.identifier.citation2018 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2018, 2018, Vol., , pp.678-683en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/7565-
dc.description.abstractCorrosion 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.en_US
dc.titleCorrosion Damage Identification and Lifetime Estimation of Ship Parts using Image Processingen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.