Underwater Corrosive Material Identification and Image Enhancement

One of the most essential problems underwater during the transmission of gas or crude oil through carbon steel pipelines is corroded, it is the critical issue—the subject of numerous research employing a variety of methodologies. The main goal of this research is to create a reliable and competent model that can precisely detect corrosion using certain algorithms specifically underwater image enhancement for corrosion pipeline inspection to improve the input photos, a dependable algorithm is used. The findings of this detection model show that the underwater image enhancement for corrosion pipeline inspection could be easily identified using a resized image and edge detection.

Authors

Publication Details

Published
2025-03-04
DOI
https://doi.org/10.1109/icvadv63329.2025.10961150
Citations
1
Primary Topic
Non-Destructive Testing Techniques
Type
article
Field-Weighted Citation Impact
0.71
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Underwater Corrosive Material Identification and Image Enhancement

VARMA SRIJA, Reeta Devi, N V Keerthana, B Roopini et al.
1 citations
Non-Destructive Testing Techniques
0.71
article

Underwater Corrosive Material Identification and Image Enhancement

VARMA SRIJA, Reeta Devi, N V Keerthana, B Roopini, J M Sharumathi
article en
1 citations

Abstract

One of the most essential problems underwater during the transmission of gas or crude oil through carbon steel pipelines is corroded, it is the critical issue—the subject of numerous research employing a variety of methodologies. The main goal of this research is to create a reliable and competent model that can precisely detect corrosion using certain algorithms specifically underwater image enhancement for corrosion pipeline inspection to improve the input photos, a dependable algorithm is used. The findings of this detection model show that the underwater image enhancement for corrosion pipeline inspection could be easily identified using a resized image and edge detection.

Openalex Percentile: Top 34%
Non-Destructive Testing Techniques
0.71
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