A DATA-DRIVEN ROV FRAMEWORK FOR UNDERWATER CRACK DETECTION USING MATHEMATICAL IMAGE ENHANCEMENT TECHNIQUES

Miral Michel, Farida Sharkas, Zeyad Ayman Soliman, Youssef Negm, Osama Nasser, Talat El-balshy, Fares Saad, Ahmed S. Shehata

Abstract


Underwater inspection of concrete systems remains difficult due to turbidity, volatile illumination, and colour attenuation, which considerably reduce the visibility of defects along with cracks. Conventional diver-based techniques often fail to offer consistent assessments underneath those situations. This paper proposes a deployment-orientated ROV inspection framework integrating a lightweight mathematical photo enhancement pipeline to improve underwater crack visibility prior to analysis. The enhancement version combines shade-attenuation reimbursement and assessment stretching to mitigate wavelength loss and expand the dynamic range of submerged imagery. The ROV follows a predefined inspection trajectory with solid movement modelling, permitting systematic frame acquisition and repeatable evaluation. Validation in controlled pool surroundings demonstrates that the enhanced pix show off better clarity, sharper crack limitations, and stepped forward interpretability as compared to uncooked underwater frames, with noticeable noise reduction throughout one-of-a-kind water situations. The proposed integration affords a sensible and efficient method for assisting safer and greater resilient tracking of submerged concrete infrastructure, and it could serve as a basis for future real-global marine deployments. 

Keywords


Remotely Operated Vehicle (ROV), Underwater Inspection, Crack Detection, Image Enhancement, Marine Infrastructure.

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DOI: https://dx.doi.org/10.21622/MARLOG.2026.15.1.92

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Copyright (c) 2026 Miral Michel, Farida Sharkas, Zeyad Ayman Soliman, Youssef Negm, Osama Nasser, Talat El-balshy, Fares Saad, Ahmed S. Shehata

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The International Maritime Transport and Logistics Journal (MARLOG)

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