# Computer Vision and Image Processing Approaches for Corrosion Detection
## 5 Challenges in Corrosion Detection  
The implementation of machine vision and image processing approaches for corrosion detection, assessment, and prediction is fraught with challenges. In terms of sewage pipes, it is critical to address the challenges of assessing and maintaining corrosion in situ. The sewage pipes contain many bacteria and other microorganisms that settle inside the pipes which can pose health threats to the corrosion inspectors because of practical reasons. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Detection Approach** & & **Description** & **Limitation** \\ \hline \multirow{6}{*}{[PERSON] and [PERSON] [91]} & \(\bullet\) & Explore the current corrosion maintenance & \\  & & employed in maritime sector. & \\  & & Monitor very low sulphur fuel oil (VLSFO) & \\  & & characteristics to lower critical risk. & \\  & & Provide detection and corrective action for & \\  & & corrosion caused by sulphur emissions. & \\ \hline \multirow{6}{*}{[PERSON] et al. [92]} & \(\bullet\) & Detect corrosion of steel in a marine environment. & \\  & & Sensor detects corrosion region by & \\  & & calculating the difference between concrete & \\  & & moisture degree and steel layer. & \\  & & Superwise and manage the steel’s mass loss & \\  & & by detecting corrosion status. & \\ \hline \multirow{6}{*}{[PERSON] et al. [93]} & \(\bullet\) & Pitt depth prediction that requires & \\  & & immediate maintenance. & \\  & & Degradation process from real-time data is & \\  & & used, considering peaks over threshold. & \\  & & Assess and detect corrosion failures with & \\  & & high performance. & \\ \hline \multirow{6}{*}{[PERSON] et al. [94]} & \(\bullet\) & Predict corrosion damages on ship & \\  & & structures. & \\  & & Determine RUL and corrosion damage & \\  & & over time. & \\ \hline \multirow{6}{*}{[PERSON] et al. [95]} & \(\bullet\) & Detect particular fault indicators, like air & \\  & & temperature and pressure, that could prove & \\  & & beneficial in the formulation of a & \\  & & corrosion model. & \\  & & & \\ \hline \multirow{6}{*}{[PERSON] et al. [96]} & \(\bullet\) & Machine learning and time-series & \\  & & anomaly detection. & \\  & & Detect and predict corrosion on specific & \\  & & parts of a ship engine. & \\  & & & \\ \hline \multirow{6}{*}{[PERSON] et al. [97]} & \(\bullet\) & Historical and real-time data for & \\  & & employment of generalized extreme & \\  & & value distribution. & \\  & & Adapt to defect depth distribution and & \\  & & high reliability. & \\ \hline \multirow{6}{*}{[PERSON] [98]} & \(\bullet\) & Specific location can be determined. & \\  & & & \\  & & & to corrosion. \\ \hline \multirow{6}{*}{[PERSON] et al. [99]} & \(\bullet\) & Initiate solution for hull corrosion. & \\  & & Breakdowns and failures can be reduced & \\  & & with predictive maintenance. & \\ \hline \end{tabular}
\end{table} 
Table 2: _Cont._Machine vision and image processing approaches could be considered for corrosion inspection in sewage pipes because of their NDT and remote inspection. The roles of corrosion inspectors can be further reduced, with minimal exposure and physical contact with the health hazards. The other concern for computer vision and image processing approaches for corrosion detection is the availability or readiness of the imaging equipment technology. The information of the structure's condition cannot be provided using a camera or video camera. This equipment and its technology are not able to penetrate the material itself, thus the degree of corrosion cannot be identified. The information and condition of the outer material can be analyzed, although the inner side would be totally ignored. Only a general understanding of the corroded area can be provided instead of individual flaws. This approach also has an invasive installation process, as the equipment is not water-resistant and is not durable enough to be operated during the underwater and inner pipe corrosion inspections. Dewatering is required, thus, the operation can be interrupted.