A Pipeline Extraction Algorithm for Forward-Looking Sonar Images Using the Self-Organizing Map

Review on condition monitoring techniques for water pipelines

“…The performance of SSS technique in terms of image resolution can be improved with the efficient probabilistic and geometric approaches [20,22]. Forward looking sonar is designed and configured to visualise the frontal view, and it is also capable of locating and extracting the path of pipeline through small particles and turbulence [23].…”

“…Sonar profiling techniques provide an appropriate method for the monitoring of pipelines in subsea environmental conditions. However, the reliability and robustness can be improved by incorporating more enhanced imaging algorithms and integrating the sensors such as doppler velocity log, an inertial measurement unit and field gradient sensor [23].…”

Evaluating the Adaptability of Deep Learning-Based Multi-feature Sonar Image Detection Algorithms

“…Robust target detection in sonar images is an essential task for underwater exploration, navigation, and mapping and is valuable in exploring information about the underwater environment [1,2]. In sonar images, sonar can easily be imaged through turbulence and small particles, but the target in the sonar image is mixed with the background, has high noise, and is susceptible to environmental interference [3]. Therefore, it is necessary to extract target information through feature detection and classify and recognize the target.…”