A method for undersea gas bubbles detection from acoustic image

In recent years, there has been an increasing requirement for methods of detecting bubbles released from the seabed into the water column, such as leaks from undersea gas pipelines and seeps from carbon capture and storage facilities. Considering the peculiarity of the layout of submarine gas pipelines and that of the ocean environment around them, we construct an underwater mobile platform equipped with autonomous underwater vehicles carrying multi-beam echo sounder (MBES) and various types of other sensors. Analogous to optical flow, this paper describes a scale-invariant feature transform (SIFT) flow algorithm, which includes both the detection of key points and the computation of local descriptors. This SIFT flow algorithm estimates the motion characteristics of gas leaks and the results show a positive correlation relationship between the rising velocity of leakage gas and the leakage pressure as well as the leakage aperture. Finally, the validity of this method is verified in tank and sea experimental research.