Underwater object detection and localization based on multi-beam sonar image processing

Automatic detection and localization of underwater objects in sonar images is of great importance in applications of Autonomous Underwater Vehicle navigation. This paper presents a new framework capable of analyzing multi-beam sonar images for underwater object detection and localization. Real-time sonar data flow is collected by a multi-beam sonar, and denoising techniques are mandatory before applying subsequent procedures. An improved adaptive thresholding method is proposed to separate the objects from background. A contour detection algorithm is used to find objects´ contour for calculating the position of the objects. Experiments show that the proposed framework can detect objects and figure out their position accurately.