Underwater image segmentation based on computer vision and research on recognition algorithm

Abstract

Due to the continuous growth of the world’s population, the development and utilization of marine resources have received great attention. At present, marine fishing relies heavily on divers for underwater operations, which have the disadvantages of high risk, low efficiency, and high cost. Therefore, the development of underwater capture robot which can automatically detect, locate, and capture targets is of great significance for the development of marine economy. Underwater robot is an indispensable equipment for deep-sea operation and plays an irreplaceable role in the development of the ocean. When autonomous underwater vehicles perform underwater operations, they can use computer vision system to obtain clear underwater images and accurate target category information, which can help the manipulator select different grasping parts for different shapes and categories and improve work efficiency. The current underwater vision technology includes “acoustic vision” and “light vision.” Due to the influence of multichannel effect and blind area, the acoustic vision research in detecting and tracking underwater targets is not deep enough. Compared with the acoustic image processing system, the underwater optical vision system has the advantages of image and video capture and has higher real-time performance, which can aim at the target faster and more conveniently. Underwater vision optical system plays an important leading role in the detailed research of underwater vehicle sensing system, which can further improve the autonomous performance of underwater vehicle. In addition, considering the nature of underwater image imaging, we are developing an underwater image segmentation and recognition system based on image processing.