SLPDR: A Benchmark For Ship License Plate Detection And Recognition
Abstract
Ship identification is a prerequisite for the intelligent management of maritime transportation, yet existing research is limited to the overall detection and categorization of ships, and there is a lack of data and related research on ship identification. Inspired by the research on vehicle license plates, we make the first attempt to propose the concept of ship license plate and construct the first ship license plate detection and recognition (SLPDR) dataset, which contains 88, 862 images and 1,420 instances. In addition, this paper presents a state space attention based YOLO model, which effectively integrate global information and local details for fast and accurate ship license plate detection. Furthermore, we explore the application of ship license plate in intelligent maritime transportation, including ship identification, connecting images and ships and ship compliance assessment, which provides new ideas for intelligent management of maritime vessels.
