Resumen
The new way of offshore operation and maintenance based on unmanned ships has outstanding advantages. Aiming at the problem of lack of overall understanding of the complex environment above and under the water surface during the operation and maintenance of unmanned ships, a stitching and fusion technology of overwater and underwater visual images for unmanned ships is proposed. The software and hardware framework of the overwater and underwater visual image fusion system is constructed, the image processing methods in different environments are defined, and the accurate acquisition of obstacle information is realized. In the two experimental scenarios, the stitching accuracy of the obstacle model based on an extended neighborhood method can reach more than 85% within the obstacle distance of 8 m and more than 80% within the obstacle distance of 14 m. An image-driven Frustum?PointNets detection algorithm is proposed to obtain comprehensive obstacle avoidance information. In addition, the average accuracy of the three-dimensional detection of the algorithm is up to 91.40%. These results are significant and have a good reference value, as it demonstrates that the stitching and fusion method can effectively obtain the comprehensive information of overwater and underwater objects for unmanned ship.