水利信息化Issue(2)：46-53,8.DOI:10.19364/j.1674-9405.2026.02.007
面向河湖水域的AI半自动标注方法及软件设计
AI-based semi-automatic annotation method and software design for river and lake water bodies
朱水萍 1胡世明 2王灵敏 2江乘辉 1李翼星 2唐喜珍2
作者信息
- 1. 舟山市普陀区农业农村局,浙江舟山 316100
- 2. 浙江中泓智水科技有限公司,浙江 杭州 310052
- 折叠
摘要
Abstract
Currently,mainstream open-source annotation tools often require manual outlining and delineation of water conservancy targets during semantic annotation,which is time-consuming,labor-intensive,and prone to inaccuracies.To address these issues,a semi-automatic annotation method for river and lake water bodies was proposed,combining MAFs(Morphological Attribute Filtering)and SAM(Segment Anything Model).Interactive prompt points were input into the SAM prompt encoder to obtain initial segmentation masks.MAFs was then applied to the masks to eliminate noise such as"isolated islands"and"speckles"in the initial SAM results,ultimately producing high-quality masks.Experiments and software development were conducted using more than 12 000 UAV-acquired water body images.The results showed that,compared with traditional annotation tools,the average annotation time was reduced from 20～30 seconds per image to 2～3 seconds per image.In addition,noise interference such as"isolated islands"and"burrs"was reduced,resulting in higher-quality annotated images.These findings indicate that the proposed method achieves high annotation efficiency and quality,thereby shortening sample preparation time and improving sample quality in semantic model training.关键词
AI语义识别/半自动标注/SAM/MAFs/河湖库Key words
AI semantic recognition/semi-automatic annotation/SAM/MAFs/rivers and lakes分类
信息技术与安全科学引用本文复制引用
朱水萍,胡世明,王灵敏,江乘辉,李翼星,唐喜珍..面向河湖水域的AI半自动标注方法及软件设计[J].水利信息化,2026,(2):46-53,8.
