基于语义分割和霍夫变换的可见光图像海天线检测方法
Sea-sky-line detection method for visible image based on semantic segmentation and Hough Transform
陈信强 1陈建慧 2刘恕浩 2韩冰 3赵建森 2李朝锋4
作者信息
- 1. 上海海事大学物流科学与工程研究院,上海201306;上海海事大学商船学院,上海201306
- 2. 武汉理工大学内河航运技术湖北省重点实验室,湖北武汉430063
- 3. 上海船舶运输科学研究所有限公司,上海200135;闽江学院物理与电子信息学院,福建福州350108
- 4. 上海海事大学物流科学与工程研究院,上海201306
- 折叠
摘要
海天线检测是船舶智能航行视觉感知的关键技术.针对水上交通图像中海天线检测受船舶、海浪和天气等因素干扰问题,提出一种基于语义分割和霍夫变换的海天线检测方法.将图像输入基于SegNet网络改进的Mo-SegNet图像语义分割算法进行训练,对图像特征进行学习;用Canny检测算法在语义分割图像中检测出边缘轮廓线;采用霍夫变换拟合边缘像素得到海天线检测结果.在场景一,其检测准确率和交并比分别达到99.28％和74.85％;在场景二,其检测准确率和交并比分别达到98.60％和59.41％;在场景三,其检测准确率和交并比分别达到99.31％和77.19％,试验结果表明,所提出的语义分割与霍夫变换结合的算法在检测海天线方面具有较高的准确性和有效性.
Abstract
Sea-sky-line detection is a key technology for the visual perception of intelligent navigation of ships.To address the challenge of sea-sky line detection being interfered with by ship,waves,and weather in maritime traffic images,a detection method based on semantic segmentation and Hough Transform is proposed.The image is input into the Mo-SegNet image semantic segmentation algorithm improved based on SegNet network for training,and the image features are learned;the Canny detection algorithm is used to detect the contours in the semantically segmented image;and the Hough Transform is used to fit the edge pixels to get the sea-sky-line detection results.In Scene 1,its detection accuracy and intersection and concatenation ratio reach 99.28％ and 74.85％,respectively;in Scene 2,its detection IoU (Intersection over Union) reach 98.60％ and 59.41％,respectively;in Scene 3,its detection IoU reach 99.31％ and 77.19％,respectively,and the experimental results show that the proposed algorithm combining the semantic segmentation and the Hoff Transform has high accuracy and high precision in the sea-sky-line detection.with high accuracy and effectiveness.
关键词
海天线检测/SegNet网络/霍夫变换/水上交通/智能航行Key words
sea-sky-line detection/SegNet network/Hough Transform/water transportation/intelligent navigation引用本文复制引用
出版年
2024
NETL
NSTL
万方数据