电光与控制, 2019, 26 (1): 43, 网络出版: 2019-01-19  

应用LSD和聚类的海天/岸岛线检测算法

Application of LSD and Clustering in Sea-Sky Line and Coastline Detection Algorithm
作者单位
海军航空大学, 山东 烟台 264001
摘要
红外图像舰船目标检测中, 目标通常位于海天/岸岛线附近, 预先检测出海天/岸岛线, 确定舰船目标的潜在区域, 可减少目标检测过程中的搜索范围, 降低数据处理量, 提高检测速度。针对传统的海天/岸岛线检测算法对不同背景图像适应性差的问题, 分析了海天/岸岛线特征, 提出了应用LSD线段检测算法和聚类的海天/岸岛线检测算法。首先通过LSD线段检测算法获取图像中局部直线轮廓, 然后通过K-均值聚类获取潜在海天/岸岛线区域, 最后通过分析潜在海天/岸岛线区域纹理特征确定真实的海天/岸岛线位置。实验结果表明, 该方法对多种背景下海天/岸岛线检测适应性强, 检测精度高。
Abstract
In ship target detection of infrared images, the target is usually near the sea-sky line or coastline, thus the sea-sky line and coastline should be detected in advance to determine the potential area of the ship target, reduce the search range of target detection, simplify the data processing, and improve the detection speed.Aiming at the poor adaptability of the traditional sea-sky-line/coastline detection algorithm to different background images, we made an analysis to the features of sea-sky line and coastline, and proposed an algorithm for sea-sky-line/coastline detection by use of LSD line segment detection algorithm and clustering.Firstly, the local straight line contour of the image was obtained by the LSD line segment detection algorithm, and then the potential sea-sky-line/coastline area was obtained by K-means clustering.Finally, the real sea-sky-line/coastline position is determined by analyzing the texture features of the potential sea-sky line and coastline areas.The experimental results show that this method is highly adaptive to the detection of sea-sky line and coastline under various backgrounds and has high detection precision.

詹维, 仇荣超, 马新星. 应用LSD和聚类的海天/岸岛线检测算法[J]. 电光与控制, 2019, 26(1): 43. ZHAN Wei, QIU Rong-chao, MA Xin-xing. Application of LSD and Clustering in Sea-Sky Line and Coastline Detection Algorithm[J]. Electronics Optics & Control, 2019, 26(1): 43.

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!