动态视频监控中海上舰船目标检测  

Ship Target Detection for Moving Video Maritime Surveillance

作　　者：李庆忠[1] 臧风妮[1] 张洋[1] 

机构地区：[1]中国海洋大学工程学院山东省海洋工程重点实验室,山东青岛266100

出　　处：《中国激光》2014年第8期268-274,共7页Chinese Journal of Lasers

基　　金：国家863计划(2006AA09Z237)

摘　　要：为了监测一些危险的海洋区域,使用了基于电荷耦合器件(CCD)的动态平台,提出了一种基于海面背景纹理模型的舰船目标检测算法。利用图像子块离散余弦变换(DCT)域的能量特征,实现了天空背景和海天线的快速检测。为了将船舰目标从水平线下复杂的海水背景中分离出来,提取海天线以下的海面区域图像子块的DCT域纹理特征,并利用自适应模糊c均值聚类方法建立海面的混合纹理模型。利用建立的海面纹理模型,实现了海面背景与舰船目标的分割。实验结果表明该算法可以实现舰船目标的快速、稳健检测,尤其适合于大浪海况下基于运动监视平台的海事监测。In order to monitor some critical maritime areas, a dynamic platform based on charge coupled device （CCD） cameras is used, a novel algorithm for ship target detection based on texture model of sea surface is presented. The sky background and horizon are detected quickly by using an energy feature in discrete cosine transform （DCT） domain of image blocks. In order to separate ship targets from the complex sea background below the horizon, the texture feature of sea surface domain under the horizon image blocks in DCT domain is extracted, and a new texture mixture model of sea surface is developed by using adaptive fuzzy c means clustering technique. Ship targets are segmented from sea background by the constructed sea surface texture model. The experimental results show that the proposed algorithm can detect ship targets quickly and steadily, especially suitable for maritime surveillance based on non-stationary monitoring platforms under the large wave sea background.

关 键 词：图像处理 舰船目标检测 动态视频监测 自适应模糊聚类 纹理建模 离散余弦变换 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]