摘要
运动船舶尺寸等参数的视频检测中,与船体同步运动的水面拖纹干扰会严重影响检测精度.为此,在描述显著性检测机理的基础上,提出了抑制船尾拖纹的船舶显著性视频检测方法:根据颜色对比度直方图得到内河场景的显著图;将原图超像素分割成若干子区域,以区域空间位置关系改进直方图对比度显著性检测结果得到区域显著图;通过该区域显著图初始化GrabCut算法,迭代分割过程中加入腐蚀膨胀操作来逼近目标边缘,从而提取运动船舶.实况视频测试结果表明,该方法能有效地抑制船尾拖纹,准确地检测出内河运动船舶,准确性达到94.6%.
In the video detection of parameters such as ship size,the synchronous movement of the stern ripples seriously affects the accuracy. A novel algorithm of ships saliency detection for inhibiting the stern ripples was proposed based on video sequence. Firstly,the algorithm utilized a histogram-based contrast( HC) method to define HC saliency map for inland waterway by using color statistics of the input image.Then,it performed super-pixel segmentation on original image to get several sub-regions and used regional spatial relationship to improve HC saliency test results,which was named as regional saliency map. Finally,by the initialization of Grab Cut algorithm with the regional saliency map,the iterative process was added by erosion and dilation operations to get close to the target edge,so that the moving ship was extracted. Experimental results showed that the proposed approach could effectively restrain the stern ripple,accurately detect the ship in inland waterway,and its accuracy was up to 94. 6%.
出处
《北京邮电大学学报》
EI
CAS
CSCD
北大核心
2017年第S1期72-76,共5页
Journal of Beijing University of Posts and Telecommunications
基金
国家自然科学青年基金项目(61502226)
国家船联网专项科技项目(2012-364-641-209)
