海上作业工作中，通常通过机器视觉获取环境视频信息。其中，分析海上舰船目标是一项重要工作。为此，提出基于动态视频信息分析的海上舰船目标检测方法。首先使用差分处理方法去除动态视频图像中的噪声，并适应度增强背景光线。然后缩小运动目标检测区域，实时更新背景模型，降低背景对检测目标的影响。在划分海上舰船动态视频图像后，检测天空和海天线，构建海面背景的纹理模型。最后，去除天空与非海面纹理的像素点，即可得到海上舰船目标。实验结果表明，该方法的检测精度高，对动态视频检测响应速度快且去噪效果较好。
In offshore operations, environment video information is usually obtained through machine vision. Among them, the analysis of ship targets at sea is an important work. Therefore, this study proposes a method of ship target detection based on dynamic video information analysis. First, the difference processing method is used to remove the noise in the dynamic video image, and the fitness is used to enhance the background light. Then the moving object detection area is reduced, and the background model is updated in real time to reduce the impact of the background on the detected object. After dividing the dynamic video images of ships on the sea, the sky and sea antennas are detected to build a texture model of the sea background. Finally, by removing the pixels of the sky and non sea surface texture, the ship target on the sea can be obtained. The experimental results show that the method has high detection accuracy, fast response to dynamic video detection and good denoising effect.
2022,44(20): 169-172 收稿日期：2022-03-29
DOI：10.3404/j.issn.1672-7649.2022.20.035
分类号：TP399
基金项目：教育部“春晖计划”资助项目（Z2016078）；青海师范大学科研基金资助项目（17ZR15）
作者简介：杨帆(1983-)，男，硕士，讲师，研究方向为视频异常分析及人机系统
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