背景分割和阴影检测算法研究

Studies of Background Subtraction and Shadow Detection Algorithm

在基于视觉检测方式的泊位自动引导系统中,从序列图像中提取泊位飞机,检测泊位飞机的阴影区域,是泊位系统实现的关键。基于高斯混合模型的背景分割算法被广泛应用于静态背景分割中,但是该算法在处理高分辨率图像时,算法实时性显著下降;分割体积大而且运动缓慢的物体时,容易产生"拖尾"现象;不能检测出运动物体的阴影区域。为此提出了基于分层图像的改进高斯混合模型背景分割算法,有效地克服了算法实时性差和"拖尾"现象。在此基础上,提出了基于色彩特征和区域特征相结合的阴影检测算法,利用部分空间约束信息,检测出运动物体的阴影区域。实验结果表明了该算法的有效性和实用性。

Docking aircraft extraction from the captured image sequence and its shadow detection are the key works in the Visual Docking Guidance System. The algorithm based on Mixture of Gaussians （MOGS） is widely used to subtract static background. However, the real-time performance of the MOGS algorithm is reduced remarkably when high resolution image is processed, the ＂bad-tail＂ phenomenon occurs when slowly moving and large object is extracted, and the shadow of moving object can not be detected. An improved MOGS algorithm based on hierarchical image is proposed, and the problems of bad real-time and ＂ bad-tail＂ phenomenon are solved. On this condition, a new shadow detection algorithm based on color character and region character is presented, partially spatial constraints are used, and the shadow of moving object is detected exactly. The experimental results in Visual Docking Guidance System show the validity and the practicality of the algorithms.