基于分层码本模型的阴影消除方法

SHADOW ELIMINATION APPROACH BASED ON LAYERED CODEBOOK MODEL

为了解决复杂环境,特别是背景改变带来的背景模型变化,对运动目标的阴影检测与消除效果产生影响的问题,给出一种在YCb Cr颜色空间下基于分层码本模型的阴影消除方法。目标检测时采用分层建模与检测技术检测出运动区域并更新背景模型,从永久背景模型中提取背景图像并采用基于色度的阴影检测方法消除阴影,避免在阴影检测与消除中使用固定背景的问题。在公开测试集上的实验结果表明,该方法能有效地适应背景的动态变化,对复杂环境中的前景目标检测与阴影消除有很好的效果。

The background model changes brought about by the complex environment, and in particular the variation of background have the impact on the shadow detection and elimination effects for moving objects. In order to solve this problem, we proposed a shadow elimination method which is based on layered codebook model in YCbCr colour space. In objects detection phase, the method uses the stratified modelling and detection technique to detect the moving regions and to update the background model, and extracts from the permanent background model the background images, and adopts the chroma-based shadow detection method to remove shadows, thus avoids the problem of using the fixed background when detecting and removing shadows. Results of experiment on public test set demonstrated that the method was able to effectively adapt to the dynamic changes of background, and had excellent effect on foreground objects detection and shadow elimination in complex environment.