一种有效的图像阴影自动去除算法

An effective shadow removal approach

  • 摘要: 目标跟踪与检测研究中,在检测运动前景时也会检测到运动目标投射的阴影。阴影使得运动目标发生几何变形,可能造成运动目标粘连,甚至造成检测不到目标。阴影去除后才能较真实的得到运动目标重心。本文研究一种利用图像YCbCr颜色信息去除阴影的方法。首先利用背景减的方法得到带影子的目标区域,其次进行YCbCr空间的背景减,由于影子和目标物体在YCbCr空间背景减信息有较大差别,因此可以通过阈值判断得到去影之后的精确目标区域,目标物体识别的精确性和鲁棒性将会得到提高。实验结果表明,该方法在去除阴影的同时又较好地保留了前景目标的信息,是一种有效的阴影去除方法。

     

    Abstract: In the research of object tracking and detection, the shadow of objects usually is thought as part of the moving foreground, it will cause the merger of moving targets, geometric distortion and even loss of target. If the shadow of moving objects could be removed we could truly get the gravity center of objects and recognize the action of the object correctly. In this paper we propose a shadow removal approach in YCbCr color space. Firstly, we used background subtraction method to get the candidate target area with a shadow. Second, we did background subtraction in the YCbCr space, because the YCbCr information of Shadow and target objects were very different, So you could get the precise target area after shadow removal through threshold determination, it would improve accuracy and robustness of a specific object recognition. Experimental results show that the method could remove the shadow while retaining the information of foreground objects as much as possible.

     

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