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Therefore, the majority of moving shadow detection methods cannot be directly used to detect static shadows in single images.
For majority of the moving shadow detection methods, chromatic analysis is the first step.
Sanin et al. [1] classified the moving shadow detection methods under various categories.
Moving shadow detection methods can employ the frame difference technique to locate moving objects and their moving shadows.
Siala et al. [14] described a moving shadow detection algorithm by training the manually segmented shadow regions.
Compared with static shadow detection methods, moving shadow detection methods can employ the powerful background subtraction techniques.
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To prove the effectiveness of our moving shadow algorithm, we carry it out with a practical application of traffic flow detection in ITS (Intelligent Transportation System)—vehicle counting.
The artifact is caused by the moving shadow cast by flowing blood cells.
Most shadow detection methods focus on detecting moving shadows.
However, some factors like dynamic backgrounds and moving shadows might affect the results of foreground detection and make the problems more complicated.
Then, the problem of shadow detection becomes differentiating the moving objects and the moving shadows.
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