7 October 2014 Moving shadow detection with multifeature joint histogram
Yanzhao Su, Aihua Li, Yanping Cai, Guoyan Feng, Guangzhi Jin
Author Affiliations +
Abstract
This paper describes a method for moving shadow detection using the joint histogram of multifeatures. In our method, we first obtain the moving region by background subtraction. Then, based on the intensity feature, candidate shadow regions are extracted. Moreover, the joint histogram of intensity, color, and gradient features is constructed in candidate background and foreground regions. Furthermore, the joint histogram is backprojected to the foreground regions to yield the moving shadow likelihood image. In the end, the adaptive threshold is derived by the joint histogram of the foreground and background, and accurate shadow regions are extracted by segmenting the shadow likelihood image with this threshold. The main contribution of this paper is twofold. First, multifeatures are fused together by the joint histogram, which is a unified and simple description method for shadow detection. Second, the histogram of background and foreground was compared with backprojection. Moreover, the final result only depends on a few parameters. Unlike other approaches, our method does not make any assumption and moving shadow regions can be detected fast and accurately. Experimental results show that the proposed method is efficient and robust over a broad range of shadow types and challenging video conditions.
© 2014 SPIE and IS&T 0091-3286/2014/$25.00 © 2014 SPIE and IS&T
Yanzhao Su, Aihua Li, Yanping Cai, Guoyan Feng, and Guangzhi Jin "Moving shadow detection with multifeature joint histogram," Journal of Electronic Imaging 23(5), 053015 (7 October 2014). https://doi.org/10.1117/1.JEI.23.5.053015
Published: 7 October 2014
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image segmentation

Detection and tracking algorithms

Video

Feature extraction

Image processing algorithms and systems

Model-based design

Signal detection

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