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Tao Zhang
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A Moving Objects Detection Method with Resistance to Illumination Change Xiaoling Wang; Tao Zhang; Changhong Chang
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 5: May 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Moving objects detection is conducted in the sequential image of moving objects, which is favorable to detect, identify and analyze the moving objects. It has been applied in video surveillance, virtual reality, and advanced user interfaces. Based on existing research on the Frame Difference Method (FDM) and the Background Subtraction Method (BSM), considering the short time interval between adjacent images used for difference, FDM is adopted for its smaller impact by scene illumination variation, which is complementary to the drawback that BSM is sensitive to environmental variation; while BSM can detect the integral moving objects, which can also make up the disadvantage of FDM in failing to detect the integral moving objects. In this paper, we propose a moving objects detection method with resistance to illumination change. We conclude from the experiment that this method is noise-proof and can adapt the abrupt change in illumination to ensure accuracy of the detection. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.5094
Moving Shadow Removal Algorithm Based on HSV Color Space Xinbo Zhang; Kunpeng Liu; Xiaoling Wang; Changhong Yu; Tao Zhang
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 4: April 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

In order to accurately separate a moving object from its shadow in a monitoring scene, this paper proposes a algorithm, which combines Multi-frame Average method for building background and HSV color space. First, the multi-frame average is used for setting up the background model. Second, the current frame and the background model are converted to HSV color space. In the foreground area, the values of brightness and saturation are smaller than that of the background, while the colors basically remain same. Just using these characters, the shadow is detected and eliminated. Finally, the algorithm is applied in videos with different monitoring scenes from the standard video library, such as highway, laboratory and campus, etc, to verify its effectiveness.  The experiment results show that the algorithm has better accuracy, reliability and robustness than the compared algorithm. DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4991
Co-Authors Changhong Chang Changhong Yu Kunpeng Liu Xiaoling Wang Xinbo Zhang