Abstract
In order to improve the accuracy of the detection and tracking task in the intelligent surveillance system, we propose a shadow elimination algorithm based on HSV spatial feature and texture feature. In this paper, firstly the background subtraction is used to obtain the motion area of the sequence image, where HSV feature is used to determine the threshold value of the shadow elimination which can be completely removed. Then the complete moving target is obtained by OR operator of combining the foreground which is extracted by OTSU and the result which is extracted by HSV. The algorithm is applied to several realistic scenario where exists various shadow. We compare our method with other traditional algorithm and report experimental results, both in terms of noise suppression and detection accuracy. The experimental results show that the proposed method has the better noise suppression and detection accuracy.
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Acknowledgments
This research was supported by National Natural Science Foundation of China (61471162); Program of International science and technology cooperation (2015DFA10940); Science and technology support program (R & D) project of Hubei Province (2015BAA115); PhD Research Startup Foundation of Hubei University of Technology (BSQD13032); Open Foundation of Hubei Collaborative Innovation Center for High-Efficiency Utilization of Solar Energy (HBSKFZD2015005, HBSKFTD2016002).
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Song, R., Liu, M., Wu, M., Wang, J., Liu, C. (2018). A Shadow Elimination Algorithm Based on HSV Spatial Feature and Texture Feature. In: Barolli, L., Zhang, M., Wang, X. (eds) Advances in Internetworking, Data & Web Technologies. EIDWT 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-319-59463-7_58
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DOI: https://doi.org/10.1007/978-3-319-59463-7_58
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