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Traffic flow detection and statistics via improved optical flow and connected region analysis

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Abstract

Moving vehicle detection plays an important role in intelligent transportation systems. One of the common methods used in moving vehicle detection is optical flow. However, conventional Horn–Schunck optical flow consumes too much time when calculating dense optical flows so that it cannot meet the real-time requirements. This paper proposes a novel improved Horn–Schunck optical flow algorithm based on inter-frame differential method. In our algorithm, optical flow field distribution is only calculated for pixels with larger gray values in the difference image, while for other pixels we applied the iterative smooth. The number of vehicles in the videos of traffic conditions is counted by setting the virtual loop and detecting optical flow information. To extract the moving vehicle as accurately as possible, we also propose a method to obtain moving vehicle minimum bounding rectangle based on the connected region analysis. Finally, we compare the improved optical flow with other four optical flow algorithms in moving vehicle extraction and vehicle flow detection, from which our method gives a much more accurate result.

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Acknowledgements

This work has been supported by National Natural Science Foundation of China (61203261), China Postdoctoral Science Foundation funded project (2012M521335), Jiangsu Key Laboratory of Big Data Analysis Technology/B-DAT (Nanjing University of Information Science and Technology, Grant No.: KXK1404), Research Fund of Guangxi Key Lab of Multi-source Information Mining and Security (MIMS16-02) and the Fundamental Research Funds of Shandong University (2015JC014).

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Authors and Affiliations

  1. School of Control Science and Engineering, Shandong University, Jinan, 250061, China

    Yanan Peng, Zhenxue Chen & Chengyun Liu

  2. Department of Electrical and Computer Engineering, University of Windsor, Windsor, N9B 3P4, Canada

    Q. M. Jonathan Wu

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  1. Yanan Peng
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  2. Zhenxue Chen
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  3. Q. M. Jonathan Wu
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  4. Chengyun Liu
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Correspondence to Zhenxue Chen.

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Peng, Y., Chen, Z., Wu, Q.M.J. et al. Traffic flow detection and statistics via improved optical flow and connected region analysis. SIViP 12, 99–105 (2018). https://doi.org/10.1007/s11760-017-1135-2

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  • DOI: https://doi.org/10.1007/s11760-017-1135-2

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