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Corner based statistical modelling in vehicle detection under various condition for traffic surveillance

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Abstract

The paper proposes a robust approach to detect and track the vehicle under various climatic conditions and in the presence of camera shake, shadows, sudden illumination change. Corners have significant features to detect and track the vehicle. Corner points from the vehicular region are segmented from non - vehicular regions based on the statistical background corner point model. The foreground corner points that belong to the vehicular region are grouped using Euclidean distance as they are closely associated with each other. The flickering effects caused by the corner detection algorithm are handled by tracking these corner points. The detection accuracy of the algorithm is 94.32%.

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Acknowledgements

The Research is supported by Science Engineering Research Board, under startup Research Grant Program in Engineering Science with File NO. : SERB/SRG/2019/002277 and is gratefully acknowledged.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, KLS Gogte Institute of Technology, Belagavi, India

    Mallikarjun Anandhalli & Tanuja A

  2. Department of Computer Science and Engineering, KLE Technological University, Hubballi, India

    Vishwanath P. Baligar

  3. Department of Information Science and Engineering, Smt. Kamala, Sri Venkappa M. Agadi College of Engineering and Technology, Laxmeshwar, India

    Pavana Baligar

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  1. Mallikarjun Anandhalli
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  2. Tanuja A
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  3. Vishwanath P. Baligar
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  4. Pavana Baligar
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Correspondence to Mallikarjun Anandhalli.

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Anandhalli, M., A, T., Baligar, V.P. et al. Corner based statistical modelling in vehicle detection under various condition for traffic surveillance. Multimed Tools Appl 81, 28849–28874 (2022). https://doi.org/10.1007/s11042-022-12422-0

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  • DOI: https://doi.org/10.1007/s11042-022-12422-0

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