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The development of ViBe foreground detection algorithm using Lévy flights random update strategy and Kinect laser imaging sensor

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Abstract

This paper describes the development of a Lévy flights-based ViBe algorithm for foreground detection. It is based on a novel approach, using a particular class of the generalized random walk known as Lévy flights, to improve the spatial update mechanism. This mechanism originally used the uniform probability distribution, and it is responsible for handling the new objects that appear in the scene. The proposed approach speeds up the inclusion process of ghost regions in the background model and makes it faster than the inclusion of real static foreground objects while maintaining the classification performance. The developed detection algorithm was evaluated using inclusion speed and classification tests, the results showing the efficacy of using Lévy flights with ViBe’s updating mechanism. Experimental tests were also undertaken on the proposed algorithm to validate its ability with real images, obtained through a series of experiments performed using a multi-spectral Kinect laser imaging sensor, and also from a public dataset. The experimental results show the high adaptation capability of this algorithm against the background modification and validate its ability to deal with multi-spectral real images. The developed algorithm achieved a better performance in comparison with traditional ViBe algorithms when extracting background and detecting foreground objects.

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Acknowledgements

I would like to express my sincere gratitude to the Iraqi Ministry of Higher Education and Scientific Research.

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Authors and Affiliations

  1. Laser and Optoelectronics Engineering Department, Al-Nahrain University, Baghdad, Iraq

    Ali A. Al-Temeemy

  2. Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, L69 3GJ, UK

    Ali A. Al-Temeemy

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Correspondence to Ali A. Al-Temeemy.

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Al-Temeemy, A.A. The development of ViBe foreground detection algorithm using Lévy flights random update strategy and Kinect laser imaging sensor. Machine Vision and Applications 33, 58 (2022). https://doi.org/10.1007/s00138-022-01316-8

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  • DOI: https://doi.org/10.1007/s00138-022-01316-8

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