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Motion vector detection based on local autocorrelation coefficient

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Abstract

This paper introduced local autocorrelation (LAC) to the preprocessing of motion vector detection in order to increase the detection accuracy of the moving vector. We applied LAC coefficient, Sobel operator and moving average calculation to motion vector detection, and Peak Signal to Noise Ratio is used to quantitative evaluation and analysis of motion vector detection accuracy. LAC optimum parameters corresponding to motion vector detection are obtained by a comparative experiment. LAC with optimum parameters achieve higher detection accuracy for the two kinds of video image with illumination changes and without illumination changes. The effectiveness of the LAC coefficient as the preprocessing algorithm of motion vector detection is verified, and the accuracy of the motion vector detection is improved.

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Acknowledgements

The authors acknowledge the Changzhou Science and Technology Support Project (CE20175026, CE20165028) and Program of six talent tops of Jiangsu Province (DZXX-031).

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Authors and Affiliations

  1. School of Computer Engineering, Jiangsu University of Technology, Changzhou, 213001, Jiangsu, China

    Honghui Fan & Hongjin Zhu

  2. Key Laboratory of Cloud Computing & Intelligent Information Processing of Changzhou City, Changzhou, 213001, Jiangsu, China

    Hongjin Zhu

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  1. Honghui Fan
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  2. Hongjin Zhu
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Correspondence to Hongjin Zhu.

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Fan, H., Zhu, H. Motion vector detection based on local autocorrelation coefficient. Cluster Comput 22 (Suppl 5), 11633–11639 (2019). https://doi.org/10.1007/s10586-017-1428-9

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  • DOI: https://doi.org/10.1007/s10586-017-1428-9

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