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Erschienen in: Cluster Computing 5/2019

11.12.2017

Motion vector detection based on local autocorrelation coefficient

verfasst von: Honghui Fan, Hongjin Zhu

Erschienen in: Cluster Computing | Sonderheft 5/2019

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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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Metadaten
Titel
Motion vector detection based on local autocorrelation coefficient
verfasst von
Honghui Fan
Hongjin Zhu
Publikationsdatum
11.12.2017
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe Sonderheft 5/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-1428-9

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