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Robust video copy detection based on ring decomposition based binarized statistical image features and invariant color descriptor (RBSIF-ICD)

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Abstract

Content based video copy detection (CBVCD) is considered as an active research field due to the requirement of copyright protection, business intelligence, video retrieval, etc. In this paper, we propose a CBVCD scheme using Ring decomposition based Binarized Statistical Image Features (RBSIF) and Invariant Color Descriptor (ICD), namely RBSIF-ICD. This hybrid descriptor is based on the combination of texture features extracted using RBSIF and a color characteristics derived using ICD. Firstly, a pre-processing is applied on each video sequence to remove borders. Secondly, the RBSIF descriptor is applied to each video frame to obtain the texture features. Then, ICD is applied to the video frames to construct an invariant color description which is very robust to geometrical attacks. Finally, RBSIF and ICD are fused to develop the RBSIF-ICD that will be very robust against several attacks such as rotation, flipping, strong compression, ... etc. For the evaluation purpose, the TRECVID 2009 database is used to test the robustness of the proposed system. Experiments reveal that the proposed RBSIF-ICD system outperforms the state-of-the-art algorithms under all the attacks and manipulations considered in this framework.

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Acknowledgments

This project is supported by the CDTA project funded by the FNR (Fond National de la Recherche Scientique et de Développement Technologique) of Algeria (FNR:BIOSMC/PCV/14-16).

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Authors and Affiliations

  1. TELECOM Division, Centre de Développement des Technologies Avancées (CDTA), Baba Hassen, Algiers, 16303, Algeria

    Yassine Himeur & Karima Ait Sadi

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  1. Yassine Himeur
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  2. Karima Ait Sadi
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Correspondence to Yassine Himeur.

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Himeur, Y., Sadi, K.A. Robust video copy detection based on ring decomposition based binarized statistical image features and invariant color descriptor (RBSIF-ICD). Multimed Tools Appl 77, 17309–17331 (2018). https://doi.org/10.1007/s11042-017-5307-4

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  • DOI: https://doi.org/10.1007/s11042-017-5307-4

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