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Robust and fast image hashing with two-dimensional PCA

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Abstract

Image hashing is a useful technology of many multimedia systems, such as image retrieval, image copy detection, multimedia forensics and image authentication. Most of the existing hashing algorithms do not reach a good classification between robustness and discrimination and some hashing algorithms based on dimensionality reduction have high computational cost. To solve these problems, we propose a robust and fast image hashing based on two-dimensional (2D) principal component analysis (PCA) and saliency map. The saliency map determined by a visual attention model called LC (luminance contrast) method can ensure good robustness of our hashing. Since 2D PCA is a fast and efficient technique of dimensionality reduction, the use of 2D PCA helps to learn a compact and discriminative code and provide a fast speed of our hashing. Extensive experiments are carried out to validate the performances of our hashing. Classification comparison shows that our hashing is better than some state-of-the-art algorithms. Computational time comparison illustrates that our hashing outperforms some compared algorithms based on dimensionality reduction.

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Acknowledgements

This work is partially supported by the National Natural Science Foundation of China (61962008, 61762017,61762031,61762015), Guangxi “Bagui Scholar” Team for Innovation and Research, the Guangxi Talent Highland Project of Big Data Intelligence and Application, the Guangxi Natural Science Foundation (2017GXNSFAA198222), and Guangxi Collaborative Innovation Center of Multi-source Information Integration and Intelligent Processing. The authors would like to thank the anonymous referees for their helpful comments and suggestions.

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Authors and Affiliations

  1. Guangxi Key Lab of Multi-Source Information Mining and Security, and Department of Computer Science, Guangxi Normal University, No.15 Yucai Road, Guilin, 541004, China

    Xiaoping Liang, Zhenjun Tang, Jingli Wu & Xianquan Zhang

  2. College of Information Science and Engineering, Guilin University of Technology, Guilin, 541006, China

    Xiaolan Xie

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  1. Xiaoping Liang
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Correspondence to Zhenjun Tang.

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Liang, X., Tang, Z., Xie, X. et al. Robust and fast image hashing with two-dimensional PCA. Multimedia Systems 27, 389–401 (2021). https://doi.org/10.1007/s00530-020-00696-z

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