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Robust image hashing via visual attention model and ring partition

Guangxi Key Lab of Multi-source Information Mining & Security, and Department of Computer Science, Guangxi Normal University, Guilin 541004, China

Special Issues: Security and Privacy Protection for Multimedia Information Processing and communication

Robustness is an important property of image hashing. Most of the existing hashing algorithms do not reach good robustness against large-angle rotation. Aiming at this problem, we jointly exploit visual attention model and ring partition to design a novel image hashing, which can make good rotation robustness. In the proposed image hashing, a visual attention model called PFT (Phase spectrum of Fourier Transform) model is used to detect saliency map of preprocessed image. The LL sub-band of saliency map is then divided into concentric circles invariant to rotation by ring partition, and the means and variances of DWT coefficients on concentric circles are taken as image features. Next, these features are encrypted by a chaotic map and the Euclidean distances between normalized encrypted features are finally exploited to generate hash. Similarity between hashes is measured by L 1 norm. Many experimental tests show that our image hashing is robust to digital operations including rotation and reaches good discrimination. Comparisons demonstrate that classification performance of our image hashing outperforms those of some well-known hashing algorithms in terms of receiver operating characteristics curves. Simulation of image copy detection is carried out on an open image database called UCID and the result validates effectiveness of our hashing.
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Keywords image hashing; visual attention model; ring partition; saliency map; image copy detection

Citation: Zhenjun Tang, Yongzheng Yu, Hanyun Zhang, Mengzhu Yu, Chunqiang Yu, Xianquan Zhang. Robust image hashing via visual attention model and ring partition. Mathematical Biosciences and Engineering, 2019, 16(5): 6103-6120. doi: 10.3934/mbe.2019305


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This article has been cited by

  • 1. Zhenjun Tang, Mengzhu Yu, Heng Yao, Hanyun Zhang, Chunqiang Yu, Xianquan Zhang, Robust Image Hashing With Singular Values Of Quaternion SVD, The Computer Journal, 2019, 10.1093/comjnl/bxz127
  • 2. Zhenjun Tang, Hanyun Zhang, Shenglian Lu, Heng Yao, Xianquan Zhang, Robust image hashing with compressed sensing and ordinal measures, EURASIP Journal on Image and Video Processing, 2020, 2020, 1, 10.1186/s13640-020-00509-3

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