Robust Image Hashing Based on Random Gabor Filtering and Dithered Lattice Vector Quantization
Robust Image Hashing Based on Random Gabor Filtering and Dithered Lattice Vector Quantization
复制标题
基于随机Gabor滤波和抖动格矢量量化的鲁棒图像哈希
DOI:
10.1109/tip.2011.2171698
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发表时间:
2012-04
影响因子:
10.6
通讯作者:
Niu, Xiamu
中科院分区:
文献类型:
--
作者:
Li, Yuenan;Lu, Zheming;Zhu, Ce;Niu, Xiamu
In this paper, we propose a robust-hash function based on random Gabor filtering and dithered lattice vector quantization (LVQ). In order to enhance the robustness against rotation manipulations, the conventional Gabor filter is adapted to be rotation invariant, and the rotation-invariant filter is randomized to facilitate secure feature extraction. Particularly, a novel dithered-LVQ-based quantization scheme is proposed for robust hashing. The dithered-LVQ-based quantization scheme is well suited for robust hashing with several desirable features, including better tradeoff between robustness and discrimination, higher randomness, and secrecy, which are validated by analytical and experimental results. The performance of the proposed hashing algorithm is evaluated over a test image database under various content-preserving manipulations. The proposed hashing algorithm shows superior robustness and discrimination performance compared with other state-of-the-art algorithms, particularly in the robustness against rotations (of large degrees).
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期刊:
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发表时间:
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期刊:
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影响因子:
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