Research Article

A Benchmark for Perceptual Hashing based on Human Subjective Identification

Hui Zhang, Qiong Li, Haibin Zhang and Xiamu Niu

This study proposed a novel benchmark for evaluating the robustness and discriminability properties of perceptual hashing algorithms. Firstly, two major problems neglected by traditional benchmark are analyzed thoroughly with a concrete experiment. One problem is the inconsistence between the subjective feeling and the objective perceptual distance, the other is the partiality of the performance for different attacks. And then, in order to overcome the problems, a new benchmark for perceptual hashing based on human subjective identification is proposed and the corresponding evaluation methods are presented by illustrative experiments and examples. Present benchmark methods are fairer and more comprehensive than the traditional methods.

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Hui Zhang, Qiong Li, Haibin Zhang and Xiamu Niu, 2009. A Benchmark for Perceptual Hashing based on Human Subjective Identification. Information Technology Journal, 8: 544-550.

DOI: 10.3923/itj.2009.544.550

URL: https://scialert.net/abstract/?doi=itj.2009.544.550

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Authors

Hui Zhang

Qiong Li

Haibin Zhang

Xiamu Niu

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Research Article

A Benchmark for Perceptual Hashing based on Human Subjective Identification

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