Multimedia Tools and Applications

, Volume 70, Issue 3, pp 1651–1665 | Cite as

Secure and robust image hashing via compressive sensing

  • Rui Sun
  • Wenjun Zeng


Image hash functions find extensive applications in content authentication, database search. This paper develops a novel algorithm for generating a secure and robust image hash based on compressive sensing and Fourier-Mellin transform. Firstly, we incorporate Fourier-Mellin transform into our method to improve its performance under rotation, scale, transition attacks. Secondly, we exploit the property of dimension reduction inherent in compressive sensing for hash design. The statistic structure and sparse of the wavelet coefficients assure efficient compression in situation of including maximum the image features. The hashing method is computationally secure without additional randomization process. Such a combined approach is capable of tackling all types of attacks and thus can yield a better overall performance in multimedia identification. To demonstrate the superior performance of the proposed schemes, receiver operating characteristics analysis over a large image database is performed. Experimental results show that the proposed image hashing is robust to a wide range of distortions and attacks. When compared with the current state-of-the-art methods, the proposed method yields better identification performances under geometric attacks such as rotation attacks and brightness changes.


Compressive sensing Fourier-Mellin transform Image hashing Image identification 



This work was supported by the Natural Science Foundation of China (61001201). The authors appreciate the anonymous reviewers for their constructive comments.


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.School of Computer and InformationHefei University of TechnologyHefeiPeople’s Republic of China
  2. 2.Dept. of Computer ScienceUniversity of Missouri-ColumbiaColumbiaUSA

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