Multimedia Tools and Applications

, Volume 76, Issue 2, pp 2609–2626 | Cite as

Robust hashing for image authentication using SIFT feature and quaternion Zernike moments



A novel robust image hashing scheme based on quaternion Zernike moments (QZMs) and the scale invariant feature transform (SIFT) is proposed for image authentication. The proposed method can locate tampered region and detect the nature of the modification, including object insertion, removal, replacement, copy-move and cut-to-paste operations. QZMs considered as global features are used for image authentication while SIFT key-point features provide image forgery localization and classification. Proposed approach performance were evaluated on the color images database of UCID and compared with several recent and efficient methods. These experiments show that the proposed scheme provides a short hash length that is robust to most common image content-preserving manipulations like large angle rotations, and allows us to correctly locating forged image regions as well as detecting types of forgery image.


Robust image hashing Quaternion Zernike moments SIFT Image authentication Forgery image localization 


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.School of Computer Science and EngineeringHunan University of Science and TechnologyXiangtanChina
  2. 2.Key Laboratory of Knowledge Processing and Networked Manufacturing, College of Hunan ProvinceHunan University of Science and TechnologyXiangtanChina
  3. 3.Laboratory of Image Science and Technology, School of Computer Science and EngineeringSoutheast UniversityNanjingChina
  4. 4.Centre de Recherche en Information Médicale Sino-français (CRIBs)RennesFrance

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