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

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Abstract

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.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grants 61271312, the Research Fund for the Hunan Provincial Natural Science Foundation of china under Grant 2015JJ2056, and the Hunan Provincial University Innovation Platform Open Fund Project of China Grant 14K037.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Hunan University of Science and Technology, 411201, Xiangtan, China

    Junlin Ouyang & Yizhi Liu

  2. Key Laboratory of Knowledge Processing and Networked Manufacturing, College of Hunan Province, Hunan University of Science and Technology, 411201, Xiangtan, China

    Junlin Ouyang & Yizhi Liu

  3. Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, 210096, Nanjing, China

    Huazhong Shu

  4. Centre de Recherche en Information Médicale Sino-français (CRIBs), Rennes, F-35000, France

    Huazhong Shu

Authors
  1. Junlin Ouyang
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  2. Yizhi Liu
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  3. Huazhong Shu
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Correspondence to Junlin Ouyang.

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Ouyang, J., Liu, Y. & Shu, H. Robust hashing for image authentication using SIFT feature and quaternion Zernike moments. Multimed Tools Appl 76, 2609–2626 (2017). https://doi.org/10.1007/s11042-015-3225-x

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  • DOI: https://doi.org/10.1007/s11042-015-3225-x

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