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Transactions on Data Hiding and Multimedia Security VI pp 83–108Cite as

Histogram-Based Image Hashing for Searching Content-Preserving Copies

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Part of the book series: Lecture Notes in Computer Science ((TDHMS,volume 6730))

Abstract

Image hashing as a compact abstract can be used for content search. Towards this end, a desired image hashing function should be resistant to those content-preserving manipulations (including additive-noise like processing and geometric deformation operations). Most countermeasures proposed in the literature usually focus on the problem of additive noises and global affine transform operations, but few are resistant to recently reported random bending attacks (RBAs). In this paper, we address an efficient and effective image hashing algorithm by using the resistance of two statistical features (image histogram in shape and mean value) for those challenging geometric deformations. Since the features are extracted from Gaussian-filtered images, the hash is also robust to common additive noise-like operations (e.g., lossy compression, low-pass filtering). The hash uniqueness is satisfactory for different sources of images. With a large number of real-world images, we construct a hash-based image search system to show that the hash function can be used for searching content-preserving copies from the same source.

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Author information

Authors and Affiliations

  1. Department of Electronic Engineering, School of Information Science and Technology, Jinan University, Guangzhou, China

    Shijun Xiang

  2. State Key Laboratory of Information Security, Institute of Software, Chinese Academy of Sciences, Beijing, China

    Shijun Xiang

  3. CIST, Graduate School of Information Management and Security, Korea University, Seoul, Korea

    Hyoung Joong Kim

Authors
  1. Shijun Xiang
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  2. Hyoung Joong Kim
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Editor information

Editors and Affiliations

  1. New Jersey Institute of Technology, University Heights, 07102-1982, Newark, NJ, USA

    Yun Q. Shi

  2. Nanyang Technological University, Singapore

    Sabu Emmanuel

  3. National University of Singapore, Singapore

    Mohan S. Kankanhalli

  4. Columbia University, NewYork, NY, USA

    Shih-Fu Chang

  5. Dolby Laboratories, San Francisco, CA, USA

    Regunathan Radhakrishnan

  6. Philips Research, Shanghai, China

    Fulong Ma

  7. Tsinghua Universityy, Beijing, China

    Li Zhao

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© 2011 Springer-Verlag Berlin Heidelberg

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Cite this paper

Xiang, S., Kim, H.J. (2011). Histogram-Based Image Hashing for Searching Content-Preserving Copies. In: Shi, Y.Q., et al. Transactions on Data Hiding and Multimedia Security VI. Lecture Notes in Computer Science, vol 6730. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24556-5_5

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  • DOI: https://doi.org/10.1007/978-3-642-24556-5_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24555-8

  • Online ISBN: 978-3-642-24556-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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