Discovery of Tampered Image with Robust Hashing

  • Zhenjun Tang
  • Junwei Yu
  • Xianquan Zhang
  • Shichao Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8933)

Abstract

Tampered image discovery from similar images is a challenging problem of multimedia security. Aiming at this issue, we propose a robust image hashing with invariant moments. Specifically, the proposed hashing firstly converts the input image into a normalized image by interpolation, filtering and color space conversion. Then it divides the normalized image into overlapping blocks and extracts invariant moments of blocks to form a feature matrix. Finally, the feature matrix is compressed to make a short hash. Hash similarity is determined by measuring similarity between hash segments with correlation coefficient. Experimental results indicate that our hashing is robust against normal digital operations and can efficiently distinguish tampered images from similar images. Comparisons show that our hashing is better than some notable hashing algorithms in classification performances between robustness and content sensitivity.

Keywords

Robust hashing image hashing invariant moment tampering discovery 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Zhenjun Tang
    • 1
    • 2
  • Junwei Yu
    • 2
  • Xianquan Zhang
    • 1
    • 2
  • Shichao Zhang
    • 1
    • 2
    • 3
  1. 1.Guangxi Key Lab of Multi-source Information Mining & SecurityGuangxi Normal UniversityGuilinP.R. China
  2. 2.Department of Computer ScienceGuangxi Normal UniversityGuilinP.R. China
  3. 3.Faculty of Information TechnologyUniversity of TechnologySydneyAustralia

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