Compressive sensing-based image hashing

Li Wei Kang, Chun Shien Lu*, Chao Yung Hsu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

40 Citations (Scopus)


In this paper, a new image hashing scheme satisfying robustness and security is proposed. We exploit the property of dimensionality reduction inherent in compressive sensing/sampling (CS) for image hash design. The gained benefits include (1) the hash size can be kept small and (2) the CS-based hash is computationally secure. We study the use of visual information fidelity (VIF) for hash comparison under Stirmark attacks. We further derive the relationships between the hash of an image and both of its MSE distortion and visual quality measured by VIF, respectively. Hence, based on hash comparisons, both the distortion and visual quality of a query image can be approximately estimated without accessing its original version. We also derive the minimum distortion for manipulating an image to be unauthentic to measure the security of our scheme.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings
PublisherIEEE Computer Society
Number of pages4
ISBN (Print)9781424456543
Publication statusPublished - 2009
Externally publishedYes
Event2009 IEEE International Conference on Image Processing, ICIP 2009 - Cairo, Egypt
Duration: 2009 Nov 72009 Nov 10

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880


Other2009 IEEE International Conference on Image Processing, ICIP 2009


  • Authentication
  • Compressive sensing
  • Image hashing
  • Robustness
  • Security
  • Visual information fidelity

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing


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