Image copy detection via dictionary learning and sparse coding

Chih Yang Lin*, Li Wei Kang, Kahlil Muchtar, Jyh Da Wei, Chia Hung Yeh

*Corresponding author for this work

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

Abstract

In this paper, a new robust image hashing scheme for image authentication via dictionary-based sparse representation of images is proposed. For image hash extraction, we create an over-complete dictionary containing the prototype image atoms to build the hash for an image, where each image patch can be represented by sparse linear combinations of these atoms. The major contribution is to formulate the image authentication problem as a sparse coding problem. Based on the energy distribution of nonzero coefficients of the sparse representation for an image, the authentication of the image can be achieved. Simulation results have shown the proposed scheme is robust to several content-preserving image attacks defined in StirMark.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Information Security and Intelligent Control, ISIC 2012
Pages242-245
Number of pages4
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event3rd International Conference on Information Security and Intelligent Control, ISIC 2012 - Yunlin, Taiwan
Duration: 2012 Aug 142012 Aug 16

Publication series

NameProceedings - 3rd International Conference on Information Security and Intelligent Control, ISIC 2012

Conference

Conference3rd International Conference on Information Security and Intelligent Control, ISIC 2012
Country/TerritoryTaiwan
CityYunlin
Period2012/08/142012/08/16

Keywords

  • compressive sensing
  • copy detection
  • dictionary learning
  • image authentication
  • image hashing
  • sparse coding

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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