Image hash generation method using hierarchical histogram

Yong Soo Choi, Jong Hyuk Park

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

Recently, web applications, such as Stock Image and Image Library, are developed to provide the integrated management for user's images. Image hashing techniques are used for the image registration, management and retrieval as the identifier also, investigations have been performed to raise the hash performance like discernment. This paper proposes GLOCAL image hashing method utilizing the hierarchical histogram which is based on histogram bin population method. So far, many studies have proven that image hashing techniques based on this histogram are robust against image processing and geometrical attacks. We modified existing image hashing method developed by our research team [20]. The main idea of the paper is that it helps generate more fluent hash string if we have specific length of histogram bin. Another operation is empowering weighting factor into hash string at each level. Thus, we can raise the magnitude of hash string generated from same context or features and also strengthen the robustness of generated hash.

Original languageEnglish
Pages (from-to)181-194
Number of pages14
JournalMultimedia Tools and Applications
Volume61
Issue number1
DOIs
StatePublished - Nov 2012

Keywords

  • Hierarchical hash generation
  • Image hash
  • Robustness
  • Statistical hypothesis testing

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