Robust image hashing using progressive feature selection for tampering detection

Chi Man Pun, Cai Ping Yan, Xiao Chen Yuan

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)


The main problem addressed in this paper is the robust tamper detection of the image received in a transmission under various content-preserving attacks. To this aim the progressive feature point selection method is proposed to extract the feature points of high robustness; with which, the local feature and color feature are then generated for each feature point. Afterwards, the robust image hashing construction method is proposed by using the location-context information of the features. The constructed hash is attached to the image before transmission and it can be used for analyzing at destination to filter out the geometric transformations occurred in the received image. After image restoration, the similarity of the global hashes between the source image and restored image is calculated to determine whether the received image has the same contents as the trusted one or has been maliciously tampered. When the received image being judged as a tampered image, the hashes calculated with the proposed Horizontal Location-Context Hashing (HLCH) and Vertical Location-Context Hashing (VLCH) methods will be used to locate the tampered regions. Experimental results on different images with tampering of arbitrary size and location demonstrate that our image authentication and tampering localization scheme are superior to the state-of-the-art methods under various attacks.

Original languageEnglish
Pages (from-to)11609-11633
Number of pages25
JournalMultimedia Tools and Applications
Issue number10
Publication statusPublished - 1 May 2018
Externally publishedYes


  • Horizontal location-context hashing (HLCH)
  • Image authentication
  • Progressive feature point selection
  • Robust image hashing
  • Tampering detection
  • Vertical location-context hashing (VLCH)


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