Adaptive local feature based multi-scale image hashing for robust tampering detection

Cai Ping Yan, Chi Man Pun, Xiao Chen Yuan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


This paper proposes a novel multi-scale image hashing method by using the location-context information of the features generated by adaptive local feature extraction techniques. The adaptive local feature extraction method is proposed for more robust feature descriptors. The global hash is calculated to determine whether the received image has been maliciously tampered. The multi-scale hash is calculated to locate the tampered regions. Experimental results show that the proposed tampering detection scheme is very robust against the content-preserving attacks, including both common signal processing and geometric distortions.

Original languageEnglish
Title of host publicationTENCON 2015 - 2015 IEEE Region 10 Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479986415
Publication statusPublished - 5 Jan 2016
Externally publishedYes
Event35th IEEE Region 10 Conference, TENCON 2015 - Macau, Macao
Duration: 1 Nov 20154 Nov 2015

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON
ISSN (Print)2159-3442
ISSN (Electronic)2159-3450


Conference35th IEEE Region 10 Conference, TENCON 2015


  • Adaptive Local Feature Extraction
  • Location-Context Information
  • Multi-Scale Image Hashing
  • Tampering Detection


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