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Adaptive local feature based multi-scale image hashing for robust tampering detection
Yan C.-P.; Pun C.-M.; Yuan X.-C.
2016-01-05
Conference Name2015 IEEE Region 10 Conference
Source PublicationIEEE Region 10 Annual International Conference, Proceedings/TENCON
Volume2016-January
Conference Date1-4 Nov. 2015
Conference PlaceMacao, China
Abstract

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.

KeywordAdaptive Local Feature Extraction Location-context Information Multi-scale Image Hashing Tampering Detection
DOI10.1109/TENCON.2015.7373018
URLView the original
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000380489200307
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Citation statistics
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Yan C.-P.,Pun C.-M.,Yuan X.-C.. Adaptive local feature based multi-scale image hashing for robust tampering detection[C],2016.
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