@inproceedings{da797bd1c1d54e8e9bb54e736111e965,
title = "Adaptive local feature based multi-scale image hashing for robust tampering detection",
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.",
keywords = "Adaptive Local Feature Extraction, Location-Context Information, Multi-Scale Image Hashing, Tampering Detection",
author = "Yan, {Cai Ping} and Pun, {Chi Man} and Yuan, {Xiao Chen}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 35th IEEE Region 10 Conference, TENCON 2015 ; Conference date: 01-11-2015 Through 04-11-2015",
year = "2016",
month = jan,
day = "5",
doi = "10.1109/TENCON.2015.7373018",
language = "English",
series = "IEEE Region 10 Annual International Conference, Proceedings/TENCON",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "TENCON 2015 - 2015 IEEE Region 10 Conference",
address = "United States",
}