Image Splicing Detection Based on Statistical Properties of Benford Model

DOI

10.2991/iccsee.2013.200How to use a DOI?

Keywords

image splicing detection, statistical characteristics, AC coefficient, most significant digit, authenticity

Abstract

For the operation of the image splicing tamper, this paper proposes a novel approach for blind image splicing detection based on statistical properties of the Benford model. Having made discrete wavelet transform (DWT) to the test image, we extracted alternating current (AC) coefficients in discrete cosine transform (DCT) domain of the three RGB color channels from each wavelet component, and then we calculated probability distribution of the most significant digit (MSD) of the AC coefficients in DCT domain by using the Benford model, constructed the detection model of the proposed algorithm. The threshold is set according to significant level of the statistical property difference tampered between before and after, then judgement the authenticity of the images. Experimental results show that the proposed algorithm is capable to detect splicing image efficiently.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Senfeng Tong
AU  - Zhen Zhang
AU  - Yongjie Xie
AU  - Xiaodi Wu
PY  - 2013/03
DA  - 2013/03
TI  - Image Splicing Detection Based on Statistical Properties of Benford Model
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 792
EP  - 795
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.200
DO  - 10.2991/iccsee.2013.200
ID  - Tong2013/03
ER  -