Digital Image Forgery Detection Based on Characteristics of Background Noise

DOI

10.2991/icimm-16.2016.106How to use a DOI?

Keywords

Image forensics; Background noise; Wavelet transform; Skewness

Abstract

In this paper, we proposed a method to detect splicing forgery by using wavelet transform and background noise estimation in digital image. To achieve this target, we divide image into some sub-blocks and use wavelet transform to extract the low-frequency sub-band coefficients of each ones. Then, the noise standard deviation in each bands can be estimated with the statistical properties of skewness. In the end, the morphological marker is used to tamper with the region. Comparisons with existing methods by experiments showed that our proposed method is effective in estimating the noise standard deviation, and has high accuracy in detecting and localizing forgery parts especially in local smooth regions.

Copyright

© 2016, 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  - Jiming Zheng
AU  - Guoyu Zhou
AU  - Jinling Geng
AU  - Qinghua Zhang
PY  - 2016/11
DA  - 2016/11
TI  - Digital Image Forgery Detection Based on Characteristics of Background Noise
BT  - Proceedings of the 6th International Conference on Information Engineering for Mechanics and Materials
PB  - Atlantis Press
SP  - 585
EP  - 591
SN  - 2352-5401
UR  - https://doi.org/10.2991/icimm-16.2016.106
DO  - 10.2991/icimm-16.2016.106
ID  - Zheng2016/11
ER  -