Digital Image Forgery Detection Based on Characteristics of Background Noise
Jiming Zheng, Guoyu Zhou, Jinling Geng, Qinghua Zhang
Available Online November 2016.
- 10.2991/icimm-16.2016.106How to use a DOI?
- Image forensics; Background noise; Wavelet transform; Skewness
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.
- © 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/).
Cite this article
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 -