Passive Approach for Copy-Move Forgery Detection for Digital Image
- DOI
- 10.2991/iccasp-16.2017.69How to use a DOI?
- Keywords
- DyWT (Dyadic Wavelet Transform), SIFT (Scale Invariant Feature Transform), Copy move forgery, RANSAC etc.
- Abstract
In the present era of the digital world, digital images and videos are the main carriers of information. However, these sources of information can be easily manipulated by using readily available photo editing softwares such as Photoshop etc. Nowadays, it is possible to add or remove some important objects or features from the image without leaving any traces of tampering. Such type of forgery is called as copy move forgery in which objects from the image are copied and pasted within same image. To detect the copy move forgery in digital images have become the most hot research area nowadays. To solve the above problem, this paper proposes a hybrid method which is a combination of Dyadic Wavelet Transform (DyWT) and Scale Invariant Feature Transform (SIFT). In this method, DyWT is used to decompose image into four parts LL, LH, HL, and HH. Since LL part contains most of the information SIFT is applied on LL part to extract the features. Finally sorting algorithm RANSAC is used to match the features and to take the decision about forgery. The performance of proposed algorithm is tested on various images and the results show that algorithm works efficiently.
- Copyright
- © 2017, 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 - V. Rathod AU - J. Gavade PY - 2016/12 DA - 2016/12 TI - Passive Approach for Copy-Move Forgery Detection for Digital Image BT - Proceedings of the International Conference on Communication and Signal Processing 2016 (ICCASP 2016) PB - Atlantis Press SP - 463 EP - 470 SN - 1951-6851 UR - https://doi.org/10.2991/iccasp-16.2017.69 DO - 10.2991/iccasp-16.2017.69 ID - Rathod2016/12 ER -