Abstract
The importance and relevance of digital-image forensics has attracted researchers to establish different techniques for creating and detecting forgeries. The core category in passive image forgery is copy–move image forgery that affects the originality of image by applying a different transformation. In this paper, a frequency-domain image-manipulation method is presented. The method exploits the localized nature of discrete wavelet transform (DWT) to attain the region of the host image to be manipulated. Both patch and host image are subjected to DWT at the same level l to obtain sub-bands, and each sub-band of the patch is pasted to the identified region in the corresponding sub-band of the host image. Resulting manipulated host sub-bands are then subjected to inverse DWT to obtain the final manipulated host image. The proposed method shows good resistance against detection by two frequency-domain forgery detection methods from the literature. The purpose of this research work is to create a forgery and highlight the need to produce forgery detection methods that are robust against malicious copy–move forgery.
Highlights
In image manipulation, composition, editing, tampering, forgery, or fakery, the ultimate victim is the integrity and authenticity of the image
We propose a passive copy–move image manipulation method that exploits the localized nature of the discrete wavelet transform (DWT)
To counter edge detection and other similar techniques, we aim to dilute the potential artifacts by pasting the wavelet transformed sub-bands of the patch in the corresponding sub-bands of the host and applying inverse DWT to the latter, i.e., the tampered host sub-bands
Summary
Composition, editing, tampering, forgery, or fakery, the ultimate victim is the integrity and authenticity of the image. The usage spectrum is broad, with aesthetics on one extreme and malicious intents (such as blackmailing and character assassination) on the other. Available software such as Adobe Photoshop, GIMP, or even XnView has further escalated the matter. No matter how noble intentions are, while introducing any innovation to manipulate images, the stakes of negativity are always high. The burden to deal with such negativity shifts is on the forensic analyst. Described as an “arms race” in [1], this competition between manipulator and forensic analyst may never end
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