A copy-move image forgery detection based on speeded up robust feature transform and Wavelet Transforms

We are currently leaving in a pure digital world where all type of information is mostly stored in digital form. Thus storage of the information is no more a problem and the information can be easily passed on from one place to another in digital format. The big benefit however comes with the hidden loss and in this case it is the tampering of images and videos which has become a matter of serious concern in recent days because of the readily available software tools in the market like Photoshop etc. which can be used by a common person to tamper the image or video for hiding or changing the original contents. Thus for the aforementioned problem, we in this paper propose a series of algorithms which are combination of speeded-up robust feature transforms and Wavelet Transforms. In doing so we will first discuss Speeded-Up Robust Feature (SURF), SURF in combination with Discrete Wavelet Transform (DWT), SURF in combination with Dyadic Wavelet Transform (DyWT). These algorithms are different from the previously proposed algorithm in the manner that they are applied on the entire image to extract features rather than dividing the image into the blocks. From the results obtained we are able to conclude the proposed algorithms are better than their counterparts both in terms of computational complexity and invariance to scale and rotation and also for the combination of attacks.