Fast and Robust Copy-Move Forgery Detection Using Wavelet Transforms and SURF
Mohammad Hashmi1 and
Avinash Keskar2
1Department of Electronics and Communication
Engineering, National Institute of Technology Warangal, India
2Department
of Electronics and Communication Engineering, Visvesvaraya National
Institute of Technology Nagpur, India
Abstract: Most of the images today are stored in digital format. With the
advent of digital imagery, tampering of images became easy. The problem has
become altogether intensified due to the availability of image tampering
softwares. Moreover there exist cameras with different resolutions and encoding
techniques. Detecting forgery in such cases becomes a challenging task. Furthermore,
the forged image may be compressed or resized which further complicates the
problem. This article focuses on blind detection of copy-move forgery using a
combination of an invariant feature transform and a wavelet transform. The feature
transform employed is Speeded Up Robust Features (SURF) and the wavelet
transforms employed are Discrete Wavelet Transform (DWT) and Dyadic Wavelet
Transform (DyWT). A comparison between the performances of the two wavelet
transforms is presented. The proposed algorithms are different from the
previously proposed methods in a way that they are applied on the whole image,
rather than after dividing the image in to blocks. A comparative study between
the proposed algorithm and the previous block-based methods is presented. From
the results obtained, we conclude that these algorithms perform better than
their counterparts in terms of accuracy, computational complexity and
robustness to various attacks.
Keywords: Image forgery; SURF; DWT; DyWT, CMF.