Detection of Clones in Digital Images

TL;DR

This paper compares seven algorithms for detecting cloned regions in digital images, analyzing their effectiveness and robustness against common image manipulations to improve image authenticity verification.

Contribution

It provides a comprehensive experimental comparison of seven cloning detection algorithms, highlighting their strengths and weaknesses in various post-processing scenarios.

Findings

DCT and DWT combined with SVD show high robustness.

Simple SOBMwLS algorithm is faster but less robust.

Detection effectiveness varies with post-processing operations.

Abstract

During the recent years, tampering of digital images has become a general habit among people and professionals. As a result, establishment of image authenticity has become a key issue in fields those make use of digital images. Authentication of an image involves separation of original camera outputs from their tampered or Stego counterparts. Digital image cloning being a popular type of image tampering, in this paper we have experimentally analyzed seven different algorithms of cloning detection such as the simple overlapped block matching with lexicographic sorting (SOBMwLS) algorithm, block matching with discrete cosine transformation, principal component analysis, discrete wavelet transformation and singular value decomposition performed on the blocks (DCT, DWT, PCA, SVD), two combination models where, DCT and DWT are combined with singular value decomposition (DCTSVD and DWTSVD. A comparative study of all these techniques with respect to their time complexities and robustness of detection against various post processing operations such as cropping, brightness and contrast adjustments are presented in the paper.