Image Splicing Detection Using Inherent Lens Radial Distortion

TL;DR

This paper proposes a novel method for detecting image splicing by analyzing inconsistencies in lens radial distortion, leveraging inherent camera characteristics to identify tampered regions.

Contribution

It introduces the first approach to detect splicing by verifying the consistency of lens radial distortion across image regions.

Findings

Effective detection on synthetic images

Successful application on real images

Demonstrates robustness of radial distortion analysis

Abstract

Image splicing is a common form of image forgery. Such alterations may leave no visual clues of tampering. In recent works camera characteristics consistency across the image has been used to establish the authenticity and integrity of digital images. Such constant camera characteristic properties are inherent from camera manufacturing processes and are unique. The majority of digital cameras are equipped with spherical lens and this introduces radial distortions on images. This aberration is often disturbed and fails to be consistent across the image, when an image is spliced. This paper describes the detection of splicing operation on images by estimating radial distortion from different portions of the image using line-based calibration. For the first time, the detection of image splicing through the verification of consistency of lens radial distortion has been explored in this paper. The conducted experiments demonstrate the efficacy of our proposed approach for the detection of image splicing on both synthetic and real images.