Image Tampering Detection Based on Inherent Lighting Fingerprints

Abstract

Digital Imaging experienced unprecedented growth in the past few years with the increase in easily accessible handheld digital devices. This furthers the applications of digital images in many areas. With the amassed recognition and accessibility of low cost editing software, the integrity of images can be easily compromised. Recently, image forensics has gained popularity for such forgery detection. However, these techniques still lag behind to prove the authenticity of the images against counterfeits. Therefore, the issue of credibility of the images as a legal proof of some event or location become imperative. The proposed work showcases a state-of-the art forgery detection methodology based on the lighting fingerprints available within digital images. Any manipulation in the image(s) leaves dissimilar fingerprints, which can be used to prove the integrity of the images after the analysis. This technique performs various operations to obtain the intensity and structural information. Dissimilar features in an image are obtained using Laplacian method followed by surface normal estimation. Applying this information, source of the light direction is estimated in terms of angle $\psi$. The proposed technique demonstrates an efficient tool of digital image forgery detection by identifying dissimilar fingerprints based on lighting parameters. Evaluation of the proposed technique is successfully done using CASIA1 image dataset.