Gradient-Based Illumination Description for Image Forgery Detection

Matern F, Riess C, Stamminger M (2019)

Publication Language: English

Publication Type: Journal article, Original article

Publication year: 2019



DOI: 10.1109/TIFS.2019.2935913


The goal of blind image forensics is to determine authenticity and origin of an image without using an explicitly embedded security scheme. Most existing forensic methods can roughly be grouped into statistical and physics-based approaches. Statistical methods can oftentimes be fully automated, and achieve impressive results on current state-of-the-art benchmarks. Physics-based methods explain image inconsistencies using an analytic model, and are more robust to common image processing operations such as resizing or recompression.

In this work, we propose a physics-based forensic descriptor to characterize 2-D lighting environments of objects. The key idea is that the integral over a gradient field of an object indicates the direction of incident light in the image plane. In contrast to prior 2-D lighting methods, the proposed method is remarkably robust to changes in object color and variations in user input, as it operates on the whole object area instead of object contours. Furthermore, we show that the proposed method is unaffected by image resizing or compression, which makes it possible to analyze images that are impossible to analyze with current state-
of-the-art statistical methods.

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How to cite


Matern, F., Riess, C., & Stamminger, M. (2019). Gradient-Based Illumination Description for Image Forgery Detection. IEEE Transactions on Information Forensics and Security.


Matern, Falko, Christian Riess, and Marc Stamminger. "Gradient-Based Illumination Description for Image Forgery Detection." IEEE Transactions on Information Forensics and Security (2019).

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