Digital Image Forgery Detection Based on the Consistency of Defocus Blur

A passive blind digital image forgery detection method was proposed in this paper. Basic defocus model shows that image patches with similar distances to the lens have similar blur kernel sizes. This consistency is broken in image forgery as the result of possible blurring and different imaging conditions. Our forgery detection technique uses local blur estimation at each edge pixels to exposes the defocus blur inconsistency. Experiment results of tampered images from real law cases show the effectiveness of our technique.