Fourier-Residual for Printer Identification

摘要

Printer identification is challenging due to advanced software technologies in the field of forgery detection. This paper presents a new idea of using the Fourier transform residual for the identification of documents printed by different printers. The proposed approach first convolves a Laplacian mask with a Fourier transform in the frequency domain to smoothen the edges. Next, we apply an inverse Fourier transform to reconstruct images from smoothed information (RFL). Similarly, the proposed approach reconstructs images using gray information of the input image (RFG). Then the residual is calculated by subtracting RFG from RFL. The set of statistical features, texture and spatial features are extracted from residual images for printer identification. Experimental results with the existing method on our dataset and a standard dataset show that the proposed approach outperforms the existing approach on both the datasets in terms of classification rate, recall, precision and F-measure.