Acoustics, Speech, and Signal Processing, IEEE International Conference on (2009)
Apr. 19, 2009 to Apr. 24, 2009
Junwen Mao , ECE Dept., University of Rochester, NY, 14627-0126, USA
Gaurav Sharma , ECE Dept., University of Rochester, NY, 14627-0126, USA
Orhan Bulan , ECE Dept., University of Rochester, NY, 14627-0126, USA
We present a forensic technique for analyzing a printed image in order to trace the originating printer. Our method, which is applicable for commonly used electrophotographic (EP) printers, operates by exploiting the geometric distortion that these devices inevitably introduce in the printing process. In the proposed method, first a geometric distortion signature is estimated for an EP printer. This estimate is obtained using only the images printed on the printer and without access to the internal printer controls. Once a database of printer signatures is available, the printer utilized to print a test image is identified by computing the geometric distortion signature from test image and correlating the computes signatures against the printer signatures in the database. Experiments conducted over a corpus of EP printers demonstrate that the geometric distortion signatures of test documents exhibit high correlation with the corresponding printer signatures and a low correlation with other printer signatures. The method is therefore quite promising for forensic printer identification applications. We highlight several of the capabilities and challenges for the method.
Junwen Mao, Gaurav Sharma, Orhan Bulan, "Geometric distortion signatures for printer identification", Acoustics, Speech, and Signal Processing, IEEE International Conference on, vol. 00, no. , pp. 1401-1404, 2009, doi:10.1109/ICASSP.2009.4959855