Extrinsic signatures embedding and detection in electrophotographic halftoned images through exposure modulation

Pei-Ju Chiang, Purdue University

Abstract

Printer identification based on printed documents can provide forensic information to protect copyright and verify authenticity. In addition to intrinsic features (intrinsic signatures) of the printer, modulating the printing process to embed specific features (extrinsic signatures) will further extend the encoding capacity and decoding accuracy. One of the key issues with embedding extrinsic signatures is that the embedding should not degrade the image quality, but needs to be detectable by a detection algorithm. In this dissertation, we will demonstrate the feasibility of embedding code sequences in EP halftone images by modulating dot size through laser intensity modulation. We have developed corresponding embedding and detection algorithms to embed and extract information. Experimental results indicate that using a 600 dpi native resolution printer's default halftone algorithm, we can encode 5 bits of information in every 310 printer scan-lines or approximately every 0.5 inches. We also develop a printing-scaning model incorporating the impact of the process modulation parameter, e.g. laser intensity, with a stochastic dot interaction model and scanner modulation transfer function (MTF) to estimate the impact of the modulation on a known halftone pattern. This model can be used to examine the embedding and detection algorithm without extensive measurements. Experimental data validates the effectiveness of the proposed model in predicting the impact of laser intensity modulation on the reflectance of the printout. To ensure the extrinsic signature is detectable, the modulation amplitude can not be too low. To find the minimum modulation amplitude with required detection performance, significant amount of printing and measurements are needed. To reduce the required time and effort, a fast search based on a computational model is developed based on the proposed printing-scanning model. With the proposed fast search method, experimental data indicates that more than 90% of measurements can be eliminated.

Degree

Ph.D.

Advisors

Chiu, Purdue University.

Subject Area

Electrical engineering|Mechanical engineering

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