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 paper, we will demonstrate the feasibility of embedding code sequences in electrophotographic 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.

Digital images can be captured or generated by a variety of sources including digital cameras, scanners and computer graphics softwares. In many cases it is important to be able to determine the source of a digital image such as for criminal and forensic investigation. This paper presents methods for distinguishing between an image captured using a digital camera, a computer generated image and an image captured using a scanner. The method proposed here is based on the differences in the image generation processes used in these devices and is independent of the image content. The method is based on using features of the residual pattern noise that exist in images obtained from digital cameras and scanners. The residual noise present in computer generated images does not have structures similar to the pattern noise of cameras and scanners. The experiments show that a feature based approach using an SVM classifier gives high accuracy.

Forensic characterization of devices is important in many situations such as establishing the trust and verifying authenticity of data and the device that created it. Current forensic identification techniques for digital cameras, scanners and printers are highly reliable due to the fact that each of these devices cannot escape inherent electro-mechanical properties which add "signatures" to the data they produce. In this paper we will describe the sensor forensics work going on at Purdue University.

An improved controller design and implementation technique for electrophotographic process (EP) was proposed. The new controller was modified from a previous design to address two additional issues for generic EP platforms, i.e., reducing position-dependent disturbances and reducing system sensitivity to manufacturing variations in EP engine and consumables. To handle position-dependent periodic disturbances, a digital repetitive controller was developed and implemented using spatial sampling. The result is a control algorithm that will take into account the variation of the nominal operating speed. Second, system variations due to manufacturing variations as well as consumable changes were incorporated into the design of a two degree of freedom (TDOF) robust controller. The controller is optimal in the sense that it minimizes the size of the sensitivity function from a set of disturbance signals to a set of measurable signals critical to print quality, e.g. photoconductor drum velocity or scan line spacing. A suitable trade-off between system performance and robustness to system modeling uncertainties was considered in the synthesis and optimization formulation. The effectiveness of the proposed controller design and implementation technique was numerically and experimentally verified. Printed samples demonstrated significant reduction in visible banding that was verified by reflectance measurement.