Several methods exist for printer identification from a printed document. We have developed a system that
performs printer identification using intrinsic signatures of the printers. Because an intrinsic signature is tied
directly to the electromechanical properties of the printer, it is difficult to forge or remove. In previous work we
have shown that intrinsic signatures are capable of solving the problem of printer classification on a restricted set
of printers. In this paper we extend our previous work to address the problem of forensic printer identification,
in which a document may or may not belong to a known set of printers. We propose to use a Euclidean distance
based metric in a reduced feature space. The reduced feature space is obtained by using sequential feature
selection and linear discriminant analysis.
KEYWORDS: Printing, Information security, Optical proximity correction, Digital watermarking, System identification, Particles, Security printing, Manufacturing, Image analysis, Signal analyzers
Several methods exist for printer identification from a printed document. We have developed a system that
performs printer identification using intrinsic signatures of the printers. Because an intrinsic signature is tied
directly to the electromechanical properties of the printer, it is difficult to forge or remove. There are many
instances where existance of the intrinsic signature in the printed document is undesireable. In this work we
explore texture based attacks on intrinsic printer identification from text documents. An updated intrinsic printer
identification system is presented that merges both texture and banding features. It is shown that this system
is scable and robust against several types of attacks that one may use in an attempt to obscure the intrinsic
signature.
KEYWORDS: Printing, Modulation, Signal detection, Digital watermarking, Information security, Data hiding, Linear filtering, Optical proximity correction, Manufacturing, Particles
In today's digital world securing different forms of content is very important in terms of protecting copyright
and verifying authenticity. One example is watermarking of digital audio and images. We believe that a marking
scheme analogous to digital watermarking but for documents is very important. In this paper we describe the
use of laser amplitude modulation in electrophotographic printers to embed information in a text document.
In particular we describe an embedding and detection process which has the capability to embed 14 bits into
characters that have a left vertical edge. For a typical 12 point document this translates to approximately 12000
bits per page.
Given the wide use of Radio Frequency (RF) devices for applications ranging from data networks to wireless
sensors, it is of interest to be able to characterize individual devices to verify compliance with FCC Part 15 rules.
In an effort to characterize these types of devices we have developed a system that utilizes specially designed
probe signals to elicit a response from the device from which unique characteristics can be extracted. The
features that uniquely characterize a device are referred to as device signatures or device fingerprints.
We apply this approach to RF devices which employ different bandpass filters, and construct training based
classifiers which are highly accurate. We also introduce a model-based framework for optimal detection that can
be employed to obtain performance limits, and to study model mismatch and probe optimization.
Many emergency response units are currently faced with restrictive budgets that prohibit their use of advanced
technology-based training solutions. Our work focuses on creating an affordable, mobile, state-of-the-art emergency
response training solution through the integration of low-cost, commercially available products. The
system we have developed consists of tracking, audio, and video capability, coupled with other sensors that can
all be viewed through a unified visualization system. In this paper we focus on the video sub-system which
helps provide real time tracking and video feeds from the training environment through a system of wearable
and stationary cameras.
These two camera systems interface with a management system that handles storage and indexing of the
video during and after training exercises. The wearable systems enable the command center to have live video
and tracking information for each trainee in the exercise. The stationary camera systems provide a fixed point
of reference for viewing action during the exercise and consist of a small Linux based portable computer and
mountable camera. The video management system consists of a server and database which work in tandem with
a visualization application to provide real-time and after action review capability to the training system.
When traveling in a region where the local language is not written using the Roman alphabet, translating written
text (e.g., documents, road signs, or placards) is a particularly difficult problem since the text cannot be easily
entered into a translation device or searched using a dictionary. To address this problem, we are developing
the "Rosetta Phone," a handheld device (e.g., PDA or mobile telephone) capable of acquiring a picture of the
text, identifying the text within the image, and producing both an audible and a visual English interpretation
of the text. We started with English, as a developement language, for which we achieved close to 100% accuracy
in identifying and reading text. We then modified the system to be able to read and translate words written
using the Arabic character set. We currently achieve approximately 95% accuracy in reading words from a small
directory of town names.
In today's digital world securing different forms of content is
very important in terms of protecting copyright and verifying
authenticity. One example is watermarking of digital audio and images.
We believe that a marking scheme analogous to digital watermarking
but for documents is very important.
In this paper we describe the use of laser amplitude modulation
in electrophotographic printers to embed information in a text
document. In particular we describe an embedding and detection process
which allows the embedding of between 2 and 8 bits in a single line of text.
For a typical 12 point document this translates to between 100 and 400
bits per page. We also perform an operational analysis to compare two
decoding methods using different embedding densities.
Digital images can be captured or generated by a variety of sources including digital cameras and scanners. In
many cases it is important to be able to determine the source of a digital image. Methods exist to authenticate
images generated by digital cameras or scanners, however they rely on prior knowledge of the image source
(camera or scanner). This paper presents methods for determining the class of the image source (camera or
scanner). The method is based on using the differences in pattern noise correlations that exist between digital
cameras and scanners. To improve the classification accuracy a feature vector based approach using an SVM
classifier is used to classify the pattern noise.
Digital images can be captured or generated by a variety of sources including digital cameras and scanners. In
many cases it is important to be able to determine the source of a digital image. This paper presents methods for
authenticating images that have been acquired using flatbed desktop scanners. The method is based on using the
pattern noise of the imaging sensor as a fingerprint for the scanner, similar to methods that have been reported
for identifying digital cameras. To identify the source scanner of an image a reference pattern is estimated for
each scanner and is treated as a unique fingerprint of the scanner. An anisotropic local polynomial estimator is
used for obtaining the reference patterns. To further improve the classification accuracy a feature vector based
approach using an SVM classifier is used to classify the pattern noise. This feature vector based approach is
shown to achieve a high classification accuracy.
KEYWORDS: Printing, Modulation, Digital watermarking, Signal processing, Signal detection, Photoresistors, Amplitude modulation, Optical proximity correction, Information security, Particles
In today's digital world securing different forms of content is very important in terms of protecting copyright and verifying authenticity. One example is watermarking of digital audio and images. We believe that a marking scheme analogous to digital watermarking but for documents is very important. In this paper we describe the use of laser amplitude modulation in electrophotographic printers to embed information in a text document. In particular we describe an embedding and detection process which allows the embedding of 1 bit in a single line of text. For a typical 12 point document, 33 bits can be embedded per page.
In today's digital world securing different forms of content is
very important in terms of protecting copyright and verifying authenticity. Many techniques have been developed to protect audio, video, digital documents, images, and programs (executable code). One example is watermarking of digital audio and images. We believe that a similar type of protection for printed documents is
very important. The goals of our work are to securely print and trace documents on low cost consumer printers such as inkjet and electrophotographic (laser) printers. We will accomplish this through the use of intrinsic and extrinsic features obtained from modelling the printing process. In this paper we describe the use of image texture analysis to identify the printer used to print a document. In particular we will describe a set of features that can be used to provide forensic information about a document. We will demonstrate our methods using 10 EP printers.
KEYWORDS: Printing, Digital watermarking, Halftones, Image processing, Signal processing, Optical proximity correction, Information security, Data hiding, Forensic science, Security printing
Despite the increase in email and other forms of digital
communication, the use of printed documents continues to increase
every year. Many types of printed documents need to be "secure"
or traceable to the printer that was used to print them. Examples
of these include identity documents (e.g. passports) and documents
used to commit a crime.
Traditional protection methods such as special inks, security
threads, or holograms, can be cost prohibitive. The goals of our
work are to securely print and trace documents on low cost
consumer printers such as inkjet and electrophotographic (laser)
printers. We will accomplish this through the use of intrinsic and
extrinsic features obtained from modelling the printing process.
Specifically we show that the banding artifact in the EP print
process can be viewed as an intrinsic feature of the printer used
to identify both the model and make of the device. Methods for
measuring and extracting the banding signals from documents are
presented. The use of banding as an extrinsic feature is also
explored.
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