Wavelets are a powerful tool that can be applied to problems in image processing and analysis. They provide a multi-scale
decomposition of an original image into average terms and detail terms that capture the characteristics of the image at
different scales. In this project, we develop a figure of merit for macro-uniformity that is based on wavelets. We use the
Haar basis to decompose the image of the scanned page into eleven levels. Starting from the lowest frequency level, we
group the eleven levels into three non-overlapping separate frequency bands, each containing three levels. Each frequency
band image consists of the superposition of the detail images within that band. We next compute 1-D horizontal and
vertical projections for each frequency band image. For each frequency band image projection, we develop a structural
approximation that summarizes the essential visual characteristics of that projection. For the coarsest band comprising
levels 9,10,11, we use a generalized square-wave approximation. For the next coarsest band comprising levels 6,7,8, we
use a piecewise linear spline approximation. For the finest bands comprising levels 3,4,5, we use a spectral decomposition.
For each 1-D approximation signal, we define an appropriate set of scalar-valued features. These features are used to
design two predictors one based on linear regression and the other based on the support vector machine, which are trained
with data from our image quality ruler experiments with human subjects.
Assessment of macro-uniformity is a capability that is important for the development and manufacture of printer
products. Our goal is to develop a metric that will predict macro-uniformity, as judged by human subjects, by
scanning and analyzing printed pages. We consider two different machine learning frameworks for the metric:
linear regression and the support vector machine. We have implemented the image quality ruler, based on the
recommendations of the INCITS W1.1 macro-uniformity team. Using 12 subjects at Purdue University and
20 subjects at Lexmark, evenly balanced with respect to gender, we conducted subjective evaluations with a
set of 35 uniform b/w prints from seven different printers with five levels of tint coverage. Our results suggest
that the image quality ruler method provides a reliable means to assess macro-uniformity. We then defined
and implemented separate features to measure graininess, mottle, large area variation, jitter, and large-scale
non-uniformity. The algorithms that we used are largely based on ISO image quality standards. Finally, we used
these features computed for a set of test pages and the subjects' image quality ruler assessments of these pages
to train the two different predictors - one based on linear regression and the other based on the support vector
machine (SVM). Using five-fold cross-validation, we confirmed the efficacy of our predictor.
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.
This paper investigates the performance and proposes modifications to earlier methods for image authentication
using distributed source coding. This approach works well on images that have undergone affine geometric
transformations such as rotation and resizing and intensity transformations such as contrast and brightness
adjustment. The results show that the improvements proposed here can be used to make the original scheme for
image authentication robust to affine geometric and intensity transformations. The modifications are of much
lesser computational complexity when compared with other schemes for estimation of channel parameters.
Digital images can be obtained through a variety of sources including digital cameras and scanners. With rapidly
increasing functionality and ease of use of image editing software, determining authenticity and identifying forged
regions, if any, is becoming crucial for many applications. This paper presents methods for authenticating and
identifying forged regions in images that have been acquired using flatbed scanners. The methods are based on
using statistical features of imaging sensor pattern noise as a fingerprint for the scanner. An anisotropic local
polynomial estimator is used for obtaining the noise patterns. A SVM classifier is trained for using statistical
features of pattern noise for classifying smaller blocks of an image. This feature vector based approach is shown
to identify the forged regions with high accuracy.
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. 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.
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.
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 atomic force microscopy, a 3-D image of a substrate is obtained. With the total number of samples remains constant, there is a trade-off between the size of the scanned image and the resolution. For the scanning mechanism, the time needed to image an area depends mainly on the number of samples and the size of the image. It is desirable to improve the imaging speed with limited impact to the effective resolution of the portion of the substrate that is of interested. To improve the imaging speed, there are two options: 1) increase the data process rate or 2) reduce the amount of data. One key issue for reducing the amount of data is to maintain acceptable image fidelity. To address this issue, we need to classify the sample area into regions based on importance. For high importance regions, a higher resolution is needed. For regions of less importance, a coarse sample density is employed. In this study, we propose a new adaptive sampling scheme that is leveraged from image compression. By adapting the sampling resolution to the substrate profile, the proposed method can decrease the scanning time by reducing the amount of data while maintaining the desired image fidelity.
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.
INCITS W1 is the U.S. representative of ISO/IEC JTC1/SC28, the standardization committee for office equipment. In September 2000, INCITS W1 was chartered to develop an appearance-based image quality standard. The resulting W1.1 project is based on a proposal that perceived image quality could be described by a small set of broad-based attributes. There are currently five ad hoc W1.1 teams, each working on one or more of these image quality attributes. This paper summarizes the work of the W1.1 Microuniformity ad hoc team. The agreed-upon process for developing the W1.1 Image Quality of Printers standards is described in a statement located on the INCITS W1.1 web site (ncits.org/tc_home/w11htm/incits_w11.htm), and the process schematic is reproduced here as Figure 1, (in which a final, independent confirmation step has been excluded for brevity).
Adaptive tuned vibration absorbers for attenuation of harmonic vibration may be realized through the use of active materials in absorber designs. For example, the variable elastic modulus of shape memory alloy may be used to incorporate variable springs in an absorber, such that the absorber natural frequency may be on-line tuned. The difficulty then becomes the control of the tuned condition of the absorber. One method for controlling the tuned condition of the absorber is to drive the relative phase between the primary system and the absorber to a desired value. The classical phase-locked loop is one method that might be used to achieve this control goal. An alternative method is to utilize a simple PI controller that uses the relative phase as an error signal. The map between the control input to the active material elements and the resulting relative phase can be modeled as a first-order linear system in series with a static nonlinearity with certain characteristics. This paper presents an analysis of the stability of the phase tracking of an adaptive tuned vibration absorber made of active material. The necessary characteristics for the map between the control signal and the resulting relative phase are presented. A control algorithm is developed that results in asymptotic stability of the system in the presence of an uncertain fixed excitation frequency. Results of implementation of an experimental ATVA on a primary system are presented.
KEYWORDS: Shape memory alloys, Control systems, Device simulation, Signal attenuation, Vibration control, Data acquisition, Temperature metrology, Power supplies, Current controlled current source, Nonlinear filtering
Controlled continuous tuning of the stiffness of shape memory alloy (SMA) spring elements of an adaptively tunable vibration absorber (ATVA) is a novel concept for adaptive-passive vibration control. Minimization of the vibration of a primary system is achieved indirectly via stiffness control of the SMA structural elements supporting a secondary mass. Stiffness control is further achieved via the heating of the SMA elements. In this paper a control law to achieve phase- tracking by controlling the heating of the SMA elements is developed and implemented. Successful analytical and experimental results demonstrate the feasibility of continuous control of the SMA ATVA. Performance of the SMA ATVA is compared to the performance of comparable passive tuned vibration absorbers (TVA). The comparison shows that substantial improvements in vibration attenuation can be achieved through the implementation of the SMA ATVA.
The passive-adaptive approach to vibration control shows promise in its ability to combine the robust stability and low-complexity of passive tuned absorbers with the adaptability of active control schemes. Previous tunable vibration absorbers have been complex and bulky. Shape memory alloys (SMA) with their variable material properties, offer an alternative adaptive mechanism. Heating an SMA causes a change in the elastic modulus of the material by a factor as high as three. Incorporating SMA in parallel with traditional spring materials creates an absorber with a variable spring stiffness and a corresponding variable tuning frequency. Using on-off actuation of the SMA, discrete frequencies of tuning are obtained through the use of multiple SMA elements.
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