In the above titled paper (ibid., vol. 4, no. 4, pp. 611-627, Dec. 09), due to a production error, the affiliations of two of the authors were listed incorrectly. The correct affiliations are presented here. Also, the name of the last author in the affiliations footnote was printed incorrectly. The correct name is P. Y. A. Ryan.

Scantegrity II is an enhancement for existing paper ballot systems. It allows voters to verify election integrity - from their selections on the ballot all the way to the final tally - by noting codes and checking for them online. Voters mark Scantegrity II ballots just as with conventional optical scan, but using a special ballot marking pen. Marking a selection with this pen makes legible an otherwise invisible preprinted confirmation code. Confirmation codes are independent and random for each potential selection on each ballot. To verify that their individual votes are recorded correctly, voters can look up their ballot serial numbers online and verify that their confirmation codes are posted correctly. The confirmation codes do not allow voters to prove how they voted. However, the confirmation codes constitute convincing evidence of error or malfeasance in the event that incorrect codes are posted online. Correctness of the final tally with respect to the published codes is proven by election officials in a manner that can be verified by any interested party. Thus, compromise of either ballot chain of custody or the software systems cannot undetectably affect election integrity. Scantegrity II has been implemented and tested in small elections in which ballots were scanned either at the polling place or centrally. Preparations for its use in a public sector election have commenced.

The 13 papers in this special issue focus on electronic voting.

Random data perturbation (RDP) has been in use for several years in statistical databases and public surveys as a means of providing privacy to individuals while collecting information on groups, and has recently gained popularity as a privacy technique in data mining. This correspondence provides an information-theoretic framework for all inference attacks on RDP. The framework is used to demonstrate the existence of a tight asymptotic lower bound on the number of queries required per bit of entropy for all inference attacks with zero asymptotic error and bounded average power in the query sequence. A privacy measure based on security against inference attacks is proposed.

A coding theory framework for related-key linear cryptanalytic attacks on block ciphers is presented. It treats linear cryptanalysis as communication over a low capacity channel, and a related key attack (RKA) as a concatenated code. It is used to show that an RKA, using n related keys generated from k independent ones, can improve the amortized cost - in number of plaintext-ciphertext pairs per key bit determined over that of k single key attacks, of any linear cryptanalysis, if k and n are large enough. The practical implications of this result are demonstrated through the design of an RKA, with k=5 and n=7, predicted to produce a 29% improvement for DES attacks that use an r-1 round approximation

Counterfeiting of valuable documents is an increasingly serious problem. Banknotes, drivers licenses, passports, diplomas and stock certificates are all the subjects of increasingly frequent and accurate counterfeiting efforts. This is in part due to the performance improvements of consumer inkjet printers. Design features which required great labor and skill to reproduce on an engraved-plate printing process pose essentially no difficulty to a counterfeiter armed with an accurate scanner and high-resolution color printer. We show how simple changes in banknote design coupled with possible changes in rendering engines can make the task of counterfeiting enormously more difficult.

We formalize ideas of orthogonality and inner products implicit in the development of a number of figures of merit (FOM) of color recording filters. We show that, in negligible measurement noise, the data dependence of each FOM based on linear color correction is equivalent to a choice of inner product (and hence of orthogonality). Further, we show that optimal sensors with respect to noise sensitivity are simply defined as orthogonal with respect to this inner product. We also develop the idea of a generalized Q-factor by generalizing the Euclidean inner product to include all inner products. Simulations demonstrate the utility of our analytical results.

This paper describes the design and performance of an image capture simulator. The general model underlying the simulator assumes that the image capture device contains multiple classes of sensors with different spectral sensitivities and that each sensor responds in a known way to irradiance over most of its operating range. The input to the simulator is a set of narrow-band images of the scene taken with a custom-designed hyperspectral camera system. The parameters for the simulator are the number of sensor classes, the sensor spectral sensitivities, the noise statistics and number of quantization levels for each sensor class, the spatial arrangement of the sensors and the exposure duration. The output of the simulator is the raw image data that would have been acquired by the simulated image capture device. To test the simulator, we acquired images of the same scene both with the hyperspectral camera and with a calibrated Kodak DCS-200 digital color camera. We used the simulator to predict the DCS-200 output from the hyperspectral data. The agreement between simulated and acquired images validated the image capture response model and our simulator implementation. We believe the simulator will provide a useful tool for understanding the effect of varying the design parameters of an image capture device.

A color correction matrix is usually used to transform the raw color image obtained from color image sensors to adjust for factors such as variations in illumination and deviations of the actual filter characteristics from the ideal. Color correction matrices that have high condition numbers can greatly amplify noise, while it can be difficult to achieve good color saturation with low condition number matrices. Noise can be a significant problem for digital camera images which have limited bit-depth. We explore the trade-off between noise reduction and color saturation analytically, and using digital camera images. We present an orthonormality criterion to define optimality with respect to noise sensitivity and color saturation in the case of signal-independent, orthogonal sensor measurement noise in each color channel.

The problem of the design of color scanning filters is addressed in this paper. The problem is posed within the framework of the vector space approach to color systems. The measure of the goodness of a set of color scanning filters presented in earlier work is used as an optimization criterion to design color scanning filters modeled in terms of known, smooth, nonnegative functions. The best filters are then trimmed using the gradient of the mean square DeltaE(ab) error to obtain filters with a lower value of perceptual error. The results obtained demonstrate the utility of the method.

The problem of the sensitivity analysis of color scanning filters is addressed in this paper. The second differential of the mean square DeltaE(ab) error provides a means of calculating the sensitivity of the mean square DeltaE(ab) error to filter fabrication errors. Tolerances on the allowable change in the mean square DeltaE(ab) error are used to define bounds on the filter fabrication errors at all wavelengths and at single wavelengths.

The reconstruction of an image from incomplete view data requires the use of several constraints not derived from ray sum (projection data) measurements. The constraints can be incorporated through the method of (sequential and parallel) projections onto the constraint sets. These methods for the use of information regarding the noise and the image are implemented and compared. It is shown that the use of noise statistics decreases the mean square error in the image and that the method of parallel projections results in smaller error than the method of sequential projections if a sufficient number of iterations is permitted.

In order to reproduce perceived color accurately the three bands of a color image must be obtained using sensors whose relative spectral sensitivity satisfies certain constraints. These constraints, the design of filters which satisfy these constraints, and the effect of inaccuracies in the sensors' response are discussed. The mathematical techniques used for the error analysis have not been used previously in color scanning filter design. The results of this study are applicable to most color systems, including television, lithography, copiers and printers.>

A theoretical bound on the improvement possible due to knowledge of signal points, for the case of a Gaussian signal in Gaussian noise, has been calculated. Wiener and projections-onto-convex-sets restorations have been computed both with and without knowledge of the known points. The estimation errors are compared for different noise levels and blurs, and different numbers of known points.>