Camera-identification and common-source identification: The correlation values of mismatches.

A robust and well-known way to identify the source of an image is the use of Photo Response Non-Uniformity. The ability to be able to extract the PRNU-pattern from images is both used for camera-identification (linking one or more images to a camera) and common-source identification (linking images to images). In this paper we focus on the correlation values of mismatches, i.e. the correlation between images made with different cameras. Although the correlation values of mismatches are close to zero, they are never exactly zero. In this paper we show that it is possible with an extremely simple formula to a priori estimate the typical range for mismatch correlation values. This simple formula can be used as a decision rule in digital camera identification to either perform a complete investigation including reference recordings (which is time consuming) or not. In common-source identification this simple formula can be used to provide a well-educated guess for the threshold value to the cluster algorithm instead of just arbitrarily trying a range of threshold values.

Critical review of the use and scientific basis of forensic gait analysis.

This review summarizes the scientific basis of forensic gait analysis and evaluates its use in the Netherlands, United Kingdom and Denmark, following recent critique on the admission of gait evidence in Canada. A useful forensic feature is (1) measurable, (2) consistent within and (3) different between individuals. Reviewing the academic literature, this article found that (1) forensic gait features can be quantified or observed from surveillance video, but research into accuracy, validity and reliability of these methods is needed; (2) gait is variable within individuals under differing and constant circumstances, with speed having major influence; (3) the discriminative strength of gait features needs more research, although clearly variation exists between individuals. Nevertheless, forensic gait analysis has contributed to several criminal trials in Europe in the past 15 years. The admission of gait evidence differs between courts. The methods are mainly observer-based: multiple gait analysts (independently) assess gait features on video footage of a perpetrator and suspect. Using gait feature databases, likelihood ratios of the hypotheses that the observed individuals have the same or another identity can be calculated. Automated gait recognition algorithms calculate a difference measure between video clips, which is compared with a threshold value derived from a video gait recognition database to indicate likelihood. However, only partly automated algorithms have been used in practice. We argue that the scientific basis of forensic gait analysis is limited. However, gait feature databases enable its use in court for supportive evidence with relatively low evidential value. The recommendations made in this review are (1) to expand knowledge on inter- and intra-subject gait variabilities, discriminative strength and interdependency of gait features, method accuracies, gait feature databases and likelihood ratio estimations; (2) to compare automated and observer-based gait recognition methods; to design (3) an international standard method with known validity, reliability and proficiency tests for analysts; (4) an international standard gait feature data collection method resulting in database(s); (5) (inter)national guidelines for the admission of gait evidence in court; and (6) to decrease the risk for cognitive and contextual bias in forensic gait analysis. This is expected to improve admission of gait evidence in court and judgment of its evidential value. Several ongoing research projects focus on parts of these recommendations.

Probability intervals of speed estimations from video images: The Markov Chain Monte Carlo approach.

Closed Circuit TV (CCTV) systems often record vehicle motion prior to incidents. From the footage an estimate of the average speed of the vehicle between two frames can be calculated. In a forensic investigation not only an estimate of the average speed is needed but also an estimation of the measurement error. In earlier papers an approach was explained how to estimate the average speed and the corresponding uncertainty in terms of a confidence interval. In practice confidence intervals are often wrongly interpreted as being probability intervals. In this paper we show how to use the Markov Chain Monte Carlo approach to derive probability intervals instead of confidence intervals. We show the robustness of the Markov Chain Monte Carlo approach and the numerical differences between both approaches. In casework the difference between confidence intervals and probability intervals turns out to be very limited. As a consequence the impact of confusion between confidence and probability intervals can also be expected to be limited.

Application of forensic image analysis in accident investigations.

Forensic investigations are primarily meant to obtain objective answers that can be used for criminal prosecution. Accident analyses are usually performed to learn from incidents and to prevent similar events from occurring in the future. Although the primary goal may be different, the steps in which information is gathered, interpreted and weighed are similar in both types of investigations, implying that forensic techniques can be of use in accident investigations as well. The use in accident investigations usually means that more information can be obtained from the available information than when used in criminal investigations, since the latter require a higher evidence level. In this paper, we demonstrate the applicability of forensic techniques for accident investigations by presenting a number of cases from one specific field of expertise: image analysis. With the rapid spread of digital devices and new media, a wealth of image material and other digital information has become available for accident investigators. We show that much information can be distilled from footage by using forensic image analysis techniques. These applications show that image analysis provides information that is crucial for obtaining the sequence of events and the two- and three-dimensional geometry of an accident. Since accident investigation focuses primarily on learning from accidents and prevention of future accidents, and less on the blame that is crucial for criminal investigations, the field of application of these forensic tools may be broader than would be the case in purely legal sense. This is an important notion for future accident investigations.

Common source identification of images in large databases.

Photo-response non-uniformity noise patterns are a robust way to identify the source of an image. However, identifying a common source of images in a large database may be impractical due to long computation times. In this paper a solution for large volume digital camera identification is proposed, which combines, and sometimes slightly modifies, existing methods for a 500 times improvement in the speed of common source identification. Single image comparisons are often plagued by considerable noise contamination from scene content and random noise, which makes it harder to accomplish reliable common source identification. Therefore a new method is introduced that can increase true positive rates by more than 45% at very low computation costs. Analysis of real data from a fraud case shows the effectiveness of the proposed method. As a whole the proposed solution makes it possible to analyze a large database in forensically relevant time, without resorting to large and expensive computer clusters.

Fundamental spatial resolution of an x-ray pore optic.

We investigate the fundamental spatial resolution of an x-ray pore optic as a function of the pore dimensions, the photon energy, and the focal length. We achieve this by calculating the shape of the focal spot, using diffraction integrals such that the half-energy width is determined. Quantitative results are presented for the X-Ray Evolving Universe Spectroscopy (XEUS) telescope, showing that a resolution of better than 2 arc sec half-energy width is possible by use of an optic with pore sizes of approximately 0.5 mm.

Deep nulling by means of multiple-beam recombination.

Direct detection of exoplanets is possible by use of a technique called nulling interferometry, which is based on destructive interference of light of the bright object and constructive interference of the faint object. In the infrared wavelength region, this implies that light of a star must be attenuated by a certain factor, the so-called rejection ratio, which typically equals 10(6). This can be achieved by use of phase shifters, which apply a phase shift of pi rad with an average error nogreater than 2 mradover a predefined wavelength region. For a 6-18-microm wavelength interval, this is a tough constraint. We show that the 2-mrad constraint can be relaxed if more than two beams participate in the beam recombination. We focus our attention on dispersive phase shifters and show that rejection ratios beyond 10(6) can be reached easily by use of a system of four or more apertures and simple dispersive phase shifters that consist of only one material.

Nulling interferometry without achromatic phase shifters.

In the infrared wavelength region, a typical star is approximately a million times brighter than the planet that surrounds it, which is a major problem when we attempt to detect exoplanets in a direct manner. Nulling interferometry is a technique that one can use to solve this problem by attenuating the stellar light and enhancing that of the planet. Generally, deep nulling is achieved by use of achromatic phase shifters (APSs). Unfortunately, the technology needed to build these APSs is not yet fully developed. We show that deep nulling can also be achieved by using delay lines only. We investigate the nulling depth as a function of the width of the wavelength interval and the number of telescopes. We also show that we can obtain nulling depths of less than 10(-6), which are required for exoplanet detection. Furthermore, we investigate the properties of the transmission map and make a comparison between our system and an APS system.