This PDF file contains the front matter associated with SPIE Proceedings Volume 7119, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and the Conference Committee listing.

Designers of medium and high performance optical systems often overlook a very simple technique that can improve the system transmission and image contrast, as well as reduce scattering within the system. The resulting improvement in the optical collection efficiency can be used to increase performance or be traded off to realize improvements in other areas (i.e. aperture size, weight, etc.). The technique is based on the observation that many (if not most) anti-reflection coatings specified for lens surfaces, are specified at a normal angle of incidence. Since most of the energy incident on a typical lens impinges at angles other than the normal, the efficiency of an anti-reflection coating at any surface might be improved by using an approach based on weighted average angles of the incident radiation. This paper describes one approach to calculate weighted average coating angles for a optical systems. The optical transmissions are estimated, when the respective coatings are specified at the normal angle of incidence and at an angle based on the incident ray geometry. The measured transmission of two (otherwise identical) aspheric lenses, one coated using a standard SLAR coating specified at a normal incidence angle and the other coated using a standard SLAR coating specified at optimized incidence angles are presented.

It is well known that the quality of imagery captured by electro-optic cameras is degraded by atmospheric turbulence. This is especially true for horizontal path surveillance in challenging military environments (i.e. within 3m of the ground) where atmospheric turbulence is known to severely affect image quality. The acquisition ranges for even long range cameras can reduce from a few kilometres to less than 100 metres. In order to arrive at a solution that may be deployed in operationally significant scenarios, video imagery captured in these conditions was analysed. It became apparent that conventional civilian adaptive optics is not robust enough for generic military imaging. Therefore a pragmatic approach has been developed to lead to the design of a lens system that incorporates adaptive optics that may be used in challenging military scenarios.

The paper intends to show that Applied Multidimensional Fusion will bring the benefits that data fusion and related techniques will bring to Urban Intelligence Surveillance Target Acquisition and Reconnaissance (ISTAR) systems. In the course of this work it has been shown through the practical application of some of the multi-dimensional fusion research in the United Kingdom. This paper highlights work done in the area of: super-resolution, joint fusion, multi-resolution target detection and identification, and task based image and video fusion assessment. Work done to date has produced practical pertinent research products with direct applicability to the problems posed.

Iris recognition is an increasingly popular biometric due to its relative ease of use and high reliability. However, commercially available systems typically require on-axis images for recognition, meaning the subject is looking in the direction of the camera. The feasibility of using off-axis images is an important area of investigation for iris systems with more flexible user interfaces. The authors present an analysis of two image transform processes for off-axis images and an analysis of the utility of correcting for cornea refraction effects. The performance is assessed on the U.S. Naval Academy iris image database using the Ridge Energy Direction recognition algorithm developed by the authors, as well as with a commercial implementation of the Daugman algorithm.

The Imagery Library for Intelligent Detection Systems (i-LIDS) is the UK government's standard for Video Based Detection Systems (VBDS). The Home Office Scientific Development Branch (HOSDB) in partnership with the Centre for the Protection of National Infrastructure (CPNI) has now developed a fifth i-LIDS Scenario; Multiple Camera Tracking (MCT). The imagery contains various staged events of people walking through the camera views. A bounding box Ground Truth is provided with the imagery. A metric has been developed by HOSDB for evaluation of systems. The metric is based on precision and recall system output compared to the ground truth.

This paper focuses on how an object, such as pedestrians, can be spotted, recognised and then subsequently tracked without prior information. Rather than using conventional sliding window techniques for target/object detection, a biological-like bottom-up neural system, similar to that of human's visual perception, has been adopted for selecting the region of interest (ROI) according to the salience and relevance of the scene. Subsequently, a cortex-like feed forward object recognition mechanism is employed for categorising objects in the ROI into pedestrian and non-pedestrian classes. The result is demonstrated using a video track and the flexibility and efficiency of this biological approach for surveillance application is commented.

Moving shadow detection is an important step in automated robust surveillance systems in which a dynamic object is to be segmented and tracked. Rejection of the shadow region significantly reduces the erroneous tracking of non-target objects within the scene. A method to eliminate such shadows in indoor video sequences has been developed by the authors. The objective has been met through the use of a pixel-wise shadow search process that utilizes a computational model in the RGB colour space to demarcate the moving shadow regions from the background scene and the foreground objects. However, it has been observed that the robustness and efficiency of the method can be significantly enhanced through the deployment of a binary-mask based shadow search process. This, in turn, calls for the use of a prior foreground object segmentation technique. The authors have also automated a standard foreground object segmentation technique through the deployment of some popular statistical outlier-detection based strategies. The paper analyses the performance i.e. the effectiveness as a shadow detector, discrimination potential, and the processing time of the modified moving shadow elimination method on the basis of some standard evaluation metrics.

Presented in this paper is a detailed novel approach to tracking multiple moving targets from multiple moving platforms and fusing the individual estimates within platform centric nodes via covariance intersection. The approach presents a method of deconstructing the target model into a nonlinear element and a Kalman Filter, modelling the target position and velocity vectors of the targets. The method avoids the increased complexity of using Extended Kalman Filters. The model state noise covariance is restructured by considering the source of the noise within the simplified imposed model and the measurement noise covariance is estimated from a single coefficient optimized moving average filter. The filter coefficient is optimally determined by the minimization of the variance of the Frobenius norm of the current estimated measurement covariance matrix, via a fuzzy logic feedback structure.

The wakes of ships and small surface craft such as fast inshore attack craft (FIAC) can provide crucial intelligence about their behaviour. The development of image processing algorithms to automatically extract this information from surveillance imagery represents a challenging task, but one which can provide great benefits for naval security. This paper reports on research into novel wake detection and analysis techniques to improve the security of naval vessels and harbour environments, and demonstrates the results of novel methods for extracting the positions, heading, size and speed of a vessel from imagery through an analysis of these wake components. The wakes of small surface craft are typically many times larger than the vessel itself and therefore yield a more robust method for detection. Consequently, this detection technique can be successful even when the vessel is unresolved. These methods can be used to track the vessels and examine their paths to determine their behaviour. This is achieved through the use of Waterfall Solutions Ltd's (WS) existing tracking techniques and the development of novel anomaly detection methods. The work demonstrates the ability to extract vessel properties and infer behaviour from their wakes, which is beneficial in determining the vessel's degree of threat and intent.

Advanced multispectral, or hyperspectral, camera systems are being used to identify objects of interest on the basis of spectral characteristics. This paper will describe developments in the field of a real time spectral matched filtering. Matched filtering relies on there being a measurable difference between the spectrum of the target and that of background materials such as soil, vegetation, concrete and tarmac. If prior knowledge is available then the target can be found by matching the two spectra numerically. Previous work has identified the most robust and effective matched filtering technique. Software has been written to interface with a pushbroom hyperspectral sensor to enable fast spectrally tracking of objects. False alarms have been reduced by means of additional processing. Example detections of a number of unclassified objects will be presented.

This paper presents an algorithm for aligning 2D video to 3D point clouds. The paper is a vignette of on-going research in the area of 3D Urban Environment Modelling. The aim of this research is to produce accurate, fast and useable 3D maps of the dynamic urban environment. Paper presents development of the algorithm followed by the processing and implementation procedure to produce a realistic 3D model of an urban environment model from 3D point cloud and RGB video collected by the system. To allow further discussion the paper concludes with the results of draping 2D video frames to a solid surface developed from 3D point clouds.

Nanoparticles appear in several areas of forensic science including security documents, paints, inks, and reagents that develop latent prints. One reagent (known as the silver physical developer) that visualizes the water insoluble components of latent print residue is based on the formation of highly charged silver nanoparticles. These attach to and grow on the residue and generate a silver image. Another such reagent involves highly charged gold nanoparticles. These attach to the residue forming a weak gold image which can be amplified with a silver physical developer. Nanoparaticles are also used in items such as paints, printing inks, and writing inks. Paints and most printing inks consist of nano-sized pigments in a vehicle. However, certain modern ink jet printing inks now contain nano-sized pigments to improve their light fastness and most gel inks are also based on nano scale pigments. These nanoparticlecontaining materials often appear as evidence and are thus subject to forensic characterization. Both luminescent (quantum dots), up-converting nano scale phosphors, and non luminescent nanoparticles are used as security tags to label product, add security to documents, and as anti counterfeiting measures. These assist in determining if an item is fraudulently made.

The nuclear aspect of the CBRN* threat is often divided amongst radiological substances posing no criticality risk, often referred to as 'dirty bomb' scenarios, and fissile threats. The latter have the theoretical potential for criticality excursion, resulting in elevated neutron fluxes in addition to the &ggr;-ray component that is common to dirty bombs. Even in isolation of the highly-unlikely criticality scenario, fissile substances often exhibit radiation fields comprising a significant neutron component which can require considerably different counterterrorism measures and clean-up methodologies. The contrast between these threats can indicate important differences in the relative sophistication of the perpetrators and their organizations. Consequently, the detection and discrimination of nuclear perils in terms of mixed-field content is an important assay in combating terrorist threats. In this paper we report on the design and implementation of a fast digitizer and embedded-processor for onthe- fly signal processing of events from organic liquid scintillators. A digital technique, known as Pulse Gradient Analysis (PGA), has been developed at Lancaster University for the digital discrimination of neutrons and &ggr; rays. PGA has been deployed on bespoke hardware and demonstrates remarkable improvement over analogue methods for the assay of mixed fields and the real-time discrimination of neutrons and &ggr; rays. In this regard the technology constitutes an attractive and affordable means for the discrimination of the radiation fields arising from fissile threats and those from dirty bombs. Data are presented demonstrating this capability with sealed radioactive sources.

Results are presented on the development of a portable detector suitable for detection of individual thermal neutrons. The device is based on direct absorption of neutrons in an absorber film containing 10B. The resultant charge arising from the capture products is detected by a p-n junction partly formed from this absorber and internal to the device. When a small bias voltage is applied (typically a few volts) a current pulse is observed due to the movement of this charge in the electric field of the p-n junction. For each detected neutron the charge pulse height, rise time and time of detection are recorded. Device performance, in terms of efficiency and spectral response, is explored as a function of neutron absorber thickness, geometry and overall diode electrical characteristics and validated against neutron source measurements at the UK National Physical Laboratory (NPL). The diodes have a natural background suppression capability through traditional pulse height and pulse rise time discrimination. The manufacturing process permits fabrication of arrays of diodes, with typical areas of ~15 mm2, thus increasing the collecting area and the signal to noise ratio, albeit with increased readout complexity. The associated multi-channel readout electronics is standard, however, and commonly used in existing X-ray sensors. Simple portable sensors based on these heterodiodes are expected to have applications in the detection of nuclear materials in a variety of security related situations.

A low cost technique is reported for the rapid screening of containers for materials that potentially could be used for terrorist activities. For peroxide based samples it is demonstrated that full characterisation can be achieved in a continuous curve fitting monitoring mode acquiring up to 10 spectra per second. This clearly demonstrates the potential for a Raman based method to be incorporated into a check-point whilst retaining fast throughput. A number of precursor compounds to nerve agents and peroxide and nitrate based improvised explosive materials have been studied. The potential strengths and weaknesses of using Raman for multiple target identification are discussed with regard to the common vibrations associated with each group of agents. Within this context we also introduce the use of fast Raman line mapping into the trace analysis of multiple component targets. The method presented is suited to volatile or light sensitive samples (such as derived peroxides) and can be employed on a variety of surfaces. As speed and throughput are traded against spectral bandwidth categorising threat compounds into groups based on common functionalities allows the full potential for multiplexed targeting to be realised.

A major challenge confronting first responders, customs authorities and other security-related organisations is the accurate, rapid, and safe identification of potentially hazardous chemicals outside a laboratory environment. Currently, a range of hand portable Raman equipment is commercially available that is low cost and increasingly more sophisticated. These systems are generally based on the 785nm Stokes shifted Raman technique with many using dispersive grating spectrometers. This technique offers a broad range of capabilities including the ability to analyse illicit drugs, explosives, chemical weapons and pre-cursors but still has some fundamental constraints. 'Real world' samples, such as those found at a crime scene, will often not be presented in the most accessible manner. Simple issues such as glass fluorescence can make an otherwise tractable sample impossible to analyse in-situ. A new generation of portable Raman equipment is currently being developed to address these issues. Consideration is given to the use of longer wavelength for fluorescence reduction. Alternative optical designs are being tested to compensate for the signal reduction incurred by moving to longer wavelengths. Furthermore, the use of anti-Stokes spectroscopy is being considered as well as investigating the robustness and portability of traditional Fourier Transform interferometer designs along with future advances in detector technology and ultra small spectrometers.

The type of explosive materials used in terrorist activities has seen a gradual shift from those that are commonly manufactured but difficult to obtain, such as trinitrotoluene (TNT) and nitroglycerine (NG), to improvised explosive devices (IEDs) made from substances that are more readily available. This shift has placed an emphasis on development of instruments capable of detecting IEDs and their precursors, which are often small, volatile molecules well suited to detection through mid-infrared absorption spectroscopy. Two such examples are ammonia, a breakdown product of ammonium nitrate and urea nitrate, and hydrogen peroxide, an efficient oxidiser used in the production of triacetone triperoxide (TATP) and hexamethyl triperoxide diamine (HMTD). At this meeting in 2007 we presented results of a hydrogen peroxide detection portal utilising quantum cascade laser (QCL) technology. This trace detection system has since undergone significant development to improve sensitivity and selectivity, and the results of this will be presented alongside those of a similar system configured for bulk detection of ammonia. Detection of ammonia produced from the breakdown of ammonium nitrate has been demonstrated, both on the optical bench and in a walkthrough portal. This research has been supported by the UK government.

The ultimate goal in all fiber optic systems is to extract information about the mechanical perturbations. For example, this information may be the frequency dependent index of perturbation. For security systems we desire to detect and differentiate between different intruders based on the mechanical response. This article shows experimental investigation of ideal intruder classifier. We considered demodulation, denoising, deconvolution and normalisation. We present additionally possible configuration of fiber optic sensor to localizing perturbation place.

This paper presents a fast and robust approach to surface creation and feature extraction. The methodology is based on segmentation of point clouds iteratively till a set bound is reached. This paper concentrates on developing the methodology for developing planar surfaces. To achieve this goal vegetation is filtered and planar surfaces are created using the Delaunay triangulation. Surface creation process uses segmented point clouds based on fluctuation of normal of the surfaces in the segmented cubes. Results produced using this technique show the effect of imposing geometric constraints on the reconstruction to generate realistic surfaces.

A new algorithm is suggested to visualize the dynamics of medium response spectrum in terahertz diapason by the singly measured set of partially intersected integral characteristics of the signal. The algorithm is based on SVD method and window sliding method. The analysis, we carried out, demonstrates many advantages of the new algorithm in com-parison with the Gabor-Fourier approach, which allows obtaining the dynamics of only one spectral line for one set of measurements. Among which it is necessary to mention the possibility to get the dynamics of many spectral components simultaneously for one set of measurements as well and therefore to get the complete information about the spectrum dynamics. This allows to identify specific materials with known spectral lines and to distinguish materials with similar spectra, which is of great importance for the detection and identification of different chemicals, pharmaceutical substances and explosives. To demonstrate the efficiency of a proposed algorithm, we compare spectrum dynamics of chocolate and soap, which possess the similar spectra. Our investigation shows that their dynamics widely vary in spec-tral lines. The proposed algorithm can be also applied to voice identification and to reconstruction of a laser beam profile with a great number of local maxima. Developed algorithm allows to measure the characteristic time of medium responce. It is very important for various problems of spectroscopy.