This PDF file contains the front matter associated with SPIE Proceedings Volume 7486, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

Polymerization of the volatile sulfur nitride S₂N₂ can be brought about by interaction with latent fingerprint residues, with the resulting dark blue black polymer (SN)x visually developing the prints on a large range of media. Consideration of the technical and safety requirements of the technique allows an effective apparatus to be built and utilized with minimal risk. Observations on the diversity of media involved highlights the power of the technique, though results also indicate that no simple mechanism can account for all aspects of the interactions between the nitride, the prints and the media surfaces. This is especially apparent when prints on paper or plastic can still be imaged after washing with either water or organic solvents; likewise prints on aluminium foil can be imaged even after being heated to 500°C overnight.

The unique optical properties associated with nanostructured materials that support the excitation of surface plasmons offer many new opportunities for the enhanced optical investigation of biological materials that pose a security threat. In particular, ricin is considered a significant bioterrorism risk due to its high toxicity combined with its ready availability as a byproduct in castor oil production. Therefore, the development of optical techniques capable of rapid on-site toxin detection with high molecular specificity and sensitivity continues to be of significant importance. Furthermore, understanding of the ricin cell entry and intracellular pathways remains poor due to a lack of suitable bioanalytical techniques. Initial work aimed at simultaneously tackling both these issues is described where different approaches for the nanoparticle labeling of ricin are investigated along with changes in ricin toxicity associated with the labeling process.

Emotional or physical stresses induce a surge of adrenaline in the blood stream under the command of the sympathetic nerve system, which, cannot be suppressed by training. The onset of this alleviated level of adrenaline triggers a number of physiological chain reactions in the body, such as dilation of pupil and an increased feed of blood to muscles etc. This paper reports for the first time how Electro-Optics (EO) technologies such as hyperspectral [1,2] and thermal imaging[3] methods can be used for the detection of stress remotely. Preliminary result using hyperspectral imaging technique has shown a positive identification of stress through an elevation of haemoglobin oxygenation saturation level in the facial region, and the effect is seen more prominently for the physical stressor than the emotional one. However, all results presented so far in this work have been interpreted together with the base line information as the reference point, and that really has limited the overall usefulness of the developing technology. The present result has highlighted this drawback and it prompts for the need of a quantitative assessment of the oxygenation saturation and to correlate it directly with the stress level as the top priority of the next stage of research.

Three dimensional (3D) face recognition is a topic getting increasing interest in biometric applications. In our research framework we developed a laser scanner that provides 3D cloud information and texture data. In a user scenario with cooperative subjects with indoor light conditions, we address three problems of 3D face biometrics: the face registration, the formulation of a shape space together with a special designed gradient algorithm and the impact of initial approximation to the convergence of a registration algorithm. By defining the face registration as a problem of aligning a 3D data cloud with a predefined reference template, we solve the registration problem with a second order gradient algorithm working on a shape space designed for reducing the computational complexity of the method.

Following the development of point sensing improvised explosive device (IED) technology[1] Cascade Technologies have initial work in the development of equivalent stand-off capability. Stand-off detection of IEDs is a very important technical requirement that would enable the safe identification and quantification of hazardous materials prior to a terrorist attack. This could provide advanced warning of potential danger allowing evacuation and mitigation measures to be implemented. With support from the UK government, Cascade Technologies is currently investigating technology developments aimed at addressing the above stand-off IED detection capability gap. To demonstrate and validate the concept, a novel stand-off platform will target the detection and identification of common high vapor pressure IED precursor compounds, such as hydrogen peroxide (H2O2), emanating from a point source. By actively probing a scene with polarized light, the novel platform will offer both enhanced selectivity and sensitivity as compared to traditional hyperspectral sensors, etc. The presentation will highlight the concept of this novel detection technique as well as illustrating preliminary results.

A method of THz spectral dynamics analysis (SDA) of medium response in the THz and GHz ranges, which was developed by us in previous papers for detection and identification of materials, is used for the treatment of experimentally measured signals, passed through selected explosives, including those hidden under covering materials. This technique is based on the window sliding method and on restoration of the THz pulse. It allows researchers to follow the dynamics of many spectral lines in one set of measurements simultaneously and to obtain the full information about the spectrum dynamics of the THz pulse. Relaxation time of rotational transitions, for example, can be determined too. This information gives an opportunity to detect and identify materials despite the similarity in their THz spectra-which may be identical. We show that the spectrum dynamics of THz pulses, passed through the explosives hidden under plastic, cotton and leather barriers-covers, differ widely for these media despite little difference in their spectra. Consequently, our method allows for detection and identification of the hidden explosives with high probability.

We present the detection of liquid explosive precursor mixtures through diffusely scattering and fluorescing bottles and packaging. Spatially Offset Raman Spectroscopy (SORS) is a recently developed Raman spectroscopic method capable of non-invasively interrogating diffusely scattering containers. When compared with conventional Raman, a substantially enhanced sensitivity is achieved by the technique's inherent ability to effectively suppress fluorescence and Raman contributions originating from the wall of the container. The measurements presented here focus on challenging mixtures of hydrogen peroxide solution, a critical component of a number of liquid explosives, with highly absorbing or fluorescing beverages and creams, in which liquid explosive precursors could potentially be concealed. The method enabled the detection of concealed hydrogen peroxide solution in all the studied cases.

Standoff detection, identification and quantification of chemical agents are fundamental needs in several fields of applications. Additional required sensor characteristics include high sensitivity, low false alarms and high-speed (ideally real-time) operation, all in a compact and robust package. The thermal infrared portion of the electromagnetic spectrum has been utilized to implement such chemical sensors, either with spectrometers (with none or moderate imaging capability) or with imagers (with moderate spectral capability). Only with the recent emergence of high-speed, large format infrared imaging arrays, has it been possible to design chemical sensors offering uncompromising performance in the spectral, spatial, as well as the temporal domain. Telops has developed an innovative instrument that can not only provide an early warning for chemical agents and toxic chemicals, but also one that provides a "Chemical Map" in the field of view. To provide to best field imaging spectroscopy instrument, Telops has developed the FIRST, Field-portable Imaging Radiometric Spectrometer Technology, instrument. This instrument is based on a modular design that includes: a high-performance infrared FPA and data acquisition electronics, onboard data processing electronics, a high-performance Fourier transform modulator, dual integrated radiometric calibration targets and a visible boresight camera. These modules, assembled together in an environmentally robust structure, used in combination with Telops' proven radiometric and spectral calibration algorithms make this instrument a world-class passive standoff detection system for chemical imaging. This paper presents chemical detection and identification results obtained with the FIRST sensor.

This paper aims to address the problem of behavioural anomaly detection in surveillance videos. We propose a novel framework tailored towards global video behaviour anomaly detection in complex outdoor scenes involving multiple temporal processes caused by correlated behaviours of multiple objects. Specifically, given a complex wide-area scene that has been segmented automatically into semantic regions where behaviour patterns are represented as discrete local atomic events, we formulate a novel Cascade of Dynamic Bayesian Networks (CasDBNs) to model behaviours with complex temporal correlations by utilising combinatory evidences collected from local atomic events. Using a cascade configuration not only allows for accurate detection of video behaviour anomalies, more importantly, it also improves the robustness of the model in dealing with the inevitable presence of errors and noise in the behaviour representation resulting less false alarms. We evaluate the effectiveness of the proposed framework on a real world traffic scene. The results demonstrate that the framework is able to detect not only anomalies that are visually obvious, but also those that are ambiguous or supported only by very weak visual evidence, e.g. those that can be easily missed by a human observer.

The Imagery Library for Intelligent Detection Systems (iLids) is the UK Government's standard for Video Based Detection Systems (VBDS). The first four iLids scenarios were released in November 2006 and annual evaluations for these four scenarios began in 2007. The Home Office Scientific Development Branch (HOSDB), in partnership with the Centre for the Protection of National Infrastructure (CPNI), has also developed a fifth iLids Scenario; Multiple Camera Tracking (MCT). The fifth scenario data sets were made available in November 2008 to industry, academic and commercial research organizations The imagery contains various staged events of people walking through the camera views. Multiple Camera Tracking Systems (MCTS) are expected to initialise on a specific target and be able to track the target over some or all of the camera views. HOSDB and CPNI are now working on a sixth iLids dataset series. These datasets will cover several technology areas: • Thermal imaging systems • Systems that rely on active IR illumination The aim is to develop libraries that promote the development of systems that are able to demonstrate effective performance in the key application area of people and vehicular detection at a distance. This paper will: • Describe the evaluation process, infrastructure and tools that HOSDB will use to evaluate MCT systems. Building on the success of our previous automated tools for evaluation, HOSDB has developed the MCT evaluation tool CLAYMORE. CLAYMORE is a tool for the real-time evaluation of MCT systems. • Provide an overview of the new sixth scenario aims and objectives, library specifications and timescales for release.

This paper reports how objects in street scenes, such as pedestrians and cars, can be spotted, recognised and then subsequently tracked in cluttered background using a cortex like vision approach. Unlike the conventional pixel based machine vision, tracking is achieved by recognition of the target implemented in neuromorphic ways. In this preliminary study the region of interest (ROI) of the image is spotted according to the salience and relevance of the scene and subsequently target recognition and tracking of the object in the ROI have been performed using a mixture of feed forward cortex like neuromorphic algorithms together with statistical classifier & tracker. Object recognitions for four categories (bike, people, car & background) using only one set of ventral visual like features have achieved a max of ~70% accuracy and the present system is quite effective for tracking prominent objects relatively independent of background types. The extension of the present achievement to improve the recognition accuracy as well as the identification of occluded objects from a crowd formulates the next stage of work.

The in situ identification and spatial location of gases, discrete liquid droplets and residues on surfaces is a technically challenging problem. Active Infrared (IR) hyperspectral imaging is a powerful technique that combines real-time imaging and optical spectroscopy for "standoff" detection of suspected chemical substances, including chemical warfare agents, toxic industrial chemicals, explosives and narcotics. An active IR hyperspectral imaging system requires a coherent, broadly tunable IR light source of high spectral purity, in order to detect a broad range of target substances. In this paper we outline a compact and power-efficient IR illumination source with high stability, efficiency, tuning range and spectral purity based upon an optical parametric oscillator (OPO). The fusion of established OPO technology with novel diode-pumped laser technology and electro-mechanical scanning has enabled a broadly applicable imaging system. This system is capable of hyperspectral imaging at both Near-IR (1.3 - 1.9 μm) and Mid-IR (2.3 - 4.6 μm) wavelengths simultaneously with a line width of < 3 cm^-1. System size and complexity are minimised by using a dual InGaAs/InSb single element detector, and images are acquired by raster scanning the coaxial signal and idler beams simultaneously, at ranges up to 20 m. Reflection, absorption and scatter of incident radiation by chemical targets and their surroundings provide a method for spatial location, and characteristic spectra obtained from each sample can be used to identify targets uniquely. To date, we have recognized liquids in sample sizes as small 20 μl-and gases with sensitivity as high as 10ppm.m-at detection standoff distances > 10 m.

This paper reports how Electro-Optics (EO) technologies such as thermal and hyperspectral [1-3] imaging methods can be used for the detection of stress remotely. Emotional or physical stresses induce a surge of adrenaline in the blood stream under the command of the sympathetic nerve system, which, cannot be suppressed by training. The onset of this alleviated level of adrenaline triggers a number of physiological chain reactions in the body, such as dilation of pupil and an increased feed of blood to muscles etc. The capture of physiological responses, specifically the increase of blood volume to pupil, have been reported by Pavlidis's pioneer thermal imaging work [4-7] who has shown a remarkable increase of skin temperature in the periorbital region at the onset of stress. Our data has shown that other areas such as the forehead, neck and cheek also exhibit alleviated skin temperatures dependent on the types of stressors. Our result has also observed very similar thermal patterns due to physical exercising, to the one that induced by other physical stressors, apparently in contradiction to Pavlidis's work [8]. Furthermore, we have found patches of alleviated temperature regions in the forehead forming patterns characteristic to the types of stressors, dependent on whether they are physical or emotional in origin. These stress induced thermal patterns have been seen to be quite distinct to the one resulting from having high fever.

In some recognition form applications (which require multiple images: facial identification or sign-language), many images should be transmitted or stored. This requires the use of communication systems with a good security level (encryption) and an acceptable transmission rate (compression rate). In the literature, several encryption and compression techniques can be found. In order to use optical correlation, encryption and compression techniques cannot be deployed independently and in a cascade manner. Otherwise, our system will suffer from two major problems. In fact, we cannot simply use these techniques in a cascade manner without considering the impact of one technique over another. Secondly, a standard compression can affect the correlation decision, because the correlation is sensitive to the loss of information. To solve both problems, we developed a new technique to simultaneously compress & encrypt multiple images using a BPOF optimized filter. The main idea of our approach consists in multiplexing the spectrums of different transformed images by a Discrete Cosine Transform (DCT). To this end, the spectral plane should be divided into several areas and each of them corresponds to the spectrum of one image. On the other hand, Encryption is achieved using the multiplexing, a specific rotation functions, biometric encryption keys and random phase keys. A random phase key is widely used in optical encryption approaches. Finally, many simulations have been conducted. Obtained results corroborate the good performance of our approach. We should also mention that the recording of the multiplexed and encrypted spectra is optimized using an adapted quantification technique to improve the overall compression rate.

Nowadays, protecting information is a major issue in any transmission system, as showed by an increasing number of research papers related to this topic. Optical encoding methods, such as a Double Random Phase encryption system i.e. DRP, are widely used and cited in the literature. DRP systems have very simple principle and they are easily applicable to most images (B&W, gray levels or color). Moreover, some applications require an enhanced encoding level based on multiencryption scheme and including biometric keys (as digital fingerprints). The enhancement should be done without increasing transmitted or stored information. In order to achieve that goal, a new approach for simultaneous multiplexing & encoding of several target images is developed in this manuscript. By introducing two additional security levels, our approach enhances the security level of a classic "DRP" system. Our first security level consists in using several independent image-keys (randomly and structurally) along with a new multiplexing algorithm. At this level, several target images (multiencryption) are used. This part can reduce needed information (encoding information). At the second level a standard DRP system is included. Finally, our approach can detect if any vandalism attempt has been done on transmitted encrypted images.

We consider the problem of restoration of a signal that is measured in different frequency ranges by a set of spectrometers. The main goal is a demonstration of the possibility to restore the signal on the base of such scheme of registration and then to identify the medium. This problem is close to the registration of acoustic signals and also other types of signals. We suggest a new method for multichannel registration and processing of a noisy regular acoustic signal by the set of integral measurements, made simultaneously in each frequency range. This technique allows the reconstruction of partial signals in each frequency range, then sums them up and to obtain the full acoustic signal, containing both noisy and the regular part. As it shows one can to define the signal even for the case when the noise level is ten times more intense than the regular signal. Further analysis of the spectral dynamics of the full acoustic signal allows us to separate the regular part of the signal from its noisy part. The computer modeling we have carried out demonstrates many advantages of this algorithm. It provides a possibility to obtain the complete information about the dynamics of many spectral lines simultaneously and so to determine the spectral lines dynamics at regular frequencies. The proposed method also can be very useful for detection and identification of explosives in the enhanced GHz-THz range.

This paper discusses the integration of a number of advanced image and data processing technologies in support of the development of next-generation Situational Awareness systems for counter-terrorism and crime fighting applications. In particular, the paper discusses the European Union Framework 7 'SAMURAI' project, which is investigating novel approaches to interactive Situational Awareness using cooperative networks of heterogeneous imaging sensors. Specific focus is given to novel Data Fusion aspects of the research which aim to improve system performance through intelligently fusing both image data and non image data sources, resolving human-machine conflicts, and refining the Situational Awareness picture. In addition, the paper highlights some recent advances in supporting image processing technologies. Finally, future trends in image-based Situational Awareness are identified, such as Post-Event Analysis (also known as 'Back-Tracking'), and the associated technical challenges are discussed.

We demonstrate how molecular spectroscopy methods using NIR and MIR lasers can provide rapid detection and identification of many threat materials. It is increasingly recognised that one spectroscopic method will not be suited to every target in every scenario, both in terms of spectroscopic selectivity and the context e.g. vapour phase or within a sealed container. The orthogonal selection rules and capabilities of IR and Raman in combination allow the identification of a very broad range of targets, both in liquid and vapour phase. Therefore, we introduce the benefits of the combining infra-red absorbance based on Quantum Cascade lasers (QC-IR) and NIR Raman spectroscopy for nitrogenous and peroxide based materials. Rapid scan rates up to 10Hz for QC-IR and Raman and are demonstrated using current technology. However, understanding of the chemistry and spectroscopic signatures behind such materials is necessary for accurate fast fitting algorithms to benefit of the full advantage with advances in hardware. This is especially true as future users requirements move towards rapid multiplexed analysis and data fusion from a variety of sensors.

A novel approach to realize an optimized multi-decision segmented filter for recognizing a 3D object in a given scene is suggested. For that purpose, a correlation filter suitable for multi-view images is proposed. Like 3D object reconstruction techniques from multi-view images, we use multiple cameras displayed in a well-defined pickup grid. Each multi-view image gives a unique perspective of the scene. Then, the elemental images of the 3D object are separately correlated using a multi-channel correlator with the newly designed optimized filter. This optimization was carried out to take into account possible changes of the 3D object in the scene, e.g. rotation, scale, because correlation techniques are very sensitive to this kind of noise. To solve this problem, the filter must be sufficiently flexible to include information about different rotations of the elemental image. The optimization of the fusion of the different elemental references images, e.g. taken from different angles of rotation, was realized. In addition, a shifting of the different spectra was done in the filter plane to minimize the overlap between the different elemental spectra. In this study, particular attention is paid for the choice of the lateral shifting. With this correlation system, each channel gives a single decision concerning a single perspective of the 3D object. We demonstrate that the final correlation decision takes into account all these elemental decisions to determine the presence (or not) of the 3D object in the target scene.