This PDF file contains the front matter associated with SPIE Proceedings Volume 11542, including the Title Page, Copyright information, and Table of Contents

This record contains the opening remarks for the 11542 Digital Forum.

The increased availability and capabilities of drones in the consumer market has lead to increased risk in air traffic control and other public safety concerns. Automated drone detection systems can help to generate alerts and increase reaction time by security forces. Recently proposed approaches and systems are usually based on a combination of sensors and machine learning to carry out the detection of drones. While electro-optical imagery is the most prevalent modality, infrared sensors can complement it by providing better visibility in certain situations with cluttered background or low light conditions. A key limitation when using infrared data is the limited availability of data for training machine learning methods. In this work, we specifically focus on the task of drone detection in infrared imagery. Our main focus lies on investigating how the small amount of available infrared data can be compensated for. We approach this problem through three different types of experiments. First, we compare a detector resulting from training on limited infrared data with a detector trained on more diverse optical data. We then propose and evaluate several methods for pre-processing optical data in such a way that it better resembles the characteristics of infrared data. Finally, we train detectors on a combination of infrared and pre-processed optical data and evaluate the trade-off between amount of available infrared data and achieved accuracy of the resulting detector. We evaluate all detectors on our own set of diverse infrared recordings. Our results show that suitable pre-processing of optical data can significantly improve the resulting accuracy and performs much better than training solely on limited infrared data.

Object detection from infrared-band (thermal) imagery has been a challenging problem for many years. With the advent of deep Convolutional Neural Networks (CNN), the automated detection and classification of objects of interest within the scene has become popularised due to the notable increases in performance over earlier approaches in the field. These advances in CNN approaches are underpinned by the availability of large-scale, annotated image datasets that are typically available for visible-band (RGB) imagery. By contrast, there is a lack of prior work that specifically targets object detection in infrared-band images, owing to limited datasets availability that stems from more the limited availability and access to infrared-band imagery and associated hardware in general. A viable solution to this problem is transfer learning which can enable the use of such CNN techniques within infrared-band (thermal) imagery, by leveraging prior training on visible-band (RGB) image datasets, and then subsequently only requiring a secondary, smaller volume of infrared-band (thermal) imagery for CNN model fine-tuning. This is performed by adopting an existing pre-trained CNN, pre-optimized for generalized object recognition in visible-band (RGB) imagery, and subsequently fine-tuning the resultant model weights towards our specific infrared-band (thermal) imagery domain task. We use of two state-of-art object detectors, Single Shot Detector (SSD) with a VGG-16 CNN backbone pre-trained on the ImageNet dataset, and You-Only-Look-Once (YOLOV3) with a DarkNet-53 CNN backbone pretrained on the MS-COCO dataset to illustrate our visible-band to infrared band transfer learning paradigm. Exemplar results reported over the FLIR Thermal and MultispectralFIR benchmark datasets show that significant improvements in mAP detection performance to f0.804_MsFIR, 0.710_FLIRg for SSD and f0.520_MsFIR, 0.308_FLIRg for YOLOV3 via the use of transfer learning from initial visible-band based CNN training.

Real-time behaviour analysis is of paramount importance to ensure the safety of passengers in border-crossing areas. It allows to recognize the security threats on time. Moreover, it can accelerate the security check since the security personnel only consider severe checks for passengers with suspicious behaviour. In this work, we consider the following suspicious patterns: (a) mindless turn, (b) peculiar interest to the security units, and (c) avoiding the security units. We propose an algorithm to compute an abnormal behaviour score in real-time. This score can help the security personnel to assess passenger movement patterns. We show the performance of our scoring algorithm via different synthetic examples.

Multi-user applications where two or more users are interacting with the same system through a shared interface e.g., large presentation touchscreens in meeting rooms to do situation analysis in a civil security context are becoming more and more frequent. Whilst traditional single user authorization scenarios seem to be a solved problem and there are some existing solutions for collaborative multi-user applications with a separate devices per user, methods for multi-user authorization, where a single device is in simultaneous usage, come with a set of new questions. It must be considered that several users work simultaneously on the same physical device so there is no way to create a separate view for every user that fits their access rights. Especially in the context of civil security it is very likely that there are several users with different security levels and the data displayed is potential highly sensitive. Therefore new strategies are needed to decide which content is shown when certain users with potentially completely different access rights work together. We will define those strategies by doing considerations how to realize authorization for a simultaneous collaborative multi-user workspace. This is done by extending the well-known Bell-LaPadula model for multi-user authorization by using different strategies regarding data confidentiality. The feasibility of our formal models is shown with an implementation in XACML, which is described in detail. With this it is already possible to integrate our model in real world applications, which we show with the Fraunhofer Digital Map Table.

The growth of big data and its popularity in maritime surveillance has increased at an exponential rate. The amount of maritime information being collected every minute around the world exceeds the capacity of traditional databases. The development of real-time, Geospatial Web Applications e.g., MarineTraffic and VesselFinder AIS vessel tracking web sites, provide us with huge sets of structured and unstructured data that are too complex for traditional data-processing software. The aim of this paper is to exploit the benefits of query and mashup amounts of maritime data using mashup tools as a result to create a single, unique visualization. The results show that using mashup techniques in maritime surveillance could be used to monitor, compare, combine, manipulate and analyse Big Maritime data. Therefore, research on Maritime Data offers a huge potential and an opportunity to benefit from the advantages.

Person re-identification (Re-ID) is a valuable technique because it can assist in finding suspects after a terrorist attack. However, the machine learning algorithms for person Re-ID are usually trained on large datasets with images of many different people in a public space. This could pose privacy concerns for the people involved. One way to alleviate this concern is to anonymize the people in the dataset. Anonymization is important to minimize the storage and processing of personal information, such as facial information in a surveillance video. However, anonymization typically leads to loss of information and could lead to severe deterioration of the Re-ID quality. In this paper, we show that it is possible to store only anonymized person detections while still achieving a high quality person Re-ID. This leads to the conclusion that for the development of re-identification algorithms in situations where privacy is of great importance it is not necessary to store facial information in person re-identification datasets.

The current capabilities and capacities of border guards and immigration services can be enhanced using technologies that automate the analysis of travel, identity and breeder documents in order to detect fraud. These technologies can be relevant for countering emerging threats in document and identity verification (e.g., forged documents, impostor fraud, morphed faces) at both manual and highly automated border control points (both in the first and in the second line) and in the issuance process of genuine documents. The travel documents (e.g., passports) and breeder documents (e.g., birth certificates) contain personal information, such as name, date of birth and national number. The personal information must be well protected and a data breach must be avoided at all times. One of the ways to protect the personal data is to minimize the sharing of personal data. Anonymization removes the personal information (e.g., by replacing the personal information by a black bar) and can therefore be used to minimize the sharing of personal data. This paper describes the tool that assists border guards and immigration services for the anonymization of travel and breeder documents. The tool consists of a graphical user interface, document detection, keyword recognition, face detection, number detection, barcode detection and masking of personal data. The results show that only 10 annotated images are needed to reach a keyword detection accuracy of 96% and anonymization sensitivity of 93% of the related personal data.

We have studied an electrochemical detection method for the stimulants in the forensic samples using electrochemiluminescence (ECL). In this context, amphetamine type stimulant (methamphetamine (MA)) has been studied as coreactants in the [Ru(bpy)₃]²⁺ (where bpy is 2,2’-bipyridine) ECL system. This approach is developed based on a glassy carbon electrode modified with [Ru(bpy)₃]²⁺ /Nafion composite film. LoD, LoQ and linear working range for MA are studied currently. The ECL intensity was found to be concentrations over the range of 5 x 10^-8 to 2.5 x 10^-4mol/L. LoD for MA is 1.94 x 10^-10 mol/L. The regression coefficient is 0.9931 for the experiment. Our approach was applied in different medium such as saliva and human serum to detect MA This technique is simple, rapid, selective and sensitive, and shows potential for the highthroughput quantitation of MA. the results show that the present electrochemical approach seems to provide a sensitive detection of MA in forensic applications.

The ability to identify explosives by ultrasonic spectra up to 45 kHz has been investigated for forensic and anti-terror applications. To lower the threshold for laser initiation, nontrivial and well-known azides, CTAP, HMDT, ETN, HMX and other energetic materials have been synthesized. Upon initiation of copper azide by Nd:YAG laser with 11 ns pulsewidth, a threshold of only ~80 μJ was reached, and for 50 μs pulses of laser diode it was ~300 μJ, which is consistent with the thermal initiation nature. Significant differences were found in the spectrum of high-frequency acoustic and ultrasonic vibrations for various energetic materials and bilayer structures. The effective frequency range for the dissociation of copper azide, silver azide and HMTD is limited by ~27 kHz. The spectra of bilayer structures demonstrate suppression of the characteristic lines of copper azide and enrich the spectrum in the ~27 – 45 kHz range: ETN appears in relatively wide bands, while HMX modulates the spectrum with periodic ~3 kHz bands. If successful, the discovered patterns can be used in disaster forensics.

The prolonged armed conflict in Eastern Ukraine since 2014 has generated the increasing public safety concern about landmines, abandoned unexploded ordnance (UXO) and small-size explosive remnants of war, which are spreading around the region of a conflict. Such ordnance can be used for making the improvised explosive devices (IED) as well. The background studies have identified the following key obstacles which make UXO demining and cleaning in that region challenging: an absence of government-endorsed national technical standards against which demining activity can be measured in crowded areas and non-permissive operating environment (i.e. public transport hubs and metro), and not enough human and technical capacity. Demining is carried out often using different techniques and outdated equipment. During the applied research project, the available open source international best practices and the UXO risk assessment methods were reviewed and assessed, firstly. Secondly, a new demining methodology was developed for improving the existing standard operating procedures of the bomb disposal units of the State Emergency Service of Ukraine (SESU). Thirdly, a proof-of-concept was designed for field trials. A prototype of a light-weight smart steel cone was constructed which can cover small-size UXO in critical infrastructures like metro without using heavy commercial explosive ordinance disposal robots and causing a minimum impact to environment and ecology. Live field testing was conducted. Finally, based on the successful trials, the recommendations for the standard operating procedures (SOP) of the bomb disposal units of the SESU were produced. For example, this cone can be stored in metro station and easily transported by a security guard, who covers abandoned UXO. If an object goes off before the bomb squad arrives on site, then this device can efficiently protect the crowed area and environment from the bomb fragments. This new demining equipment was granted a patent.

The distinctive features of laser ionization source in field asymmetric ion mobility spectrometry method are studied in this paper. A YAG:Nd 3+ nanosecond laser (λ = 266 nm, τpulse = 6 ns) with variable pulse energy E pulse = 700 – 2500 μJ and frequency ν = 10 – 20 Hz was used as a source of laser radiation. Pentaerythritol tetranitrate (PETN), trinitrotoluene (TNT) cyclotrimethylenetrinitramine (RDX), 1,3,5,7-tetranitro-1,3,5,7-tetrazoctane (HMX), explosives were investigated with use of field asymmetric ion mobility spectrometry (FAIMS) method. Ion spectra were recorded by with separating fields 8 – 12 kV/cm. Nickel radioactive isotope 63Ni was used as reference ionization source for explosive molecules. Non-linear ion mobility spectra of each substance ionized with UV laser radiation and radioactive 63Ni were compared and reasons for similarities and distinctive features are discussed. For peaks of explosives and reactant-ion peaks the dependences of their positions along compensating voltage axis on the magnitude of separating voltage (separating electric field) were measured for all the ion sources and substances. All the experiments were carried out under controlled ambient temperature and relative humidity (t=25℃, RH 30%). Humidity was supported the same inside and outside the gas system to minimize the influence of water cluster formation on the results obtained. Explosives vapors generators were made with 10mg samples of chemically pure explosives. RDX, HMX and PETN were heated (RDX 50℃, HMX 50℃, PETN 45℃) to increase the concentration of ions. It was shown that the behavior of the peaks of the explosives at laser excitation is different from the behavior at radioactive source for each of the substances. This indicates the presence of an additional ionization mechanism under laser radiation along with the traditional one. Spectra of reactant ion peaks under radioactive ionization also show difference in ion formation for each substance. Behavior of reactant-ion peaks of each of the substances with laser ion source shows nearly perfect coincidence. This fact can demonstrate well controlled experimental conditions and further confirms the difference in ionization mechanisms for laser and nickel radioactive ion source.

Infrared reflectance spectra can be influenced by many factors, e.g. the substrate and the thickness of the layer for liquids or the surface micromorphology, the form (powder, crystal) and the particle size for solids. All these parameters can have an effect on the appearance of the measured spectrum. To avoid collecting multitudes of spectra to cover all such scenarios, the optical constants n and k, which are intrinsic properties of a material, can instead be used to model the reflectance spectrum. For solids, two techniques are commonly used to derive optical constants: ellipsometry and single-angle reflectance spectroscopy. For both methods, best results are usually obtained from single crystals. We have recently demonstrated for ammonium sulfate (a relatively soft material) that by optimizing certain conditions, high quality pellets with specularly reflective surfaces can be used in lieu of crystals. This was confirmed by the excellent agreement between the optical constants derived by these two methods. This work focuses on the possible extension of these methods to harder materials, starting with sodium sulfate. The first step is to see if high quality pellet surfaces can be obtained as for ammonium sulfate. The reflectance values and the associated optical constants can also be obtained.

The presentation reports of using two different small hyperspectral cameras in two full-length operational field exercises with CWA/TIC scenarios. The first exercise was carried out as a response to a simulated sarin attack at an airport, the other a simulated chlorine attack was carried out with a vehicle in the middle of a small town. The first exercise was led by military forces in Greece and the other by rescue service and defence forces in Finland. The motivation for testing hyperspectral cameras in these exercises was to gain through authentic operation information of the usability and performance of small cameras in mission critical situations in highly toxic environments. The two exercises were carried out with simulants, and several different technologies were used and tested during the same operations. In one of the exercises, hyperspectral camera was used for detecting simulated agent in the hot zone inside of an airport hall and outside for screening exposed devices at the decontamination station of equipment. In the other exercise, hyperspectral camera was at first used from a distant location outside of hot zone for detecting and alerting for a toxic release that was caused by a colliding vehicle. After the casualties were evacuated, hyperspectral camera was also used for screening the van that caused the hazardous incident. The exercises show that in some parts of a full-length CBRNE rescue operation there is particular advantage of using small hyperspectral cameras. Applicable usage can be found during the whole life cycle of the incident. Accuracy and speed are adjustable and dependent of the settings of the software and camera. Compared with other technologies, hyperspectral technology is potentially able to detect same agents and can also offer some additional advantages like remote detection that other technologies cannot do.

Early detection of pathogens is crucial for ensuring safe living conditions. Conventional sampling methods do not ensure the sustainability of captured microorganisms. Cyclone-based liquid absorptive samplers are the most promising devices in this regard. Most samplers have limited application scope as they are intended for laboratories. In the study we developed a special liquid-based sampler for mounting on a drone. A structure and base values of a cyclone collector were determined. The chosen design provides maximum particle capturing efficiency in terms of low air flow rate and small size of the collector. Projected capturing efficiency for particles of the size of 1mсm is approximately 20%, for particles of the size bigger than 2,5mсm is 100%. Mathematical modeling proved the correctness of theoretical considerations. This made it possible to design and fabricate a prototype of a sampler device which also includes a fan, a peristaltic pump, valves, a sensor for liquid levels monitoring, a display for operation mode controlling. Outdoor sampling on a drone has successfully proved performance efficiency at close to zero temperatures. A study on capturing efficiency was carried out by sampling sucrose aerosol with a fluorescein dye in a microbiological safety box. Specific efficiency of our sampler is 1,18 [relative units/(litre/min)], which is over twice s.e. of 0,43 [r.u./(l/min)] of existing laboratory devices. The device provides for the issuance of collected samples on standard immunochemical test strips for the analysis of adenovirus, rotavirus, influenza and other respiratory diseases with a full analysis time of 10 minutes.

Cyclotrhylmethylentrinitramine (RDX) is one of the most dangerous explosive substances. The presence of impurities in this explosive may be important for its determination as residual traces at the scene of incidents, as well as in the quick analysis of passengers and luggage by ion mobility spectrometers. In the work industrially manufactured RDX samples, that were not undergone any purification, were investigated by gas chromatography-mass spectrometry method. The attention was paid to search precursors and possible technological admixtures. On the basis of received chromatograms and mass spectra it was established the presence in the analyzed RDX samples of urotropin, acetic anhydride, acetic acid, triazine and octogen. The mass content of the substances was estimated. Special attention was paid to the products of RDX biodegradation, which can occur both in aerobic and anaerobic environments during its storage. The quantitative content of RDX biodegradation products in samples under study was estimated. Sorption of chemically pure and industrially manufactured RDX vapors on a concentrator from metal meshes were carried out. By the method of thermodesorption mass spectrometry the composition and differences of the concentrated samples were analyzed. Recommendations for taking into account the results obtained when working with vapors and traces of RDX by ion mobility spectrometers were given.

Design research of X-ray backscatter imaging system for vehicle security was carried out, aiming at the demand of accurate and rapid detection of contrabands. The influence of the chopper mechanism on the imaging resolution and the solid angle of the flying point beam was simulated, while the parameters and structure of the chopper mechanism were designed. The imaging resolution of the backscattering system is about 8 mm and the solid angle of the flying point beam is about 6.4×10^{- 5} sr. Based on the X-ray energy deposition and luminescence efficiency, the effect of detector thickness and lead doped on the detection efficiency with different energy was investigated. A calculation model of luminous flux for backscatter detection was established and the influence of detector parameters on scattered X-ray luminous flux was analyzed, also the length of the detector was determined. The results show that it is more reasonable to use the lead-free plastic scintillator with thickness of 50 mm and length of 2.5 m as the backscattering detector for the X-ray backscattering system used for scanning of vehicle bottom, which can meet the demand of security inspection of vehicle bottom.

Remote sensing is considered as an increasingly important technology for maritime surveillance. The process of maritime surveillance for safety is critical for every country. The need for information on migrant movements by sea using different sizes and types of vessels is of paramount significance. Such information is essential for the search and rescue (SaR) operations of unauthorised migrants. The aim of this paper is to show how to detect migrant vessels in the Cyprus Region using freely available Sentinel-1 SAR data. The comparison was made using open source available migrant data and Sentinel-1 SAR acquisitions. Sentinel-1 SAR images were used to investigate three Areas of Interest (AoI). The main AoI is located at the Northwest coasts, whilst the second area includes the Southeast coasts of Cyprus. The results indicate that the Sentinel-1 SAR data can provide decisionmakers with effective results and spatial information on migration routes.

The presence of characteristic peaks in the terahertz (THz) absorption spectra of many organic substances and the active development of the technology for manufacturing video cameras based on microbolometric matrices create an increased interest in methods for identifying explosive compounds using THz imaging with simultaneous recording of spectral information. The results of relevant studies can be used in the development of security systems. THz images (taking into account the spectral information in each pixel) were obtained in this work by passing radiation through a sample based on hexogen (RDX) microcrystals deposited on a polyethylene (PE) film. A photoconductive antenna was used as a source of broadband radiation in the range from 0.5 THz to 2.5 THz. Spectral resolution was provided using a Fourier spectrometer based on a Michelson interferometer. The images were recorded using a THz video camera based on a microbolometric matrix. The possibility of identifying RDX microcrystals using color visualization of spectral information in the frequency range of one of the characteristic RDX peaks (~0.8 THz) has been demonstrated.

Automatic 3-D recovery from multiview satellite images can be extremely useful for information extraction for the surveillance application. For 3-D scene reconstruction, one approach is to employ multiple cameras for creating a multiview image with the aim to make interactive free-viewpoint selection possible in 3-D data. In most cases, such a 3-D scene contains missing holes on depth maps that appear during the synthesis from multi-views. This paper presents an automated pipeline for processing multi-view satellite images to 3-D digital surface models. The proposed approach uses the modified exemplar-based technique. We propose an algorithm using the concepts of a sparse representation of quaternions, which use a new gradient to calculate the priority function by integrating the structure of quaternions with LPA-ICI (local polynomial approximation - the intersection of confidence intervals) and the saliency map. Moreover, the color information incorporates into the optimization criteria to obtain sharp inpainting results. For this purpose, we use the Hamiltonian quaternion framework. Compared with state-of-the-art techniques, the proposed algorithm provides plausible restoration of the depth map from multi-view satellite images, which makes them a promising tool for surveillance applications.

Trace detection and identification of hazardous volatile explosives has been a key challenge to the scientific community past many decades. Commercially available various analytical and spectroscopic techniques suffer from low sensitivity, swabbing of surfaces and low detection limit. Triacetone Triperoxide (TATP), used in improvised explosive devices IEDs vaporizes readily at room temperature and has a vapour signature. However, explosive trace detectors (ETDs) are incompetent to detect TATP due to absence of chromophoric groups. We have investigated the novel hollow core photonic crystal fibres (HC-PCFs) based Raman sensor for real time monitoring of such volatile explosives in airport security. Raman scattering, a powerful, non-destructive tool provides molecular fingerprinting and is a potential candidate for detection of trace explosives but suffer from weak signal strength. Simultaneous confinement of pumped light and gas in HCFs allows greater light gas interaction providing an excellent optical sensing platform. These sensors can be easily incorporated at the security terminals or baggage counters with the existing metal detection systems. This paper reports investigations carried out on the HC-PCF designed using COMSOL Multiphysics software. The Raman signal being dependent on its intensity and mode area, simulations were conducted to analyse PCF parameters like confinement losses and mode field diameter/ effective mode area and its associated wavelength dependency. Theoretical study carried out on the HC-PCF also revealed that mode field confinements within the hollow core can be modified to suit specific laser wavelengths and confinement losses can be reduced to achieve Raman signal enhancement by optimizing their geometrical parameters like air-hole size and pitch/ hole-to-hole distance.