A Review of Automated Image Understanding within 3D Baggage Computed Tomography Security Screening

Baggage inspection is the principal safeguard against the transportation of prohibited and potentially dangerous materials at airport security checkpoints. Although traditionally performed by 2D X-ray based scanning, increasingly stringent security regulations have led to a growing demand for more advanced imaging technologies. The role of X-ray Computed Tomography is thus rapidly expanding beyond the traditional materials-based detection of explosives. The development of computer vision and image processing techniques for the automated understanding of 3D baggage-CT imagery is however, complicated by poor image resolutions, image clutter and high levels of noise and artefacts. We discuss the recent and most pertinent advancements and identify topics for future research within the challenging domain of automated image understanding for baggage security screening CT

Detection of concealed weapons in X-ray images using fuzzy K-NN

ABSTRAC

Detecting shielded explosives by coupling prompt gamma neutron activation analysis and deep neural networks

Prompt Gamma Neutron Activation Analysis is a nuclear-based technique that can be used in explosives detection. It relies on bombarding unknown samples with neutrons emitted from a neutron source. These neutrons interact with the sample nuclei emitting the gamma spectrum with peaks at specific energies, which are considered a fingerprint for the sample composition. Analyzing these peaks heights will give information about the unknown sample material composition. Shielding the sample from gamma rays or neutrons will affect the gamma spectrum obtained to be analyzed, providing a false indication about the sample constituents, especially when the shield is unknown. Here we show how using deep neural networks can solve the shielding drawback associated with the prompt gamma neutron activation analysis technique in explosives detection. We found that the introduced end-to-end framework was capable of differentiating between explosive and non-explosive hydrocarbons with accuracy of 95% for the previously included explosives in the model development data set. It was also, capable of generalizing with accuracy 80% over the explosives which were not included in the model development data set. Our results show that coupling prompt gamma neutron activation analysis with deep neural networks has a good potential for high accuracy explosives detection regardless of the shield presence

Explosive Detection Equipment and Technology for Border Security

This report contains a brief survey of Explosives Detection Technology,as it is applied for inspection of goods and passengers at borders, and explains the role of European legislation and the European Commission¿s research programs in this field. It describes the techniques of trace and bulk explosives detection that are in use, the latest techniques that are in development and the characteristics of explosives that are, or might be, used to provide a signature for exploitation in detection technology. References to academic reviews are included for those wishing to study the subject in greater depth. Some additional details are given concerning plastic and liquid explosives, which are a threat of particular current importance. The report also contains a brief account of relevant European trade, safety and security legislation, a description of recent policy initiatives and tables of related European Commission funded research projects. Contact details of commercial companies selling explosive detection products are also provided.JRC.G.6-Sensors, radar technologies and cybersecurit

Automated Human Screening for Detecting Concealed Knowledge

Screening individuals for concealed knowledge has traditionally been the purview of professional interrogators investigating a crime. But the ability to detect when a person is hiding important information would be of high value to many other fields and functions. This dissertation proposes design principles for and reports on an implementation and empirical evaluation of a non-invasive, automated system for human screening. The screening system design (termed an automated screening kiosk or ASK) is patterned after a standard interviewing method called the Concealed Information Test (CIT), which is built on theories explaining psychophysiological and behavioral effects of human orienting and defensive responses. As part of testing the ASK proof of concept, I propose and empirically examine alternative indicators of concealed knowledge in a CIT. Specifically, I propose kinesic rigidity as a viable cue, propose and instantiate an automated method for capturing rigidity, and test its viability using a traditional CIT experiment. I also examine oculomotor behavior using a mock security screening experiment using an ASK system design. Participants in this second experiment packed a fake improvised explosive device (IED) in a bag and were screened by an ASK system. Results indicate that the ASK design, if implemented within a highly controlled framework such as the CIT, has potential to overcome barriers to more widespread application of concealed knowledge testing in government and business settings

Institute for the Protection and Security of the Citizen Activity Report 2002.

Abstract not availableJRC.G-Institute for the Protection and the Security of the Citizen (Ispra

Forensic Science: Current State and Perspective by a Group of Early Career Researchers

© 2016, Springer Science+Business Media Dordrecht. Forensic science and its influence on policing and the criminal justice system have increased since the beginning of the twentieth century. While the philosophies of the forensic science pioneers remain the pillar of modern practice, rapid advances in technology and the underpinning sciences have seen an explosion in the number of disciplines and tools. Consequently, the way in which we exploit and interpret the remnant of criminal activity are adapting to this changing environment. In order to best exploit the trace, an interdisciplinary approach to both research and investigation is required. In this paper, nine postdoctoral research fellows from a multidisciplinary team discuss their vision for the future of forensic science at the crime scene, in the laboratory and beyond. This paper does not pretend to be exhaustive of all fields of forensic science, but describes a portion of the postdoctoral fellows’ interests and skills

Exploring investigative question generation

A failure to conduct effective investigative interviews can have drastic consequences such as wrongful convictions or the inability to prevent terrorist attacks. One method of judging the efficacy of an interview is the ability to distinguish between honest and deceptive interviewees. Many techniques claim to improve the ability to detect deception, such as the CCE technique. However, little research has focused on the conditions that might enhance the ability to generate investigatively useful questions. In series of experiments we sought to identify the underlying dimensions of question quality. Initially, we investigated unexpectedness, finding that it was a useful dimension but dependent on the content of the questions (Chapters 2 and 3). In Chapter 5 we used a bottom-up approach to develop a 3-dimensional model of question quality. These dimensions were investigative relevance, unpredictability and type of knowledge probed. The model proved to be effective in predicting the outcome of real-world investigate interviews (Chapter 6). We also aimed to investigate the factors which might affect question generation ability. The scope of episodic information inherently available to the interviewer was shown to be a context-dependent factor affecting the ability to generate useful questions (Chapters 4 and 5). Training, via a short instructional video, was also shown to improve question generating ability (Chapter 4). Additionally, the veracity of the interviewee and the expertise of the question generator affected ability, though this was only detected by novice judges (Chapter 5). The findings presented in this thesis have implications for the investigative community, suggesting that deliberate attention should be paid to the phrasing of key interview questions in order to ensure that they are relevant, unpredictable and probing episodic knowledge. Additionally, the findings may inform current research that is focused on developing technology designed to assist investigative interviewers

Device profiling analysis in Device-Aware Network

As more and more devices with a variety of capabilities are Internet-capable, device independence becomes a big issue when we would like the information that we request to be correctly displayed. This thesis introduces and compares how existing standards create a profile that describes the device capabilities to achieve the goal of device independence. After acknowledging the importance of device independence, this paper utilizes the idea to introduce a Device-Aware Network (DAN). DAN provides the infrastructure support for device-content compatibility matching for data transmission. We identify the major components of the DAN architecture and issues associated with providing this new network service. A Device-Aware Network will improve the network's efficiency by preventing unusable data from consuming host and network resources. The device profile is the key issue to achieve this goal.http://archive.org/details/deviceprofilingn109451301Captain, Taiwan ArmyApproved for public release; distribution is unlimited