Concealed Object Detection Research Articles

Microwave and Millimeter-Wave Remote Sensing for Security Applications. By Jeffrey A. Nanzer, Artech House, 2012; 372 pages. Price £109.00, ISBN 978-1-60807-172-2

Microwave and millimeter-wave remote sensing techniques are fast becoming a necessity in many aspects of security as detection and classification of objects or intruders becomes more difficult. This groundbreaking resource offers you expert guidance in this burgeoning area. It provides you with a thorough treatment of the principles of microwave and millimeter-wave remote sensing for security applications, as well as practical coverage of the design of radiometer, radar, and imaging systems. You learn how to design active and passive sensors for intruder detection, concealed object detection, and human activity classification. This detailed book presents the fundamental concepts practitioners need to understand, including electromagnetic wave propagation in free space and in media, antenna theory, and the principles of receiver design. You find in-depth discussions on the interactions of electromagnetic waves with human tissues, the atmosphere and various building and clothing materials. This timely volume explores recently developed detection techniques, such as micro-Doppler radar signatures and correlation radiometry. The book is supported with over 200 illustrations and 1,135 equations.

Model-controlled flooding with applications to image reconstruction and segmentation

We discuss improved image reconstruction and segmentation in a framework we term model-controlled flooding (MCF). This extends the watershed transform for segmentation by allowing the integration of a priori information about image objects into flooding simulation processes. Modeling the initial seeding, region growing, and stopping rules of the watershed flooding process allows users to customize the simulation with user-defined or default model functions incorporating prior information. It also extends a more general class of transforms based on connected attribute filters by allowing the modification of connected components of a grayscale image, thus providing more flexibility in image reconstruction. MCF reconstruction defines images with desirable features for further segmentation using existing methods and can lead to substantial improvements. We demonstrate the MCF framework using a size transform that extends grayscale area opening and attribute thickening/thinning, and give examples from several areas: concealed object detection, speckle counting in biological single cell studies, and analyses of benchmark microscopic image data sets. MCF achieves benchmark error rates well below those reported in the recent literature and in comparison with other algorithms, while being easily adapted to new imaging contexts.

Real-time computational processing and implementation for concealed object detection

Millimeter wave (MMW) readily penetrates fabrics, thus it can be used to detect objects concealed under clothing. A passive MMW imaging system can operate as a stand-off type sensor that scans people both indoors and outdoors. However, because of the diffraction limit and low signal level, the imaging system often suffers from low image quality. Therefore, suitable computational processing would be required for automatic analysis of the images. The authors present statistical and computational algorithms and their implementations for real-time concealed object detection. The histogram of the image is modeled as a Gaussian mixture distribution, and hidden object areas are segmented by a multilevel scheme involving the expectation-maximization algorithm. The complete algorithm has been implemented in both MATLAB and C++. Experimental and simulation results confirm that the implemented system can achieve real-time detection of concealed objects.

Real-time concealed-object detection and recognition with passive millimeter wave imaging

Millimeter wave (MMW) imaging is finding rapid adoption in security applications such as concealed object detection under clothing. A passive MMW imaging system can operate as a stand-off type sensor that scans people in both indoors and outdoors. However, the imaging system often suffers from the diffraction limit and the low signal level. Therefore, suitable intelligent image processing algorithms would be required for automatic detection and recognition of the concealed objects. This paper proposes real-time outdoor concealed-object detection and recognition with a radiometric imaging system. The concealed object region is extracted by the multi-level segmentation. A novel approach is proposed to measure similarity between two binary images. Principal component analysis (PCA) regularizes the shape in terms of translation and rotation. A geometric-based feature vector is composed of shape descriptors, which can achieve scale and orientation-invariant and distortion-tolerant property. Class is decided by minimum Euclidean distance between normalized feature vectors. Experiments confirm that the proposed methods provide fast and reliable recognition of the concealed object carried by a moving human subject.

은닉 물체 검출을 위한 실시간 수동형 밀리미터파 영상 분할

Millimeter wave (MMW) readily penetrates fabrics, thus it can be used to detect objects concealed under clothing. A passive MMW imaging system can operate as a stand-off type sensor that scans people in both indoors and outdoors. However, because of the diffraction limit and low signal level, the imaging system often suffers from low image quality. Therefore, suitable statistical analysis and computational processing would be required for automatic analysis of the images. In this paper, a real-time concealed object detection is addressed by means of the multi-level segmentation. The histogram of the image is modeled with a Gaussian mixture distribution, and hidden object areas are segmented by a multi-level scheme involving -means, the expectation-maximization algorithm, and a decision rule. The complete algorithm has been implemented in C++ environments on a standard computer for a real-time process. Experimental and simulation results confirm that the implemented system can achieve the real-time detection of concealed objects.

Study of a New Millimeter-Wave Imaging Scheme Suitable for Fast Personal Screening

A new millimeter-wave (MMW) imaging scheme is presented, which has potential applications for fast personal screening. The proposed design employs a special pillbox-like quasi-optics that can generate a spot beam with nearly translational scanning pattern to ensure the image uniformity. The 200-GHz heterodyne transceiver was fabricated based on a microwave vector network analyzer (VNA) to couple the MMW into the quasi-optics and to extract the return wave for imaging. Experimental results based on a prototype system demonstrate the good performance of the new imaging scheme and its capability for concealed threat objects detection.

Real-time outdoor concealed-object detection with passive millimeter wave imaging

Millimeter wave imaging is finding rapid adoption in security applications such as the detection of objects concealed under clothing. A passive imaging system can be realized as a stand-off type sensor that can operate in open spaces, both indoors and outdoors. In this paper, we address real-time outdoor concealed-object detection and segmentation with a radiometric imaging system operating in the W-band. The imaging system is equipped with a dielectric lens and a receiver array operating at around 94 GHz. Images are analyzed by multilevel segmentation to identify a concealed object. Each level of segmentation comprises vector quantization, expectation-maximization, and Bayesian decision making to cluster pixels on the basis of a Gaussian mixture model. In addition, we describe a faster process that adopts only vector quantization for the first level segmentation. Experiments confirm that the proposed methods provide fast and reliable detection and segmentation for a moving human subject carrying a concealed gun.

Real-time terahertz scanning imaging by use of a pyroelectric array camera and image denoising

A high-resolution large-area terahertz (THz) scanning imaging system is demonstrated based on a 124×124 pyroelectric array camera and a CO(2) pumped continuous-wave THz laser. By applying a scanning mechanism to the real-time imaging setup, images of large-area targets were accomplished. Self-made resolution charts were employed to test the resolution. In order to improve the image quality, the noise in the images was studied and modeled, and then the performance of several denoising methods was compared with real-time THz original images. The experimental results show that, with the help of anisotropic diffusion, noise can be effectively suppressed, and the results are visually pleasant even when there is great attenuation. Those results greatly confirm application potentials of THz imaging using pyroelectric cameras in the field of concealed object detection.

330 GHz FMCW Image Sensor for Homeland Security Applications

A single-pixel imaging remote sensor operating at 330 GHz is described. It is based on a frequency modulated continuous wave (FMCW) and aimed at detection of concealed objects for ranges up to 40 m. The system consists of 2 horn-lens antennas integrated with a homodyne transceiver. The synthesized linear FMCW signal at X-band is multiplied by a factor of 32 to generate the transmitted signal. An intermediate frequency (IF) signal obtained in the output port of the 2-nd harmonic mixer is employed for image processing. Distance measurements were made by performing data acquisition unit based on LabView interface and resulting in a range resolution about 1 cm. Examples of 2D and 3D images reconstructed with this sensor are presented.

Automatic image segmentation for concealed object detection using the expectation-maximization algorithm

We address an image segmentation method to detect concealed objects captured by passive millimeter wave (MMW) imaging. Passive MMW imaging can create interpretable imagery on the objects concealed under clothing, which gives the great advantage to the security system. In this paper, we propose the multi-level expectation maximization (EM) method to separate the concealed objects from the other area in the image. We apply the EM method to obtain a Gaussian mixture model (GMM) of the acquired image. In the experiments, we evaluate the performance by the average probability of error. We will show that the consecutive EM processes separates the object area more accurately than the conventional EM method.

Back Propagation Neural Network-Modified Covariance Modelling for Improvement of Holographic Imaging

Two approaches are combined to improve the performance of modelling long wavelength holographic imaging (detection) of concealed objects. One approach is to design a multi-layer back propagation neural network that is able to reduce the effect of noise in a captured signal and results in a model as close as possible to the desired one. The other approach is to further process the captured signal by applying a modified covariance spectral estimation method to improve the resolution of the reconstructed image. Different concealing media and different values of signal to noise ratio are used to investigate the performance of such combination. It has been proved that the proposed model can provide an overall improvement in the imaging of concealed objects.

Detection and Segmentation of Concealed Objects in Terahertz Images

Terahertz imaging makes it possible to acquire images of objects concealed underneath clothing by measuring the radiometric temperatures of different objects on a human subject. The goal of this work is to automatically detect and segment concealed objects in broadband 0.1-1 THz images. Due to the inherent physical properties of passive terahertz imaging and associated hardware, images have poor contrast and low signal to noise ratio. Standard segmentation algorithms are unable to segment or detect concealed objects. Our approach relies on two stages. First, we remove the noise from the image using the anisotropic diffusion algorithm. We then detect the boundaries of the concealed objects. We use a mixture of Gaussian densities to model the distribution of the temperature inside the image. We then evolve curves along the isocontours of the image to identify the concealed objects. We have compared our approach with two state-of-the-art segmentation methods. Both methods fail to identify the concealed objects, while our method accurately detected the objects. In addition, our approach was more accurate than a state-of-the-art supervised image segmentation algorithm that required that the concealed objects be already identified. Our approach is completely unsupervised and could work in real-time on dedicated hardware.

Multispectral illumination and image processing techniques for active millimeter-wave concealed object detection

Active millimeter-wave imaging systems for concealed object detection offer the possibility of much higher image contrast than passive systems, especially in indoor applications. By studying active millimeter-wave images of different test objects derived in the W band, we show that multispectral illumination is critical to the detectability of targets. We also propose to use image change detection techniques, including image differencing, normalized difference vegetation index, and principle component analysis to process the multispectral millimeter-wave images. The results demonstrate that multispectral illumination can significantly reveal the object features hidden by image artifacts and improve the appearance of the objects.

A High-Resolution Imaging Radar at 580 GHz

We have developed a high-resolution imaging radar at 580 GHz. Coherent illumination in the 576-589 GHz range and phase-sensitive detection are implemented in an all-solid-state design based on Schottky diode sensors and sources. By employing the frequency-modulated continuous wave (FMCW) radar technique, we achieve centimeter-scale range resolution while utilizing fractional bandwidths of less than 3%. Our high operating frequencies also permit centimeter-scale cross-range resolution at several-meter standoff distances without large apertures. Scanning of a single-pixel transceiver enables targets to be rapidly mapped in three dimensions, and here we apply this technology to the detection of concealed objects on persons.

Millimeter wave probing of the acoustic phase for concealed object detection

We developed a far infrared technique for detecting objects that are concealed behind a barrier, which is opaque for visible light. The technique makes use of the fact that mechanically coupled objects can be distinguished by their acoustic phase during a driven vibration. The pattern of the acoustic phase is imaged using 70 GHz radiation. The experimental data demonstrate that virtually all objects can be sensed, which includes metals as well as dielectric materials.

Microwave imaging of concealed metal objects using a novel indirect holographic method

AbstractA novel, inexpensive technique for the detection of concealed metal objects is presented and discussed. It is shown that an indirect holographic method, usually employed at optical frequencies, can be adapted to image objects at microwave frequencies. The practical results successfully demonstrate that this technique can be used to determine the location and shape of the concealed object. © 2005 Wiley Periodicals, Inc. Microwave Opt Technol Lett 47: 536–537, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.21222

Survey of Worldwide High-Power Wideband Capabilities

Wideband and ultrawideband (UWB) technologies have achieved notable progress in recent years, aided immeasurably by improvements in solid-state manufacturing, computers, and digitizers. As a result, wideband systems that were difficult or impossible to implement ten years ago are now being built for an increasingly wide variety of applications including transient radar, concealed object detection, mine clearing, pipeline inspections, archeology, geology, electronic effects testing, and communications. In this paper, we discuss current wideband source technology around the world as well as laboratory and test facilities. We also will briefly touch on frequency limitations of anechoic chambers, design of transmission line simulators, frequency regulation requirements for outdoor ranges, and personnel exposure limits.

JOLT: a highly directive, very intensive, impulse-like radiator

Ultrawideband (UWB) systems that radiate very high-level transient waveforms and exhibit operating bandwidths of over two decades are now in demand for a number of applications. Such systems are known to radiate impulse-like waveforms with rise times around 100 ps and peak electric field values of tens of kilovolts per meter. Such waveforms, if properly radiated, will exhibit an operating spectrum of over two decades, making them ideal for applications such as concealed object detection, countermine, transient radar, and communications. In this paper, we describe a large, high-voltage transient system built at the Air Force Research Laboratory, Kirtland AFB, NM, from 1997 to 1999. The pulsed power system centers around a very compact resonant transformer capable of generating over 1 MV at a pulse-repetition frequency of /spl sim/ 600 Hz. This is switched, via an integrated transfer capacitor and an oil peaking switch onto an 85-/spl Omega/ half-impulse radiating antenna. This unique system will deliver a far radiated field with a full-width at half-maximum on the order of 100 ps, and a field-range product (rE/sub far/) of /spl sim/ 5.3 MV, exceeding all previously reported results by a factor of several.