David D. Ferris

Survey of current technologies for through-the-wall surveillance (TWS)

Recently, a survey was conducted for the Joint Project Steering Group (JPSG) of the National Institute of Justice (NIJ) and Defense Advanced Project Research Agency (DARPA)to determine the state-of-the-art at the present time in through-the-wall surveillance (TWS) technology and the expected advances within the next 10 years. The applicable technologies for TWS include: impulse radar, UHF/microwave radar, millimeter wave radiometry, x-ray transmission and reflectance, and acoustics. Proposed sensors include: monostatic radar, bistatic (or multistatic) radar, radiometers, fixed antenna systems, scanning systems, and focal plane array systems. The ability to penetrate walls leads to a natural conflict between the desire to successfully penetrate walls, which implies lower frequencies and the desire to obtain maximum resolution, which implies higher frequencies. Another conflict involves sophistication of the sensor versus unit cost. These issues and the approaches taken by various developers to find workable solutions are discussed.

Concealed weapon detection using microwave and millimeter wave sensors

Recent advances in millimeter-wave (MMW), microwave, and infrared (IR) technologies provide the means to detect concealed weapons remotely through clothing and in some cases through walls. Since the development of forward-looking infrared (FLIR) instruments, work has been ongoing in attempting to use these devices for concealed weapon detection based on temperature differences between metallic weapons and the background body temperature of the person carrying the weapon; however, the poor transmission properties of clothing in the infrared has led to the development of techniques based on lower frequencies. Focal plane arrays operating at MMW frequencies are becoming available which eliminate the need for a costly and slow mechanical scanner for generating images. These radiometric sensors also detect temperature differences between weapons and the human body background. Holographic imaging systems operating at both microwave and MMW frequencies have been developed which generate images of near photographic quality through clothing and through thin, non-metallic walls. Finally, a real-aperture radar is useful for observing people and detecting weapons through walls and in the field under reduced visibility conditions.

Morphological filters and wavelet-based image fusion for concealed weapons detection

When viewing a scene for an object recognition task, one imaging sensor may not provide all the information needed for recognition. One way to obtain more information is to use multiple sensors. These sensors should provide images that contain complementary information about the same scene. After preprocessing the source images, we use image fusion to combine the information from the difference sensors. The images to be fused may have some details such as shadows, wrinkles, imaging artifacts, etc., that are not needed in the final fused image. One application of morphological filters is to remove objects of a given size range from the image. Therefore, we use morphological filters in conjunction with wavelets to improve the recognition performance after fusion. After morphological filtering, wavelets are used to construct multiresolution representations of the source images. Once the source images are decomposed, the details are combined to form a composite decomposed image. This method allows details at different levels to be combined independently so that important information is maintained in the final composite image. We are developing image fusion algorithms for concealed weapon detection (CWD) applications. Fusion is useful in situations where the sensor types have different properties, e.g., IR and MMW sensors. Fusing these types of images results in composite images which contain more complete information for CWD applications such as detection of concealed weapons on a person. In this paper we present our most recent results in this area.

Registration and fusion of infrared and millimeter wave images for concealed weapon detection

We present an approach to automatically register and fuse IR and MMW images for concealed weapon detection. The distortion between the two images is assumed to be a rigid body transformation without rotation and we assume that the scale factor can be found from both the sensor parameters and the distance ratio of the object to the two sensors. Our registration procedure involves image segmentation, binary correlation and other image processing algorithms. Our fusion method involves a pyramidal image decomposition scheme based on the wavelet transform. Performance of the image registration and image fusion algorithm is illustrated through an example.

Image processing tools for the enhancement of concealed weapon detection

A number of technologies are being developed for Concealed Weapon Detection (CWD). Use of appropriate processing techniques will be very important to the success of such technologies. This article describes digital image processing procedures currently being investigated to enhance the detection of weapons concealed underneath clothing.

Survey of image processing techniques applied to the enhancement and detection of weapons in MMW data

Several image processing procedures have been used for the enhancement and detection of weapons concealed underneath clothing in millimeterwave data. Specifically, registration, fusion, tracking, enhancement, segmentation, and recognition procedures have been successfully tested. These procedures are reviewed in this paper along with examples of their application.

Microwave and millimeter-wave systems for wall penetration

The need for through-the-wall surveillance sensors has existed for many years. Recent advances in microwave and millimeter-wave (MMW) technologies provide new applications for law enforcement use. These applications include the potential to conduct surveillance through walls and the ability to detect the presence of living persons behind doors or other barriers. Covert surveillance and personnel detection are of high interest to both the Department of Defense in support of Small Unit Operations and the Justice Department for civilian law enforcement applications. Microwave sensors are under development that can detect the presence of persons (and even weapons) behind walls and track moving persons behind walls. MMW sensors are under development which can provide pseudo-images of persons behind the walls including radiometric sensors at 95 GHz, active 95 GHz real aperture radars, and heartbeat detection radars. Radiometric sensors include 2D FPA systems, 1D FPA, scanned systems, and single element scanned sensors. Active FPA radars include illuminated radiometric systems and coherent radar systems. Real aperture MMW radar systems include raster scanned and non-scanned (hand-held) sensors.

New law enforcement applications of millimeter-wave radar

Recent advances in millimeter-wave (MMW) radar technologies provide new applications for law enforcement use over-and- above the venerable speed timing radar. These applications include the potential to detect weapons under clothing and to conduct surveillance through walls. Concealed Weapon Detection and covert surveillance are of high interest to both the Department of Defense in support of Small Unit Operations and the Justice Department for civilian law enforcement applications. MMW sensors are under development which should provide the needed capabilities including radiometric sensors at 95 GHz, active 95 GHz real aperture radars, active focal plane array (FPA) radars, and holographic radars. Radiometric sensors include 2D FPA systems, 1D FPA, scanned systems, and single element scanned sensors. Active FPA radars include illuminated radiometric systems and coherent radar systems. Real aperture MMW radar systems include raster scanned and conical scanned sensors. Holographic systems ruse mechanical scanners to collect coherent data over a significant solid angular sector.

Multi-scale decomposition tool for Content Based Image Retrieval

Content Based Image Retrieval (CBIR) is a technical area focused on answering “Who, What, Where and When,” questions associated with the imagery. A multi-scale feature extraction scheme based on wavelet and Contourlet transforms is proposed to reliably extract objects in images. First, we explore Contourlet transformation in association with Pulse Coupled Neural Network (PCNN) while the second technique is based on Rescaled Range (R/S) Analysis. Both methods provide flexible multi-resolution decomposition, directional feature extraction and are suitable for image fusion. The Contourlet transformation is conceptually similar to a wavelet transformation, but simpler, faster and less redundant. The R/S analysis, uses the range R of cumulative deviations from the mean divided by the standard deviation S, to calculate the scaling exponent, or a Hurst exponent, H. Following the original work of Hurst, the exponent H provides a quantitative measure of the persistence of similarities in a signal. For images, if information exhibits self-similarity and fractal correlation then H gives a measure of smoothness of the objects. The experimental results demonstrate that our proposed approach has promising applications for CBIR. We apply our multiscale decomposition approach to images with simple thresholding of wavelet/curvelet coefficients for visually sharper object outlines, salient extraction of object edges, and increased perceptual quality. We further explore these approaches to segment images and, the empirical results reported here are encouraging to determine who or what is in the image.

Sensors for military special operations and law enforcement applications

Improvement in the capabilities of infrared, millimeter- wave, acoustic, and x-ray, sensors has provided means to detect weapons concealed beneath clothing and to provide wide-area surveillance capability in darkness and poor light for military special operations and law enforcement application. In this paper we provide an update on this technology, which we have discussed in previous papers on this subject. We present new data showing simultaneously obtained infrared and millimeter-wave images which are especially relevant because a fusion of these two sensors has been proposed as the best solution to the problem of concealed weapon detection. We conclude that the use of these various sensors has the potential for solving this problem and that progress is being made toward this goal.