High detection performance is required for an operational system for the detection of landmines. Humanitarian de-mining scenarios, combined with inherent difficulties of detecting landmines on an operational (vibration, motion, atmosphere) as well as a scenario level (clutter, soil type, terrain), result in high levels of false alarms for most sensors. To distinguish a landmine from background clutter one or more discriminating object features have to be found. The research described here focuses on finding and evaluating one or more features to distinguish disk-shaped landmines from background clutter in infrared images. These images were taken under controlled conditions, with homogenous soil types. Two methods are considered to acquire shape-based features in the infrared imagery. The first method uses a variation of the Hough transformation to find circular shaped objects. The second method uses the tophat filter with a disk-shaped structuring element. Furthermore, Mahalanobis and Fisher based classifiers are used to combine these features.@en

A specular model has been used to predict the passive polarimetric infrared (IR) signature of surface-laid landmines. The signature depends on the temperature of the landmine and the sky radiance. The temperature of the landmine is measured using a thermocouple. The signature itself is measured using a polarimetric IR camera setup. The predictions are fit to the measurements using the refractive index as an optimization parameter. The obtained refractive indices of each landmine type are consistent, but for the PMN landmine much lower than determined in a previous indoor experiment. Throughout the measurement day, the average landmine polarimetric signature was higher than the average background signature. Moreover the polarimetric signature appears to be a more robust indicator of the shape of the landmine's top surface than the normal IR signature. A simulator of passive polarimetric imagery is also being developed. That work is based on a physical model for both the thermal and radiometric processes, and it includes a finite-element solution for the heat transfer problem, ray tracing to describe the incident sunlight and the effects of shadowing, and analytical models for the Mueller matrices of rough dielectric surfaces. Preliminary results from that model show substantial qualitative agreement with measured images. A specular model has been used to predict the passive polarimetric infrared (IR) signature of surface-laid landmines. The signature depends on the temperature of the landmine and the sky radiance. The temperature of the landmine is measured using a thermocouple. The signature itself is measured using a polarimetric IR camera setup. The predictions are fit to the measurements using the refractive index as an optimization parameter. The obtained refractive indices of each landmine type are consistent, but for the PMN landmine much lower than determined in a previous indoor experiment. Throughout the measurement day, the average landmine polarimetric signature was higher than the average background signature. Moreover the polarimetric signature appears to be a more robust indicator of the shape of the landmine's top surface than the normal IR signature. A simulator of passive polarimetric imagery is also being developed. That work is based on a physical model for both the thermal and radiometric processes, and it includes a finite-element solution for the heat transfer problem, ray tracing to describe the incident sunlight and the effects of shadowing, and analytical models for the Mueller matrices of rough dielectric surfaces. Preliminary results from that model show substantial qualitative agreement with measured images.@en

Linear polarization of thermal infrared (TIR) radiation occurs when radiation is reflected or emitted from a smooth surface (such as the top of a landmine) and observed from a grazing angle. The background (soil and vegetation) is generally much rougher and therefore shows less pronounced linearly polarized radiation. This difference in polarization is utilized to enhance detection of landmines using TIR cameras. A setup has been constructed for the acquisition of polarized TIR images. This setup contains a polarization filter that rotates synchronously to the frame sync of the camera. Either a long wave infrared (LWIR) or a mid wave infrared (MWIR) camera can be mounted behind the rotating polarization filter. The synchronization allows a sequence of images to be taken with a predefined constant angle of rotation between the images. Using this image sequence, three independent Stokes images are calculated, consisting of the unpolarized radiance, the difference between vertically and horizontally polarized radiances, and the difference between the two diagonally polarized radiances. A model has been developed that describes the polarization due to reflection of and emission from a smooth surface. This model predicts the linear polarization for a landmine ``illuminated¿¿ by a source that is either hotter or cooler than the surface of the landmine. The measurement setup has been used to validate the model. The measurements agree well with the model predictions and can be used for estimating the real part of the refractive index of the rubber surface of the landmine. Besides the indoor measurement, outdoor measurements have also been performed. The results of these measurements show that under the given conditions the majority of landmines can be observed in the polarized radiance, whereas they are not clearly visible in the normal (unpolarized) radiance or the visual image. Subject terms: infrared polarization model; measurement setup; measurements; landmine detection.@en

Several sensor fusion approaches are in use for detection of land mines. These are based on different techniques and show different results. Meaningful comparisons of fusion algorithm performance are difficult, because the performance achievable may be limited by the data acquired and the sensors used. Especially in comparing such dissimilar situations, it is important to compare measures that are not dependent of sensor peculiarities or layout of test lanes. Nonetheless, a quantitative comparison of algorithms is necessary to identify the most effective fusion techniques. This comparison must sometimes be done when the algorithms are being applied to different data sets. In this paper we describe a methodology to evaluate the performance of sensor-fused mine-detection systems. This process can be used to compare different minedetecting sensors in well-defined scenarios. Keywords: Mine detection, sensor fusion, test and evaluation methodologies, system design.@en