Identification of landmines in thermal infrared images

This paper explores the detection of landmines using thermal images acquired in military context. The conditions in which the images are obtained have a direct influence on the methods used to perform the automatic detection of landmines through image processing techniques. The proposed methodology follows two main phases: acquisition of thermal images and its processing. In the first phase, four different experiences were prepared to analyze the factors that influence the quality of the detection. In the second phase was conducted the image processing on a set of images based on classification techniques using the K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) algorithms. The classification was performed on a set of features extracted from ROI’s obtained by a sliding window. A second approach was also implemented based on segmentation using thresholds. The results achieved allow to identify factors that influence the detection of the mines: the burial depth, the presence of vegetation on the surface and the time of the day at which images were obtained. The optimal classification was obtained with the KNN classifier with 40 features selected with Sequential Backward Selection (SBS), and using the distance metric of correlation.info:eu-repo/semantics/publishedVersio

Modeling and performance estimation for airborne minefield detection system

Many programs aimed at airborne mine and minefield detection are being pursued and different algorithms are being developed and evaluated to achieve performance specifications. Thus far, no single algorithm or detection architecture has been able to fulfill the performance specifications for different mine and minefield detection scenarios...a need exists for a simulation based approach. One such simulation system is developed and evaluated in this thesis. The factors affecting the performance of an airborne detection system include physical parameters (type of background, time of day), data collection parameters (swath width, number of steps, in-step and in-flight overlap), and minefield scenarios. Data collection parameters are included in the simulation tool. False alarms and mine statistics are modeled based on the available data collected as a part of the developmental programs. Various mine and minefield detection algorithms are modeled and evaluated. Simulations are run, and Receiver Operating Characteristic (ROC) curves are used to evaluate the performance at both the mine and minefield levels. Analytical models for minefield detection performance are formulated and used to validate the simulated performance --Abstract, page iii

InSAR Coherence and Intensity Changes Detection

This research aims at differentiating human-induced effects over the landscape from the natural ones by exploiting a combination of amplitude and phase changes in satellite radar images. At a first step, ERS and Envisat data stacks are processed using COS software developed by the company SARMAP. Various features related to amplitude and phase as well as to their changes are then extracted from images of the same sensor. Combinations of the features extracted from one image, from several images of one sensor as well as from different sensors are performed to derive robust indicators of potential human-related changes. Finally, possibilities of exploiting and integrating other types of information sources such as various reports, maps, historical or agricultural data, etc. in the combination process are analyzed to improve the obtained results. The outcomes are used to evaluate the potential of this method applied to Sentinel-1 images

Guidebook on Detection Technologies and Systems for Humanitarian Demining

The aim of this publication is to provide the mine action community, and those supporting mine action, with a consolidated review and status summary of detection technologies that could be applied to humanitarian demining operations. This Guidebook is meant to provide information to a wide variety of readers. For those not familiar with the spectrum of technologies being considered for the detection of landmines and for area reduction, there is a brief overview of the principle of operation for each technology as well as a summary listing of the strengths, limitations, and potential for use of the technology to humanitarian demining. For those with an intermediate level of understanding for detection technologies, there is information regarding some of the more technical details of the system to give an expanded overview of the principles involved and hardware development that has taken place. Where possible, technical specifications for the systems are provided. For those requiring more information for a particular system, relevant publications lists and contact information are also provided

The Journal of Conventional Weapons Destruction Issue 21.1 (2017)

Feature: Improvised Explosive Devices (IED) and Pressure Plate IED\u27s Spotlight: Bosnia and Herzegovina 2- years later Field Notes Research and Developmen

Remote Sensing for Non‐Technical Survey

This chapter describes the research activities of the Royal Military Academy on remote sensing applied to mine action. Remote sensing can be used to detect specific features that could lead to the suspicion of the presence, or absence, of mines. Work on the automatic detection of trenches and craters is presented here. Land cover can be extracted and is quite useful to help mine action. We present here a classification method based on Gabor filters. The relief of a region helps analysts to understand where mines could have been laid. Methods to be a digital terrain model from a digital surface model are explained. The special case of multi‐spectral classification is also addressed in this chapter. Discussion about data fusion is also given. Hyper‐spectral data are also addressed with a change detection method. Synthetic aperture radar data and its fusion with optical data have been studied. Radar interferometry and polarimetry are also addressed