Abstract: Substantial interest resides in identifying sensors, algorithms and fusion theories to detect buried explosive hazards. This is a significant research effort because it impacts the safety and lives of civilians and soldiers alike. Herein, we explore the fusion of… Read More
Tag: landmine
LBP Features for Hand-Held Ground Penetrating Radar
Abstract: Ground penetrating radar (GPR) has the ability to detect buried targets with little or no metal content. Achieving superior detection performance with a hand-held GPR can be very challenging due to the quality of the data, inconsistency of target… Read More
Fourier Features for Explosive Hazard Detection using a Wideband Electromagnetic Induction Sensor
Abstract: Sensors which use electromagnetic induction (EMI) to excite a response in conducting bodies have been investigated for the purpose of detecting buried explosives. In particular, wide band EMI sensors which use a relatively low number of operating frequencies have… Read More
Binary Fuzzy Measures and Choquet Integration for Multi-Source Fusion
Abstract: Countless challenges in engineering require the intelligent combining (aka fusion) of data or information from multiple sources. The Choquet integral (ChI), a parametric aggregation function, is a well-known tool for multisource fusion, where source refers to sensors, humans and/or… Read More
Genetic Programming Based Choquet Integral for Multi-Source Fusion
Abstract: While the Choquet integral (ChI) is a powerful parametric nonlinear aggregation function, it has limited scope and is not a universal function generator. Herein, we focus on a class of problems that are outside the scope of a single… Read More
Adaptive coherence estimator (ACE) for explosive hazard detection using wideband electromagnetic induction (WEMI)
Abstract: The adaptive coherence estimator (ACE) estimates the squared cosine of the angle between a known target vector and a sample vector in a whitened coordinate space. The space is whitened according to an estimation of the background statistics, which… Read More
Buried object detection using handheld WEMI with task-driven extended functions of multiple instances
Abstract: Many effective supervised discriminative dictionary learning methods have been developed in the literature. However, when training these algorithms, precise ground-truth of the training data is required to provide very accurate point-wise labels. Yet, in many applications, accurate labels are… Read More
On the use of log-gabor features for subsurface object detection using ground penetrating radar
Abstract: Handheld ground penetrating radar (GPR) enables the detection of subsurface objects under different terrains or over regions with significant amount of metal debris. The challenge for the handheld GPR is to reduce the false alarm rate and limit the… Read More
Anomaly detection of subsurface objects using handheld ground-penetrating radar
Abstract: This paper develops an anomaly detection algorithm for subsurface object detection using the handheld ground penetrating radar. The algorithm is based on the Mahalanobis distance measure with adaptive update of the background statistics. It processes the data sequentially for… Read More
Landmine classification using possibilistic K-nearest neighbors with wideband electromagnetic induction data
Abstract: A possibilistic K-Nearest Neighbors classifier is presented to classify mine and non-mine objects using data collected from a wideband electromagnetic induction (WEMI) sensor. The proposed classifier is motivated by the observation that buried objects often have consistent signatures depending… Read More