Abstract: In this thesis, a possibilistic K-nearest neighbor classifier is presented to distinguish between and classify mine and non-mine targets on data obtained from wideband electromagnetic induction sensors. The goal of this work is to develop methods for classifying wide-band… Read More
Tag: landmine
Vegetation mapping for landmine detection using long-wave hyperspectral imagery
Abstract: We develop a vegetation mapping method using long-wave hyperspectral imagery and apply it to landmine detection. The novel aspect of the method is that it makes use of emissivity skewness. The main purpose of vegetation detection for mine detection… Read More
SPICE: a sparsity promoting iterated constrained endmember extraction algorithm with applications to landmine detection from hyperspectral imagery
Abstract: An extension of the Iterated Constrained Endmembers (ICE) algorithm that incorporates sparsity promoting priors to find the correct number of endmembers is presented. In addition to solving for endmembers and endmember fractional maps, this algorithm attempts to autonomously determine… Read More
Sensor fusion for airborne landmine detection
Abstract: Sensor fusion has become a vital research area for mine detection because of the countermine community’s conclusion that no single sensor is capable of detecting mines at the necessary detection and false alarm rates over a wide variety of… Read More
Multi-sensor and algorithm fusion with the choquet integral: applications to landmine detection
Abstract: We discuss the application of Choquet integrals to multi-algorithm and multi-sensor fusion in landmine detection. Choquet integrals are defined. Specific classes of measures, the full and Sugeno measures, are described. Full measures are optimized via quadratic programming. A steepest… Read More