Multi-Stage Sensor Fusion for Landmine Detection

This paper proposes a multi-stage approach for landmine detection. It is based on a feature-level data fusion which combines data from several nonspecific sensors. The sensor fusion process is analysed and divided in three stages in order to improve the final result. During the first stage all suspected objects are detected against a background. Then, the detected objects are classified to be a man-made or natural object. And, finally, the landmines are distinguished among the identified manmade objects. The last two stages are described in detail in this paper, demonstrating the advantages for their separation. Classification features, which enable the sensor fusion, are also presented in this work together with an approach for their integration. The proposed ideas are tested using real experimental data obtained from pulsed and continuous metal detectors, infrared camera and ground penetrating radar