Skip to Main Content
In this paper, we address the problem of the detection and identification of surface-laid and shallowly buried landmines from measured infrared images. A three-dimensional thermal model has been developed to study the effect of the presence of landmines in the thermal signature of the bare soil. Based on this model, a target identification procedure is proposed aiming at detecting and classifying the anomalies found on the soil thermal signature. In our approach, landmines are thought of as a thermal barrier in the natural flow of the heat inside the soil, which produces a perturbation of the expected thermal pattern on the surface. The detection of these perturbations will put into evidence the presence of potential mine targets. We propose an iterative procedure to classify the detected perturbations as mines or nonmines and to estimate their depth of burial. This paper describes the main principles of our method and illustrates classification results on a set of acquired images. Qualitative and quantitative comparisons with independent component analysis are also given.