<title>Landmine detection using a time-sequence of thermal infrared images</title>

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Thermal Infrared (TIR) techniques have some interesting capabilities that may assist in the detection of shallowly buried objects, in particular to help in the identification of landmine contaminated areas. The working principle of the sensor is the measurement of the thermal contrast on the soil surface, caused by the disturbance of the thermal flow due to the presence of the buried object with respect to the surroundings. This paper presents some preliminary results for the detection of buried antipersonnel landmines (APLs) with a thermal infrared imaging system. We describe an algorithm for the detection of landmine candidates by exploiting features in the image associated with the observed thermal contrast. Different threshold levels are applied to select groups of pixels that correspond to hot formations in the image, and are the ones that could indicate a target position. A logical AND combination that is then applied to the produced binary images, and can deliver an acceptable performance for landmine detection. However the method cannot distinguish landmine candidates from background variations sharing similar spatial patterns. Since the performance of the method depends strongly on the environmental conditions, a time series measurement is potentially a more promising approach to the whole problem of thermal IR measurement of buried objects. The time series of the IR data set presented in this paper was collected from the test lanes of JRC in Ispra, Italy, in the framework of the Multi-sensor Mine-signature (MsMs) measurement project.