Temporal analysis for land mine detection

Abstract

In this paper the FOI temporal analysis method is presented and tested on images randomly chosen from a diurnal sequence. The method integrates data collection, both sensor images and weather, as well as modelling, with the signal processing detection methods. The detection methods presented show that mines can be detected using optical methods, even when the image sequence show very little contrast. Increasing the number of data collection times affects the detection rate and false alarm rate in a positive way. The result from the test with randomly chosen images show performance better than random for all of the tested cases, excellent for some cases. Using prior knowledge in the choice of time of data collection, the result from testing the method on real mine field data shows interesting result.