Algorithm Overview Based On Image Processing with Electromagnetic (EM) Techniques in X Band and GA Approach for Depth Estimation of Shallow Burried Dummy Mines

Detection of buried landmines and estimation of depth by modeling layered media is a complex and computationally intensive task. Microwave remote sensing with the capability to penetrate subsurface and its ability to resolve landmines as well as non-lethal targets can therefore be used for subsurface landmine detection. A model based on electromagnetic scattering and image analysis techniques at X-band frequency for sub-surface detection of dummy landmines buried under a sand layer and estimation of its depth has been proposed in this paper. An extensive set of lab experiments have been carried out using dummy landmines (without explosives) and backscatter observed at different depths. The raw data is processed through a series of image processing steps, the detection is carried out using Otsu´s thresholding and the depth estimated by optimizing through a GA (genetic algorithm) based electromagnetic model developed. The method does not have any requirement of separate training and test data set to train the optimizer and validate the results. The results under laboratory conditions indicate that detection of dummy landmines is possible using thresholding techniques with data generated in X band and the proposed model is capable of estimating depth of the buried landmine to a significant accuracy.