Infrared Detection of Buried Land Mines Based on Texture Modeling

Paper in proceeding, 2001

A parametric model for the infrared signature caused by a buried land mine is presented. Further, two ways of modeling the colored background noise, is proposed. In the first, it is assumed the noise can be approximated by an autoregressive process, while in the second, the statistics of the noise is described using recent development in texture modeling, the so called FRAME method. Given an a priori distribution of the mine parameters in combination with a trained noise distribution, a Bayesian detector is derived. Experiments indicate that significant gains in performance can be achieved as compared to the standard detector used, which correlates the infrared image with the known mine shape and thresholds the square of the output.