Use of an application-specific dictionary for matching pursuits discrimination of landmines and clutter

The HSTAMIDS handheld landmine detection system has been used in a number of humanitarian demining activities. Existing algorithms used with this system to assist human in discrimination process do a better job than the operator alone. However, they are unable to model mine and clutter signatures completely, leading to inaccurate mine confidence assignment. This paper presents a matching pursuits (MP) based landmine detection system using an application-specific dictionary. Prototypes for mine and clutter classes are built using MP decomposition of class members. A fuzzy K-nearest neighbor rule is used to assign confidence values for mine and clutter discrimination. The proposed algorithm is demonstrated on data acquired from three different landmines test sites.