A Hybrid Approach to Disturbed Soil and Mine Detection

"IAI and Prof. Chang of the University of Maryland at Baltimore County (UMBC), jointly propose a new hybrid framework for disturbed soil and mine detection using airborne images from two perspectives: spatial and spectral. The first approach is a spatialapproach, which mainly focuses on texture analysis. The idea is motivated by the fact that, the ground texture will be disturbed if mines are planted. By systematically looking the gray level changes in an airborne image, one can obtain texture patternsthat are unusual. This approach is applicable to EO, IR, hyperspectral, and SAR images. The second approach is a spectral approach and has two steps. First, a new automatic target generation process (ATGP) is used to generate a set of potential targets(mines) from the image data in an unsupervised fashion without using any prior knowledge. The ATGP idea originates from the concept of orthogonal subspace projection (OSP) in signal processing. Second, a novel Automatic Target Detection and ClassificationAlgorithm (ATDCA) is used to identify the potential mines. The algorithm can be used to detect anomalies (new and unknown mines) in blind environments. The algorithm is suitable for surveillance operations where the objective is to detect the presence ofany potential mines. The proposed algorithm will be useful for surveillance. The market for military applications is quite large. The Commercial marketplace for this algorithm may be equally