Multi-sensor image interpretation using laser radar and thermal images

The authors present a knowledge-based system called AIMS (automatic interpretation system using multiple sensors) to interpret registered laser radar and thermal images. The objective is to detect and recognize man-made objects at kilometer range in outdoor scenes. Various sensing modalities (range, intensity, velocity, and thermal) are used to improve both image segmentation and interpretation. Low-level attributes of image segments (regions) are computed by the segmentation modules and then converted to databases in the KEE format. KEE is a commercial package for expert system shell development. The interpretation system applies forward chaining to derive object-level interpretations from databases. Segments are grouped into objects and then objects are classified into predefined categories. AIMS transfers nonsymbolic processing tasks to a concurrent service manager (program). Therefore, tasks with different characteristics are executed using different software tools and methodologies. Experimental results using real data are presented.<
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