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Abstract

An automated system and/or method is disclosed for rapidly, accurately, and efficiently processing bulk three-dimensional digital image data of both path/corridor and area scenes to discriminate different structures or classifications of objects from within the image. The method first decomposes the three-dimensional digital imagery coordinate points into simple local structures and then extracts the globally complex structures from the local structures. The system and/or method incorporates procedures for sub-dividing the three-dimensional image data into rectilinear and/or ellipsoidal finite element cells, mathematically analyzing the contents (point coordinates) of each individual cell to classify/define the local structure, and extracting the globally complex structure or object from the image. The system and/or method applies accepted mathematical formulas to filter or classify large volumes of apparently random three-dimensional point coordinate spatial data into simpler structures and then to extract more globally complex objects generally encountered within the real world imagery scene being investigated.

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First Claim