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Proceedings Paper

Hierarchical Recognition Process For Structural Target Analysis
Author(s): Harry C. Lee; Albert R. Sanders
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Paper Abstract

Pyramidal structures created from resolution sequences of imagery contain a hier-archical structure induced by the resolution function. Conversion of this pyramidal structure into a Resolution Syntax Tree (RST) lends itself to a hierarchical recognition process. The conversion is accomplished by creating a representation of the global and local connectivity of the internal structure segmentation at each level of the pyramid. The recognition process uniquely classifies targets by determining a structural similarity with a knowledge base. The analysis is a matching strategy that has its foundation in formal languages using a graph, theoretic approach. A stochastic metric is added to the recognition process to account for real-world variations. The recognition process begins by down-selecting the knowledge base into a working set using a priori knowledge of the image viewing geometry. The hierarchical recognition individually tests each entry in the working set against the target to determine a probability of structural similarity. The process begins at the root of the RST, which corresponds to the global information of the pyramidal structure. The segmentation of the internal structure produces a graph; the edges of the graph represent the boundaries found during segmentation, and the vertices are the endpoints of these boundaries. A structural match between a working set entry and the target is obtained by determining a subgraph common to both boundary graphs. The subgraph is found by forming a match in the bipartite graph developed from two sets of boundary graph vertices. A stochastic metric is derived based on the commonality of the subgraph to the two boundary graphs. The recognition process may be recursively applied to the next level of the RST, utilizing the level-to-level connectivity. Recursion is performed only as warranted by the stochastic metric determined at the previous level.

Paper Details

Date Published: 4 December 1984
PDF: 6 pages
Proc. SPIE 0504, Applications of Digital Image Processing VII, (4 December 1984); doi: 10.1117/12.944842
Show Author Affiliations
Harry C. Lee, Martin Marietta Orlando Aerospace (United States)
Albert R. Sanders, Martin Marietta Orlando Aerospace (United States)

Published in SPIE Proceedings Vol. 0504:
Applications of Digital Image Processing VII
Andrew G. Tescher, Editor(s)

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