Hierarchical Recognition Process For Structural Target Analysis

Harry C. Lee; Albert R. Sanders

doi:10.1117/12.944842

4 December 1984 Hierarchical Recognition Process For Structural Target Analysis

Harry C. Lee, Albert R. Sanders

Proceedings Volume 0504, Applications of Digital Image Processing VII; (1984) https://doi.org/10.1117/12.944842
Event: 28th Annual Technical Symposium, 1984, San Diego, United States

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.

Citation Download Citation

Harry C. Lee and Albert R. Sanders "Hierarchical Recognition Process For Structural Target Analysis", Proc. SPIE 0504, Applications of Digital Image Processing VII, (4 December 1984); https://doi.org/10.1117/12.944842

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Target recognition

Image processing

Digital image processing

Image segmentation

Image resolution

Stochastic processes

Stars

Show All Keywords

Keywords/Phrases

Search In:

Publication Years