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Proceedings Paper

Performance analysis of a parallel target recognition architecture
Author(s): Arnold N. Pears; Melissa L. Ojczyk
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Paper Abstract

Previous research indicates that geometric hashing can provide a reliable and transformation independent representation of a target. The characterization of a target object is obtained by establishing a vector basis relative to a number of interest points unique to the target. The representation is invariant under both affine and geometric transformations of the target interest points. A previous paper discusses the complexity measures associated with task division and target image processing using geometric hashing. These measures were used to determine the areas which most benefit from implementation in hardware; and an architecture design for a high speed, hardware assisted, geometric hashing approach to target recognition was described. To confirm the performance of a parallel hardware approach to target recognition based on geometric hashing a complete component level simulation of the proposed hardware has been developed using OBJECTSIM. OBJECTSIM is an object oriented architecture modeling tool developed at La Trobe University for simulating concurrent systems. This paper describes the structure of the architecture and its simulation model in detail. Several hardware configurations are presented and their comparative performance evaluated for a suite of test images. The hardware performance specifications required for real time target recognition from video input are presented and discussed. The paper concludes that, on suitable images, real time target recognition can be achieved.

Paper Details

Date Published: 18 September 1998
PDF: 11 pages
Proc. SPIE 3371, Automatic Target Recognition VIII, (18 September 1998); doi: 10.1117/12.323858
Show Author Affiliations
Arnold N. Pears, La Trobe Univ. (Australia)
Melissa L. Ojczyk, La Trobe Univ. (Australia)

Published in SPIE Proceedings Vol. 3371:
Automatic Target Recognition VIII
Firooz A. Sadjadi, Editor(s)

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