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Proceedings Paper

Parallel algorithm for target recognition using a multiclass hash database
Author(s): Mosleh Uddin; Harley R. Myler
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Paper Abstract

A method for recognition of unknown targets using large databases of model targets is discussed. Our approach is based on parallel processing of multi-class hash databases that are generated off-line. A geometric hashing technique is used on feature points of model targets to create each class database. Bit level coding is then performed to represent the models in an image format. Parallelism is achieved during the recognition phase. Feature points of an unknown target are passed to parallel processors each accessing an individual class database. Each processor reads a particular class of hash data base and indexes feature points of the unknown target. A simple voting technique is applied to determine the best match model with the unknown. The paper discusses our technique and the results from testing with unknown FLIR targets.

Paper Details

Date Published: 17 July 1998
PDF: 9 pages
Proc. SPIE 3374, Signal Processing, Sensor Fusion, and Target Recognition VII, (17 July 1998); doi: 10.1117/12.327093
Show Author Affiliations
Mosleh Uddin, Univ. of Central Florida (United States)
Harley R. Myler, Univ. of Central Florida (United States)

Published in SPIE Proceedings Vol. 3374:
Signal Processing, Sensor Fusion, and Target Recognition VII
Ivan Kadar, Editor(s)

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