Title
A parallel algorithm for target recognition using a multi-class hash database
Keywords
Basis pair; Geometric hashing; Hash table; Hash table image; Transformation invariant
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.
Publication Date
12-1-1998
Publication Title
Proceedings of SPIE - The International Society for Optical Engineering
Volume
3374
Number of Pages
158-166
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1117/12.327093
Copyright Status
Unknown
Socpus ID
0032337676 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0032337676
STARS Citation
Uddin, Mosleh and Myler, Harley R., "A parallel algorithm for target recognition using a multi-class hash database" (1998). Scopus Export 1990s. 3654.
https://stars.library.ucf.edu/scopus1990/3654