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Proceedings Paper

Multi-parametric data fusion for enhanced object identification and discrimination
Author(s): Stephen Kupiec; Vladimir Markov; Joseph Chavez
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Paper Abstract

Effective fusion of multi-parametric heterogeneous data is essential for better object identification, characterization and discrimination. In this report we discuss a practical example of fusing the data provided by imaging and nonimaging electro-optic sensors. The proposed approach allows the processing, integration and interpretation of such data streams from the sensors. Practical examples of improved accuracy in discriminating similar but non-identical objects are presented.

Paper Details

Date Published: 23 May 2013
PDF: 10 pages
Proc. SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, 87450W (23 May 2013); doi: 10.1117/12.2016519
Show Author Affiliations
Stephen Kupiec, Advanced Systems & Technologies, Inc. (United States)
Vladimir Markov, Advanced Systems & Technologies, Inc. (United States)
Joseph Chavez, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 8745:
Signal Processing, Sensor Fusion, and Target Recognition XXII
Ivan Kadar, Editor(s)

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