Paper
23 May 2013 Multi-parametric data fusion for enhanced object identification and discrimination
Author Affiliations +
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.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stephen Kupiec, Vladimir Markov, and Joseph Chavez "Multi-parametric data fusion for enhanced object identification and discrimination", Proc. SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, 87450W (23 May 2013); https://doi.org/10.1117/12.2016519
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KEYWORDS
Sensors

Data fusion

Data modeling

Image fusion

Optical sensors

Printed circuit board testing

Electro optical sensors

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