15 October 1993 Probabilistic IR modeling for Bayesian automatic object recognition
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Abstract
Based upon the requirements of Bayesian object recognition theory, this paper provides the fundamental framework to determine the joint probability density function of object regions in an IR image. This probability function contains all information about the region that is required to achieve minimum probability of error recognition. The techniques advanced here are expected to be of significant use in certain rather hostile and difficult situations such as testing piping for fault conditions within operational nuclear power plants.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rufus H. Cofer, Samuel Peter Kozaitis, "Probabilistic IR modeling for Bayesian automatic object recognition", Proc. SPIE 1960, Automatic Object Recognition III, (15 October 1993); doi: 10.1117/12.160595; https://doi.org/10.1117/12.160595
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