Bayesian network using edge probabilities for target detection and recognition

Renjian Zhao; Patrick A. Kelly; Haluk Derin

doi:10.1117/12.436957

16 August 2001 Bayesian network using edge probabilities for target detection and recognition

Renjian Zhao, Patrick A. Kelly, Haluk Derin

Proceedings Volume 4380, Signal Processing, Sensor Fusion, and Target Recognition X; (2001) https://doi.org/10.1117/12.436957
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

Abstract

It has been noted recently that, in a number of applications, effective approximations to complex posterior probabilities can be computed through the framework of probability propagation in Bayesian networks. In this paper, we develop a Bayesian network for the problem of target detection and recognition. Our multiply-connected Bayesian network is based on a distribution decomposition of the form p(y,t,e)=p(y|t,e)p(t|e)p(e), where y is an observed image, t is a set of target pixels together with identifying labels, and e is a set of edge pixels. Running a probability propagation algorithm on this network leads to an approximation of the desired posterior probability p(t|y) as a product of terms that correlate the conditional observation distribution p(y|t,e) and target distribution p(t|e) with a posterior edge distribution p(e|y). We describe approaches for generating the required posterior edge distribution and for calculating the correlations through template matching. The result is a computationally-efficient algorithm for computing posterior target probabilities that can be used either to generate hard decisions or for fusion with other information. Target detection based on the posterior probability p(t|y) is discussed in the paper.

Citation Download Citation

Renjian Zhao, Patrick A. Kelly, and Haluk Derin "Bayesian network using edge probabilities for target detection and recognition", Proc. SPIE 4380, Signal Processing, Sensor Fusion, and Target Recognition X, (16 August 2001); https://doi.org/10.1117/12.436957

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