Position-independent ATR using hierarchical hidden Markov model as the identification algorithm

Andre Sokolnikov

doi:10.1117/12.2017037

10 June 2013 Position-independent ATR using hierarchical hidden Markov model as the identification algorithm

Andre Sokolnikov

Proceedings Volume 8744, Automatic Target Recognition XXIII; 87440B (2013) https://doi.org/10.1117/12.2017037
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

A recursive algorithm based on hidden Markov models is used to build a model of the identification target. The end result of the recursive matching is an optimal scene-to-model transformation, along with a recognition degree of suitability value between the scene and the model. The hierarchical structure of the model allows a maximization of the target identification probability.

Citation Download Citation

Andre Sokolnikov "Position-independent ATR using hierarchical hidden Markov model as the identification algorithm", Proc. SPIE 8744, Automatic Target Recognition XXIII, 87440B (10 June 2013); https://doi.org/10.1117/12.2017037

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