Asian Journal of Information Technology

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An HMM-Based Model for Moving Object Detection

A.R. Debilou and S. Aouragh
Page: 1034-1038 | Received 21 Sep 2022, Published online: 21 Sep 2022

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Abstract

A new probabilistic background-foreground model based on Hidden Markov Models (HHMs) is presented. The hidden states of the model enable discrimination between Foreground and Background. This method is composed of two phases. First, an ICE (Iterative Conditional Estimation) algorithm is introduced to learn the unknown HMM parameters. In the second stage, each pixel is classified with an MPM (Maximum Posterior Marginal) classification algorithm. The potential and efficiency of the method have been proven through simulations under Matlab.

How to cite this article:

A.R. Debilou and S. Aouragh . An HMM-Based Model for Moving Object Detection.
DOI: https://doi.org/10.36478/ajit.2006.1034.1038
URL: https://www.makhillpublications.co/view-article/1682-3915/ajit.2006.1034.1038