Green Communications and Networks pp 867-875 | Cite as
An Improved Approach for Moving Object Detection Based on Markov Random Field
Abstract
Due to utilization of the relativity of every pixel of an image, the Markov random field (MRF) model is effective in solving the problem of detecting moving objects under a complex background. In this paper, the bits-segmentation of inter-frame difference images is used as the label field of MRF, and the compatibility function related to such labels and the hidden states is provided, so that an improved detection method for moving objects is proposed based on MRF. Compared with the traditional MRF method, the proposed approach can avoid the threshold selection process for obtaining the label field, which is a sensitive issue that may affect the detection negatively. The experiment results show that this approach is more effective and has a better adaptability than traditional methods.
Keywords
Markov random filed Inter-frame difference images Moving object detecting Belief propagationReferences
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