An Improved Approach for Moving Object Detection Based on Markov Random Field

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 113)

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 propagation 

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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.School of Computer and InformationHefei University of TechnologyHefeiChina
  2. 2.Engineering Research Center of Safety Critical Industry Measure and Control TechnologyMinistry of EducationHefeiChina

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