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  • Research Article
  • Open Access

Local Histogram of Figure/Ground Segmentations for Dynamic Background Subtraction

EURASIP Journal on Advances in Signal Processing20102010:782101

  • Received: 23 October 2009
  • Accepted: 9 June 2010
  • Published:


We propose a novel feature, local histogram of figure/ground segmentations, for robust and efficient background subtraction (BGS) in dynamic scenes (e.g., waving trees, ripples in water, illumination changes, camera jitters, etc.). We represent each pixel as a local histogram of figure/ground segmentations, which aims at combining several candidate solutions that are produced by simple BGS algorithms to get a more reliable and robust feature for BGS. The background model of each pixel is constructed as a group of weighted adaptive local histograms of figure/ground segmentations, which describe the structure properties of the surrounding region. This is a natural fusion because multiple complementary BGS algorithms can be used to build background models for scenes. Moreover, the correlation of image variations at neighboring pixels is explicitly utilized to achieve robust detection performance since neighboring pixels tend to be similarly affected by environmental effects (e.g., dynamic scenes). Experimental results demonstrate the robustness and effectiveness of the proposed method by comparing with four representatives of the state of the art in BGS.


  • Detection Performance
  • Candidate Solution
  • Background Subtraction
  • Background Model
  • Neighboring Pixel

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Authors’ Affiliations

Department of Computer Science and Engineering, Harbin Institute of Technology, No.92, West Da-Zhi Street, Harbin, Heilongjiang, 150001, China
National Laboratory of Pattern Recognition, Institute of Automation, CAS, Beijing, 100080, China


© Bineng Zhong et al. 2010

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.