C-EFIC: Color and Edge Based Foreground Background Segmentation with Interior Classification

  • Gianni AlleboschEmail author
  • David Van Hamme
  • Francis Deboeverie
  • Peter Veelaert
  • Wilfried Philips
Part of the Communications in Computer and Information Science book series (CCIS, volume 598)


The detection of foreground regions in video streams is an essential part of many computer vision algorithms. Considerable contributions were made to this field over the past years. However, varying illumination circumstances and changing camera viewpoints provide major challenges for all available algorithms. In this paper, a robust foreground background segmentation algorithm is proposed. Both Local Ternary Pattern based edge descriptors and RGB color information are used to classify individual pixels. Furthermore, camera viewpoints are detected and compensated for. We will show that this algorithm is able to handle challenging conditions and achieves state-of-the-art results on the comprehensive ChangeDetection.NET 2014 dataset.


Foreground background segmentation Moving edges Illumination invariance Camera motion compensation 



We would like to thank the creators of ChangeDetection.NET and all those responsible for providing the means to evaluate our foreground background estimation algorithm on this very comprehensive dataset.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Gianni Allebosch
    • 1
    Email author
  • David Van Hamme
    • 1
  • Francis Deboeverie
    • 1
  • Peter Veelaert
    • 1
  • Wilfried Philips
    • 1
  1. 1.Department of Telecommunications and Information Processing, Image Processing and InterpretationGhent University - iMindsGentBelgium

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