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A Background Subtraction and Post-Processing for Effective Foreground Object Detection

  • Journal of Knowledge Information Technology and Systems
  • Abbr : JKITS
  • 2011, 6(6), pp.143-150
  • Publisher : Korea Knowledge Information Technology Society
  • Research Area : Interdisciplinary Studies > Interdisciplinary Research
  • Published : December 31, 2011

Young-Sub Kim 1 박종대 1 Kwangseok Lee 2 고시영 3 Hur Kang In 1

1동아대학교
2경남과학기술대학교
3경일대학교

Candidate

ABSTRACT

This paper is studies on object detection using background subtraction techniques and effective post-processing technique on detected objects. AMF(Approximated Median Filtering) as a typical background subtraction technique is effective to processing time and memory use by recursive technique. But it generates loss on the interior of object and processing time slow because of process of positively curved region. To overcome problems, this paper is proposed to modified AMF and we prove a superiority of modified AMF by performance evaluations of adaptive Gaussian mixture model and Eigen-background. Also, to precisely rapidly detect objects, we propose a effective post-processing method on a binary foreground segmentation mask acquired through a proposed background subtraction techniques and prove through experiments.

Citation status

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