Extended fuzzy background modeling for moving vehicle detection using infrared vision

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概要

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• Running average is a simple and effective background modeling method that generates adaptive background image for moving object detection. Fuzzy Running Average (FRA) improves the selectivity of Standard Running Average (SRA). However, its background restoration rate is slow. This leads to false object detection when a static object becomes dynamic. To overcome this problem, an Extended Fuzzy Running Average (EFRA) is proposed. The results show that the EFRA not only retains the selectivity benefit of FRA, but also improves the restoration rate significantly.

著者

• Kit Wong

  Faculty of Engineering and Technology, Multimedia University

• Chin Yeo

  Faculty of Engineering and Technology, Multimedia University

• Soong Lim

  Faculty of Engineering and Technology, Multimedia University

• Siong Lim

  Faculty of Engineering and Technology, Multimedia University

関連論文

• Extended fuzzy background modeling for moving vehicle detection using infrared vision
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