Extended fuzzy background modeling for vehicle detection using infrared vision

Chin, Yeo Boon and Soong, Lim Way and Siong, Lim Heng and Kit, Wong Wai (2011) Extended fuzzy background modeling for vehicle detection using infrared vision. IEICE Electronics Express, 8 (6). pp. 340-345. ISSN 1349-2543

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Abstract

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.

Item Type: Article
Subjects: Q Science > Q Science (General)
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 19 Dec 2013 04:37
Last Modified: 19 Dec 2013 04:37
URI: http://shdl.mmu.edu.my/id/eprint/4615

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