Extended scale invariant local binary pattern for background subtraction

Background subtraction based on change detection is the first step in many video surveillance systems, an effective background subtraction algorithm should distinguish foreground from the background sensitively, and adapt to the variation of background scenes robustly. In this study, the authors pro...

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Vydáno v:	IET image processing Ročník 12; číslo 8; s. 1292 - 1302
Hlavní autoři:	Zeng, Dongdong, Zhu, Ming, Xu, Fang, Zhou, Tongxue
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	The Institution of Engineering and Technology 01.08.2018
Témata:	background scenes background sensitively effective background subtraction algorithm extended scale invariant local binary pattern feature extraction image colour analysis image segmentation image texture local texture features object detection photometric invariant colour measurement Research Article rich texture regions robust background subtraction algorithm video surveillance video surveillance systems well‐known change detection dataset effective background subtraction algorithm robust background subtraction algorithm object detection video surveillance systems image texture photometric invariant colour measurement background scenes local texture features well-known change detection dataset image segmentation feature extraction background sensitively rich texture regions image colour analysis video surveillance extended scale invariant local binary pattern
ISSN:	1751-9659, 1751-9667
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Shrnutí:	Background subtraction based on change detection is the first step in many video surveillance systems, an effective background subtraction algorithm should distinguish foreground from the background sensitively, and adapt to the variation of background scenes robustly. In this study, the authors propose a robust background subtraction algorithm which takes advantages of local texture features represented by an extended scale invariant local binary pattern and colour intensities to characterise pixel representations. Local texture features achieve good tolerance against illumination variations in rich texture regions but not so efficiently on uniform regions, so a photometric invariant colour measurement is proposed to overcome its limitation. Both quantitative and qualitative evaluations carried out on a well-known change detection dataset are provided to demonstrate the effectiveness of the proposed algorithm.
ISSN:	1751-9659 1751-9667
DOI:	10.1049/iet-ipr.2016.1026