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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Bibliographic Details
Published in:IET image processing Vol. 12; no. 8; pp. 1292 - 1302
Main Authors: Zeng, Dongdong, Zhu, Ming, Xu, Fang, Zhou, Tongxue
Format: Journal Article
Language:English
Published: The Institution of Engineering and Technology 01.08.2018
Subjects:
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
Online Access:Get full text
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Summary: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