Performance analysis of Lab2000HL color space for background subtraction

2013 ◽  
Author(s):  
Muhammet Balcilar ◽  
Fethullah Karabiber ◽  
A. Coskun Sonmez
Keyword(s):  
Performance Analysis ◽  
Background Subtraction ◽  
Color Space

Background Subtraction Using Background Sets With Image- and Color-Space Reduction

2016 ◽  
Vol 18 (10) ◽  
pp. 2093-2103 ◽  
Author(s):  
Hasup Lee ◽  
HyungSeok Kim ◽  
Jee-In Kim
Keyword(s):  
Background Subtraction ◽  
Color Space ◽  
Space Reduction

Multiple Motion Segmentation of Sport Image Based on Multi-Layer Background Subtraction

2013 ◽  
Vol 846-847 ◽  
pp. 1266-1269
Author(s):  
Meng Zhao ◽  
Zhan Ping Li
Keyword(s):  
Background Subtraction ◽  
Color Space ◽  
Texture Features ◽  
Local Binary Patterns ◽  
Growth Conditions ◽  
Subtraction Method ◽  
Subtraction Technique ◽  
Stationary Objects ◽  
Long Time ◽  
Rgb Color Space

Segmentation of motion in an image sequence is one of the most challenging problems in image processing. In image analysis engineering, accurate statistics of sport image is one of the most important subjects, while at the same time one that finds numerous applications. In this paper, we propose a robust multi-layer background subtraction technique which takes advantages of local texture features represented by local binary patterns (LBP) and photometric invariant color measurements in RGB color space. Due to the use of a simple layer-based strategy, the approach can model moving background pixels with quasiperiodic flickering as well as background scenes which may vary over time due to the addition and removal of long-time stationary objects, which plays an important role in optimizing the growth conditions of sport image. Segmentation of sport images is successfully realized by means of multi-layer background subtraction method and then the sport image is computed precisely.

Image Segmentation Algorithm Research for Sport Graphics Based on Multi-Layer Background Subtraction

2013 ◽  
Vol 339 ◽  
pp. 265-268
Author(s):  
Ming Jing Lu ◽  
Zhan Ping Li
Keyword(s):  
Background Subtraction ◽  
Color Space ◽  
Texture Features ◽  
Bilateral Filter ◽  
Local Binary Patterns ◽  
Stationary Objects ◽  
Long Time ◽  
Rgb Color Space ◽  
Image Segmentation Algorithm ◽  
Similar Intensity

Segmentation of motion in an image sequence is one of the most challenging problems in image processing, while at the same time one that finds numerous applications. In this paper, we propose a robust multi-layer background subtraction technique which takes advantages of local texture features represented by local binary patterns (LBP) and photometric invariant color measurements in RGB color space. Due to the use of a simple layer-based strategy, the approach can model moving background pixels with quasiperiodic flickering as well as background scenes which may vary over time due to the addition and removal of long-time stationary objects. The use of a cross-bilateral filter allows to implicitly smooth detection results over regions of similar intensity and preserve object boundaries.

A Novel Approach Based on Multi-Layer Background Subtraction and Seed Region Growing for Sport Graphics Segmentation

2014 ◽  
Vol 513-517 ◽  
pp. 3358-3361
Author(s):  
Li Liang ◽  
Hong Wei Wang
Keyword(s):  
Background Subtraction ◽  
Color Space ◽  
Region Growing ◽  
Texture Features ◽  
Local Binary Patterns ◽  
Seed Region ◽  
Novel Approach ◽  
Segmentation Quality ◽  
Stationary Objects ◽  
Long Time

Segmentation of motion in an image sequence is one of the most challenging problems in image processing, while at the same time one that finds numerous applications. In this paper, we propose a robust multi-layer background subtraction technique and seed region growing approach which takes advantages of local texture features represented by local binary patterns (LBP) and photometric invariant color measurements in RGB color space. Due to the use of hybridization of layer-based strategy and seed region growing approach, the approach can model moving background pixels with quasiperiodic flickering as well as background scenes which may vary over time due to the addition and removal of long-time stationary objects. The experiment results prove that in the view of the sport image segmentation, this algorithm provides fast segmentation with high perceptual segmentation quality.

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