A New Pixel-Level Background Subtraction Algorithm in Machine Vision

被引:1
|
作者
Zhang, Songsong [1 ]
Jiang, Tian [1 ]
Peng, Yuanxi [1 ]
Peng, Xuefeng [1 ]
机构
[1] Natl Univ Def Technol, Coll Comp, State Key Lab High Performance Comp, Changsha 410073, Peoples R China
来源
INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2017, PT II | 2017年 / 10463卷
关键词
Background modeling; Machine vision; Background foreground segmentation; SEGMENTATION;
D O I
10.1007/978-3-319-65292-4_45
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the machine vision, the algorithm of background subtraction is used in target detection widely. In this paper, we reproduce some algorithms such as ViBe, Local Binary Similar Pattern (LBSP), Local Ternary Pattern (LTP) and so on. In view of the problem of inaccurate edge in target detection, we propose a method of combining color and LBSP for background model. It can obtain information both in pixel and texture (marked as improved-LBSP in the paper). On this basis, we propose a new method marked as BFs-method in the paper, which have a new persistence consists of color, LBSP, and time (t). The key advantage of this method lie in its highly robust dictionary model as well as it's ability to automatically adjust pixel-level segmentation behavior, which improves the ability to remove the shadow of the target and the hole inside the target.
引用
收藏
页码:520 / 531
页数:12
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