一种基于鲁棒局部纹理特征的背景差分方法

针对复杂场景下运动目标的精确检测这一问题,提出一种对噪声鲁棒并具备灰度尺度不变性的局部纹理特征描述子LBP_Center,将其与像素的颜色信息结合应用于背景建模中,采用随机抽样的机制更新模型,同时引入背景复杂度以去除多模态动态背景产生的噪点。在标准测试数据集上的实验结果表明,该算法对柔性阴影及光照缓慢变化具备良好的鲁棒性,综合性能更优。...

Full description

Saved in:
Bibliographic Details
Published in计算机工程与科学 Vol. 39; no. 8; pp. 1513 - 1519
Main Author 金静 党建武 王阳萍 翟凤文
Format Journal Article
LanguageChinese
Published 兰州宇信信息技术有限责任公司,甘肃兰州730070 2017
兰州交通大学电子与信息工程学院,甘肃兰州,730070%兰州交通大学电子与信息工程学院,甘肃兰州730070
Subjects
局部纹理特征
柔性投射阴影
背景差分
运动目标检测
local texture feature
柔性投射阴影
背景差分
局部纹理特征
运动目标检测
detection of moving objects
background subtraction
soft projected shadows
Online AccessGet full text
ISSN1007-130X
DOI10.3969/j.issn.1007-130X.2017.08.020

Cover

More Information
Summary:针对复杂场景下运动目标的精确检测这一问题,提出一种对噪声鲁棒并具备灰度尺度不变性的局部纹理特征描述子LBP_Center,将其与像素的颜色信息结合应用于背景建模中,采用随机抽样的机制更新模型,同时引入背景复杂度以去除多模态动态背景产生的噪点。在标准测试数据集上的实验结果表明,该算法对柔性阴影及光照缓慢变化具备良好的鲁棒性,综合性能更优。
Bibliography:Focusing on the precise detection of moving objects, we propose a new local texture descriptor--LBP_Center, which is robust to noise and invariant to gray scale. And together with the color information of pixels we apply it to the background model. Then we update the model by random sampiing and introduce background complexity to remove the noise of the multimode dynamic background. Experimental results on standard testing datasets indicate that the new method has good robustness to soft project shadows and slow illumination change, and better comprehensive performance in comparison with other algorithms.
detection of moving objects; background subtraction; local texture feature; soft projected shadows
43-1258/TP
JIN Jing1 , DANG Jian-wu1 , WANG Yang-ping1,2 , ZHAI Feng-wen1 （1. School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070; 2. Lanzhou Yuxin Information and Technology Co, LTD, Lanzhou 730070, China）
ISSN:1007-130X
DOI:10.3969/j.issn.1007-130X.2017.08.020