• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学

• 论文 • 上一篇    下一篇

一种基于鲁棒局部纹理特征的背景差分方法

金静1,党建武1,王阳萍1,2,翟凤文1   

  1. (1.兰州交通大学电子与信息工程学院,甘肃 兰州 730070;2.兰州宇信信息技术有限责任公司,甘肃 兰州 730070)
     
  • 收稿日期:2015-12-10 修回日期:2016-05-03 出版日期:2017-08-25 发布日期:2017-08-25
  • 基金资助:

    国家自然科学基金(61162016,61562057);甘肃省科技支撑计划(1104FKCA102,1104GKCA057);甘肃省青年科技基金(148RJYA011);兰州交通大学校青年基金(2015003);兰州市人才创新创业科技计划(2014-RC-7)

A background subtraction method based
on robust local texture features
 

JIN Jing1,DANG Jian-wu1,WANG Yang-ping1,2,ZHAI Feng-wen1   

  1. (1.School of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730070;
    2.Lanzhou Yuxin Information and Technology Co,LTD,Lanzhou 730070,China)
  • Received:2015-12-10 Revised:2016-05-03 Online:2017-08-25 Published:2017-08-25

摘要:

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。

关键词: 运动目标检测, 背景差分, 局部纹理特征, 柔性投射阴影

Abstract:

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 sampling 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.

Key words: detection of moving objects, background subtraction, local texture feature, soft projected shadows