红外技术Issue(8)：628-632,5.
基于改进的混合高斯模型的红外运动目标检测
Infrared Moving Object Detection Based on Improved Gaussian Mixture Model
摘要
Abstract
Traditional Gaussian mixture modeling is likely to cause motion artifact, while the noise or regions with low contrast will bring gaps or holes when extracting the targets. In view of above problems, this paper assigns different background updating rate to the motion and static regions, and make the most of the background and foreground information, and then the final results are fusion with Gaussian background subtraction and the foreground image from Gaussian mixture modeling with a certain proportion. The experimental results demonstrate that improved Gaussian mixture modeling for infrared moving targets detection can overcome problems existing in traditional algorithm. It could extract the moving object completely from complex backgrounds, and also has a good anti-noise capability.关键词
红外视频序列/混合高斯模型/运动目标检测Key words
infrared video sequence/Gaussian mixture model/moving target detection分类
信息技术与安全科学引用本文复制引用
付冬梅,唐升波..基于改进的混合高斯模型的红外运动目标检测[J].红外技术,2014,(8):628-632,5.基金项目
国家自然科学基金，编号61272358；北京市工业波谱工程试验研究中心项目，编号60977065；北京市重点学科建设项目，编号00012007。 （）
