首页 | 本学科首页   官方微博 | 高级检索  
     

HSV自适应混合高斯模型的运动目标检测
引用本文:林庆,徐柱,王士同,詹永照.HSV自适应混合高斯模型的运动目标检测[J].计算机科学,2010,37(10):254-256,290.
作者姓名:林庆  徐柱  王士同  詹永照
作者单位:1. 江苏大学计算机科学与通信工程学院,镇江,212013;南京理工大学计算机系,南京,210094
2. 江苏大学计算机科学与通信工程学院,镇江,212013
3. 南京理工大学计算机系,南京,210094;江南大学信息学院,无锡,214122
基金项目:本文受国家自然科学基金项目((60673190)资助。
摘    要:在目前的计算机视觉应用中,从视频序列中提取出运动目标是一个研究热点。针对传统方法在复杂多变环境下不能很好地检测出运动目标且运算量较大的问题,根据HSV颜色空间的特点,提出了一种基于HSV颜色空间的自适应混合高斯背景建模和阴影消除的方法。首先,在传统的混合高斯背景建模的基础上,引入了一种新的混合高斯模型高斯成分个数的自适应选择策略以提高建模的效率。其次,根据阴影在HSV向量空间的特点,融入了一种新的阴影消除方法,以检测出带阴影的运动目标。该方法能够快速准确地建立背景模型,准确分割前景目标。与传统的阴影消除方法相比,该方法可以在不需要设置阂值的情况下,对运动目标的阴影进行很好的消除,有很好的鲁棒性和实用性。

关 键 词:自适应混合高斯模型,运动目标检测,阴影消除,HSV
收稿时间:2009/11/18 0:00:00
修稿时间:2/8/2010 12:00:00 AM

Moving Objects Detection of Adaptive Gaussian Mixture Models on HSV
LIN Qing,XU Zhu,WANG Shi-tong,ZHAN Yong-zhao.Moving Objects Detection of Adaptive Gaussian Mixture Models on HSV[J].Computer Science,2010,37(10):254-256,290.
Authors:LIN Qing  XU Zhu  WANG Shi-tong  ZHAN Yong-zhao
Affiliation:(Dept.of Computer Science and Communication Engineering,Jiangsu University,Zhenjiang 212013,China)(Dept. of Computer,Nanjing University oI Science&Technology,Nanjing 210094,China)(School of Information Technology,Jiangnan University,Wuxi 214122,China)
Abstract:In the current computer vision apphcations,the research on extracting moving objects from video sequences is very hot. hhe traditional methods can not detect moving object in the complex environment well. Accodding to the characteristics of HSV color space, a adaptive mixed Gaussian background Modeling based on HSV color space and the way to remove the shadow was also proposed. Firstly, in order to improve the efficncicny of Modeling, an adaptive selection strategy of number of components of mixture of Gaussinas model was proposed. Secondly, according to the shadow characters in the HSV vector space,we also proposed a new method to remove the shadow of objects. The paper can also build the model quickly and remove the shadow accurately under the situation of light with big change. Compared with the traditional shadows suppression method,this method can suppress shadows to moving objects without setting the threshold value.
Keywords:Aadaptive mixture gaussian model    Moving object detection  Shadow suppression  HSV
本文献已被 万方数据 等数据库收录!
点击此处可从《计算机科学》浏览原始摘要信息
点击此处可从《计算机科学》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号