视频交通流检测中的背景提取  

Background Extraction in Traffic Flow Eetection by Video

作　　者：唐佳林[1] 王镇波[2] 陈华春[1] 

机构地区：[1]北京理工大学珠海学院信息学院,广东珠海519085 [2]中山大学智能交通研究中心,广东广州510006

出　　处：《山西电子技术》2011年第4期39-40,46,共3页Shanxi Electronic Technology

基　　金：广东省科技厅2009年度创新基金项目(2009CD055)

摘　　要：在基于视频的交通流检测系统中,静止背景的快速准确提取是基础。背景的提取主要分为模型法和非模型法,非模型法的算法复杂度低,能满足交通流检测实时性要求。论文比较和分析了均值法、直方图统计法、中值滤波法和背景学习法四种常用的背景提取方法。并通过实际的交通视频测试比较了四种方法。Background extraction is a fundamental and critical task in video traffic detection system. Approaches of background extraction can be divided into two groups, that are the methods based on model and the model-free methods. With lower time-consuming feature, model-free methods can satisfy the demand on real-time processing in video traffic detection system. This essay compares four common model-free methods, including medial filtering, histogram method, median filtering, and background learning method by analyzing traffic video, and gains a conclusion on their features.

关 键 词：背景提取 非模型法 背景更新 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]