摘要
在RGB空间中对彩色交通视频图像进行多通道边缘检测,利用融合的边缘信息进行多帧迭加建立自适应背景模型,通过背景模型抽取运动车辆.受车速,车流量,噪声等影响,得到的是不完整的目标边缘,依靠边缘生长对目标进行修补,以提高运动车辆检测的准确性,保证边缘的连续性.实验结果表明,该方法计算量小,能够满足实时系统的要求,可有效地检测运动车辆.
This paper employs a muhichannel edge detecting approach to traffic color video image in RGB space, an adaptive background model is built on the frames iteration of fused edge information and the moving vehicles are based on the background model subtraction. The edge of target is in- complete because of effecting by speed of vehicles, freight flow, noise and so on. Mending the edge of target with edge growing in order to improve the accuracy of moving vehicles detection and smooth the edge. The experimental results show that the method needs little calculation, and can satisfy the requirement of the real - time system and detect moving vehicles effectively.
出处
《福州大学学报(自然科学版)》
CAS
CSCD
北大核心
2007年第1期41-44,共4页
Journal of Fuzhou University(Natural Science Edition)
基金
福建省自然科学基金资助项目(A0510010)
关键词
运动车辆
检测
彩色边缘
背景模型
边缘生长
moving vehicles
detection
color edge
background model
edge growing