多目标跟踪算法在水质监测中的应用  

Water quality monitoring using multi-object tracking algorithm

作　　者：胡江龙[1] 方景龙[1] 王大全[1] 

机构地区：[1]杭州电子科技大学图形图像研究所,浙江杭州310018

出　　处：《机电工程》2012年第5期613-615,共3页Journal of Mechanical & Electrical Engineering

基　　金：浙江省科技计划资助项目(2009C14032)

摘　　要：针对活鱼水质监测系统中的活鱼跟踪中存在的问题,提出了一种基于视频的多目标跟踪算法,通过采用一种基于统计模型的背景建模方法得到了实验鱼缸的初始背景,并在活鱼目标检测跟踪过程中实时更新背景,在此基础上采用背景相减法和自适应图像二值化实现了活鱼运动目标的提取,并用连通区域分析提取活鱼的大小、质心等特征值,最后将卡尔曼预测器应用于基于运动特征的跟踪技术中,实现了活鱼的轨迹跟踪,提取到了活鱼的运动轨迹,最终达到了为后续的水质预警提供了可靠的轨迹数据的目的,所跟踪得到的活鱼运动轨迹数据是监测系统水质预警的重要基础。研究结果表明,该算法符合系统的实时性和准确性要求,能实现活鱼运动轨迹的准确快速跟踪。Aiming at the problems of tracking the fishes in live-fish water quality monitoring system,a video-based multi-target tracking algorithm was proposed.The initial background of the experimental fish tank was built using a statistical background modeling method,and the background was updated during target detection and tracking in real-time.On this basis,background subtraction method and adaptive image binarization were used to achieve the extraction of fish moving target,and the connected component analysis was used to extract fish size,mass and other characteristics of value,and finally the Kalman predictor for the motion tracking based on characteristics was applied to achieve trajectory tracking of fish,extracting fish＇s trajectory.It is achieved that providing a reliable trajectory data to the follow-up early warning of water quality eventually.The data of the tracked trajectory is an important basis for analysis of water quality in the monitoring system.The results show that the algorithm,with the requirements of real-time and accuracy in the system,could achieve trajectory of fish tracking accurately and quickly.

关 键 词：活鱼水质监测 多目标视频跟踪 图像分割 计算机视觉 

分 类 号：TN401[电子电信—微电子学与固体电子学] TP216[自动化与计算机技术—检测技术与自动化装置]