多视觉信息融合的内河航道智能监控系统  

An Intelligent Surveillance System for Freshwater Sea-route Based on Multi-vision Information Fusion

作　　者：汤一平[1] 柳圣军[1] 周超 严海东[1] 金海民[1] 朱艺华[1] 

机构地区：[1]浙江工业大学信息工程学院,杭州310014 [2]浙江省港航局,杭州310005

出　　处：《中国图象图形学报》2008年第8期1608-1616,共9页Journal of Image and Graphics

基　　金：浙江省科技厅重大科技项目(2006C11202);国家自然科学基金项目(60673177)

摘　　要：探讨了利用动态图像理解技术对内河船舶的交通状况进行监控,采用多视觉传感器数据融合技术对跟踪的船舶对象进行特写抓拍;通过对交通流信息的实时采集、处理、跟踪与分析,得到内河航道中交通状态信息,如船舶流量、船舶速度、通航密度等重要基础信息。通过对抓拍到的船舶对象图像进行船名牌识别和吃水深度的估算,得到被跟踪船舶对象的基本属性数据和载重量等重要内河管理基础信息,为航运管理部门进行水域交通管理和交通规划提供决策依据。此外,通过自定义感兴趣监控区域以及监控对象来减少图像处理时间,提高系统实时处理能力及鲁棒性。实验结果表明,系统可以实现对船舶稳定跟踪,并对船舶进行特写抓拍和识别,识别准确率高,最终实现吨位估算。In this paper we discussed about monitoring the traffic of freshwater sea-route by mean of dynamic image understanding technology, in which multi-vision-sensor data amalgamation technology is used to capture the concerned areas of tracked ships. With real-time collecting, processing, tracking, and analyzing the video flow, some important traffic information including speed, number of ships, and the density of the ship in route are automatically obtained. The captured ship images are analyzed to determine license plates and load of the tracked ships and to obtain some basic data useful for river management department＇ s decision-making for management and planning. In addition, the surveillance area and object can be defined by users so that the system processing time is reduced while the ability to real-time processing, reliability, and robustness are improved. Experimental results show that the system can realize tracking the ships stably, can capture and recognise the specified part of the ship. The accuracy rate of recognition is high, at last the system realizes calculating the tonnage.

关 键 词：视频智能监控 船舶对象跟踪 动态图像理解 视频数据融合 船舶流量统计算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]