本文選題：高速公路 + 視頻監(jiān)控��； 參考：《長安大學(xué)》2016年碩士論文

【摘要】：近些年來,由于自然環(huán)境的惡化,由霧霾、沙塵、強(qiáng)光等引起的低能見度天氣對我國高速公路安全行車的影響越來越為嚴(yán)重,高速公路沿線的能見度天氣全面檢測與預(yù)警處置需求也變得愈來愈迫切。相比于常規(guī)能見度測量儀器造價(jià)昂貴、采樣空間小、安裝復(fù)雜、維護(hù)困難等缺點(diǎn),密布于高速公路沿線的監(jiān)控?cái)z像機(jī)電設(shè)備所記錄的交通監(jiān)控視頻包含了豐富的能見度信息,為高速公路能見度探測提供了新的思路。有鑒于此,本文利用高速公路沿線監(jiān)控?cái)z像頭拍攝的監(jiān)控視頻,設(shè)計(jì)了一種基于監(jiān)控視頻的能見度檢測方法,并圍繞該方法開發(fā)了一款分布式的道路能見度檢測與預(yù)警信息系統(tǒng)。具體而言,本文的研究內(nèi)容包括:(1)系統(tǒng)總體框架設(shè)計(jì)。在分析我國交通行業(yè)能見度監(jiān)測與預(yù)警需求的基礎(chǔ)上,設(shè)計(jì)了基于監(jiān)控視頻分析的高速公路能見度檢測與預(yù)警系統(tǒng)的整體框架。該框架主要由上位機(jī)和下位機(jī)兩部分組成:下位機(jī)圍繞高速公路現(xiàn)場的視頻監(jiān)控系統(tǒng)搭建,用于視頻分析和能見度計(jì)算;上位機(jī)部署于路網(wǎng)信息中心,向用戶提供能見度監(jiān)控、低能見度預(yù)警處置、公共信息發(fā)布等功能。(2)能見度檢測方法。該方法利用密集布設(shè)于高速公路沿線的監(jiān)控?cái)z像頭,在攝像頭視野內(nèi)安裝固定規(guī)格與顏色模式的參照物擋板,并基于經(jīng)典能見度理論及視頻圖像分析技術(shù),通過分析攝像頭所采集的參照物圖像的失真程度來計(jì)算實(shí)時(shí)能見度值。實(shí)驗(yàn)驗(yàn)證表明,該算法具有較高的檢測精度,可以很好地滿足我國高速公路的能見度檢測應(yīng)用需求。(3)能見度檢測與預(yù)警系統(tǒng)研發(fā)。該系統(tǒng)的下位機(jī)子系統(tǒng)運(yùn)行于現(xiàn)場嵌入式工控機(jī),其核心軟件程序具有插件式體系結(jié)構(gòu);上位機(jī)子系統(tǒng)基于JAVA EE技術(shù)研發(fā),具有包含實(shí)體層、業(yè)務(wù)邏輯層、表現(xiàn)層等的分層體系結(jié)構(gòu)。示范應(yīng)用表明,該系統(tǒng)能夠持續(xù)全面檢測高速公路沿線能見度,并及時(shí)發(fā)布第能見度預(yù)警,具有重要的應(yīng)用價(jià)值。
[Abstract]:In recent years, due to the deterioration of the natural environment, the impact of low visibility weather caused by haze, dust and strong light on the safe driving of expressways in China has become more and more serious.The demand of visibility weather detection and early warning along highway becomes more and more urgent.Compared with the conventional visibility measuring instruments, such as expensive cost, small sampling space, complex installation, difficult maintenance and other shortcomings, the traffic surveillance video recorded by the monitoring camera electromechanical equipment along the highway contains rich visibility information.It provides a new idea for highway visibility detection.In view of this, this paper designs a visibility detection method based on surveillance video, which is taken by the surveillance camera along the highway.A distributed road visibility detection and early warning information system is developed around this method.Specifically, the content of this paper includes the design of the general framework of the system.On the basis of analyzing the requirement of visibility monitoring and early warning in China's transportation industry, the whole frame of highway visibility detection and warning system based on surveillance video analysis is designed.The frame consists of two parts: the lower computer is built around the scene video surveillance system of the freeway, which is used for video analysis and visibility calculation; the upper computer is deployed in the network information center to provide visibility monitoring to users.Low visibility warning disposal, public information release and other functions. 2) visibility detection method.Based on the classical visibility theory and video image analysis technology, the method uses the surveillance camera which is located in the highway, and installs the reference baffle with fixed specifications and color patterns in the view of the camera.The real-time visibility is calculated by analyzing the distortion of the reference image collected by the camera.The experimental results show that the algorithm has high detection accuracy and can meet the requirement of visibility detection and warning system of freeway in China.The sub-system of the system runs in the field embedded industrial control computer, its core software program has the plug-in architecture, the upper computer subsystem is developed based on JAVA EE technology, it has the entity layer, the business logic layer, and the sub-system of the upper computer is based on the technology of JAVA EE.Hierarchical architecture representing layers, etc.The demonstration application shows that the system can continuously and comprehensively detect the visibility along the highway and issue the visibility warning in time. It has important application value.
【學(xué)位授予單位】：長安大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：U495;TP391.41

【相似文獻(xiàn)】

相關(guān)期刊論文 前10條

1 謝俊宏;;淺談監(jiān)控視頻干擾問題的解決[J];海峽科學(xué);2008年08期

2 歐溫暖;田緒紅;朱同林;;基于教室監(jiān)控視頻的課堂行為計(jì)數(shù)分析[J];圖學(xué)學(xué)報(bào);2012年02期

3 李勃;陳啟美;;基于監(jiān)控視頻的運(yùn)動(dòng)車輛行為分析算法[J];儀器儀表學(xué)報(bào);2006年S3期

4 梁浩哲;徐樹奎;李國輝;張軍;;面向監(jiān)控視頻的行為模式挖掘[J];山東大學(xué)學(xué)報(bào)(工學(xué)版);2011年06期

5 孫晉明;;遠(yuǎn)程監(jiān)控視頻無線傳輸方式的比選設(shè)計(jì)[J];電氣時(shí)代;2011年05期

6 姜振鳳;遲慶云;;基于DBAN的監(jiān)控視頻數(shù)據(jù)挖掘[J];河北工程大學(xué)學(xué)報(bào)(自然科學(xué)版);2013年02期

7 祝林峰;方思平;張興明;張平;馬旭;;監(jiān)控視頻中的車體特征檢驗(yàn)在交通肇事逃逸案件中的應(yīng)用[J];警察技術(shù);2013年06期

8 胡平;;霧霾天氣下高速公路監(jiān)控視頻的一種增強(qiáng)算法[J];公路交通科技;2014年01期

9 閆帥輝;柏正堯;尹立國;楊仁青;高v，

本文編號：1769760