本文選題：智能交通 + 車輛通過檢測�。� 參考：《電子科技大學》2014年碩士論文

【摘要】：圖像抓拍技術(shù)(Video Enforcement System,VES)是智能交通系統(tǒng)的重要組成部分。本文通過車輛檢測技術(shù)、圖像抓拍技術(shù)以及車牌自動識別技術(shù),自動捕獲路口紅燈時所經(jīng)過的車輛車牌信息,從而實現(xiàn)道路交通的智能管理。本文對車輛圖像智能抓拍系統(tǒng)的研究主要集中在如下幾個方面。(1)車輛通過檢測子系統(tǒng)通過紅燈檢測器、環(huán)形感應(yīng)線圈和Athenex車輛自動檢測器,實現(xiàn)對路口紅燈信息的自動監(jiān)控,當信號燈狀態(tài)為綠燈狀態(tài)時,關(guān)閉車輛通過檢測子系統(tǒng),;當信號燈為紅燈狀態(tài)時,當檢測到有車輛通過時,啟動圖像抓拍模塊,進行通過車輛的抓拍。通過對紅燈信號的檢測,實現(xiàn)車輛檢測模塊的自動開關(guān),達到降低誤拍、節(jié)省能源的目標。(2)圖像抓拍功能子系統(tǒng)圖像抓拍功能子系統(tǒng)在接收到車輛檢測功能子系統(tǒng)所發(fā)送的拍攝信號之后,進行拍照,并且將所拍得的圖片發(fā)送到服務(wù)器端進行處理。采用工業(yè)攝像機,在車輛通過檢測模塊的控制下,進行闖紅燈車輛的抓拍,并且將抓拍的圖像,通過Socket技術(shù)傳輸?shù)椒⻊?wù)器端進行車牌號碼的自動識別。(3)車牌號碼自動識別子系統(tǒng)車牌號碼自動識別功能是在接收到圖片抓拍功能子系統(tǒng)上傳的闖紅燈車輛抓拍圖片之后,采用車牌號碼自動識別技術(shù)識別抓拍圖片中的車牌號碼,并且將車牌號碼、時間、地點等信息傳送給交通管理系統(tǒng)。在本文的研究中,首先通過對抓拍圖像的分析,進行車牌號碼的定位,并且利用Tury LRP車牌號碼自動識別技術(shù),首先對車牌號碼的自動識別。(4)信息發(fā)布子系統(tǒng)車輛圖像智能抓拍系統(tǒng)出了對闖紅燈的車輛進行抓拍,并且進行抓拍圖像的車牌號碼自動識別以外,更為重要的是為城市交通管理系統(tǒng)提供闖紅燈車輛的車牌號碼等信息。而為了滿足系統(tǒng)可擴充性的需求,以及為了滿足不同操作系統(tǒng)平臺的要求,本文所研究的車輛圖像智能抓拍系統(tǒng)采用SOA技術(shù)來實現(xiàn)數(shù)據(jù)的共享。在測試中,系統(tǒng)對闖紅燈車輛的抓拍率達到98%以上,車牌號碼的自動識別率達到95%以上,人工識別率達到100%。表明本文所設(shè)計的車輛圖像智能抓拍系統(tǒng)能夠滿足路口闖紅燈車輛的智能抓拍要求,符合系統(tǒng)設(shè)計時的要求。
[Abstract]:Video Enforcement System (VES) is an important part of the intelligent transportation system. In this paper, the vehicle license plate information is automatically captured by vehicle detection technology, image capture technique and license plate automatic recognition technology, so as to realize the intelligent management of road traffic. The intelligent grasp of vehicle image is carried out in this paper. The research of the beat system is mainly concentrated in the following aspects. (1) the vehicle through the detection subsystem through the red light detector, the ring induction coil and the Athenex vehicle automatic detector to realize the automatic monitoring of the red light information of the intersection. When the state of the signal light is green, the car is closed through the detection subsystem, and when the signal lamp is a red light state. When the vehicle is detected, the image capture module is started and the capture of the vehicle is carried out. The automatic switch of the vehicle detection module is realized through the detection of the red light signal to achieve the goal of reducing the error and saving energy. (2) the image capture function sub-system of the image capture function subsystem is sent to the vehicle detection function subsystem. After the shooting signal, take pictures, and send the pictures to the server to handle. Use industrial video camera, under the control of the vehicle through the detection module, carry on the capture of the red light vehicle, and transfer the captured image to the server side by Socket technology to automatically identify the number of the license plate. (3) license plate. The automatic recognition function of the number automatic identification subsystem is to identify the license plate number in the captured picture by using the license plate number automatic identification technique after receiving the picture of the red light vehicle captured by the picture capture function subsystem, and transmit the license number, time and ground point to the traffic management system. In the study, first of all, the location of the license plate number is carried out through the analysis of the captured image, and the auto recognition technology of Tury LRP license plate number is used to automatically identify the number of the license plate first. (4) the vehicle image intelligent capture system of the information publishing subsystem has captured the car of the red light, and the license plate number of the captured image is carried out. In addition to dynamic recognition, it is more important for the urban traffic management system to provide information about the license plate number of red light vehicles. In order to meet the requirements of the system extensibility and to meet the requirements of different operating system platforms, the vehicle image intelligent capture system studied in this paper uses SOA technology to realize data sharing. In the system, the rate of capturing the red light vehicles is up to 98%, the automatic recognition rate of the license plate number is above 95% and the artificial recognition rate reaches 100%., which shows that the intelligent capture system designed in this paper can meet the requirements of the intelligent capture of the red light vehicles at the intersection, and the system meets the requirements of the system timing.
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：U495;TP391.41

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