本文選題：目標(biāo)檢測(cè)與跟蹤 + 陰影消除��； 參考：《鄭州大學(xué)》2015年碩士論文

【摘要】：智能交通系統(tǒng)(Intelligent Transportation System,簡(jiǎn)稱(chēng)ITS)是未來(lái)交通系統(tǒng)的發(fā)展方向,它將先進(jìn)的信息技術(shù)、控制技術(shù)及計(jì)算機(jī)技術(shù)等有效地集成運(yùn)用于整個(gè)地面交通管理系統(tǒng),其中交通違規(guī)抓拍、車(chē)輛跟蹤及車(chē)流量統(tǒng)計(jì)是ITS的重要組成部分�；诘馗芯�(xiàn)圈的傳統(tǒng)交通系統(tǒng)安裝工程量大、維修困難,并且功能有限,不能滿(mǎn)足現(xiàn)代交通的需求。因此,設(shè)計(jì)一個(gè)基于視頻序列的車(chē)輛跟蹤、違章抓拍與車(chē)流量統(tǒng)計(jì)一體式系統(tǒng)具有十分重要的意義。本文分析了基于視頻序列的交通違章監(jiān)測(cè)系統(tǒng)原理,研究了系統(tǒng)設(shè)計(jì)中的圖像預(yù)處理、目標(biāo)檢測(cè)與跟蹤、陰影消除和車(chē)流量統(tǒng)計(jì)理論和算法,并進(jìn)行了仿真和分析。綜合該仿真結(jié)果和系統(tǒng)實(shí)時(shí)性要求,采用金字塔特征光流(L-K)算法進(jìn)行目標(biāo)檢測(cè)、并基于HSV顏色空間消除運(yùn)動(dòng)目標(biāo)的陰影,采用基于時(shí)空上下文信息(STC)進(jìn)行目標(biāo)跟蹤,結(jié)合背景差分法的虛擬線(xiàn)圈技術(shù)實(shí)現(xiàn)車(chē)流量統(tǒng)計(jì)。選擇基于RS Components公司的ARM11作為硬件的核心模塊,采用Micron公司MT9P031 CMOS傳感器設(shè)計(jì)圖像采集端,并提供了系統(tǒng)電源及其保護(hù)電路。最后,基于Python接口的Qt和Open Cv在硬件平臺(tái)上實(shí)現(xiàn)具有車(chē)輛跟蹤、違規(guī)抓拍和車(chē)流量統(tǒng)計(jì)功能的一體式違章監(jiān)測(cè)軟件。經(jīng)現(xiàn)場(chǎng)測(cè)試驗(yàn)證表明:系統(tǒng)工作可靠、穩(wěn)定,具有實(shí)用價(jià)值。
[Abstract]:Intelligent Transportation system (ITSs) is the development direction of traffic system in the future. It effectively integrates advanced information technology, control technology and computer technology into the whole ground traffic management system, in which traffic violations are captured.Vehicle tracking and traffic flow statistics are important parts of ITS.The traditional traffic system based on the earth sense coil can not meet the needs of modern traffic because of its large amount of installation, difficult maintenance and limited function.Therefore, it is of great significance to design a vehicle tracking system based on video sequence, an integrated system of capture and traffic statistics.In this paper, the principle of traffic violation monitoring system based on video sequence is analyzed, and the theories and algorithms of image preprocessing, target detection and tracking, shadow cancellation and traffic flow statistics are studied.Based on the simulation results and the real-time requirements of the system, the pyramidal feature optical flow (L-K) algorithm is used to detect the target, and the shadow of moving target is eliminated based on the HSV color space, and the target tracking is carried out based on the temporal and spatial context information.The virtual coil technology based on background difference method is used to realize traffic flow statistics.The ARM11 based on RS Components company is selected as the core module of the hardware. The MT9P031 CMOS sensor of Micron company is used to design the image acquisition terminal, and the system power supply and its protection circuit are provided.At last, QT and Open CV based on Python interface are realized on the hardware platform, which has the functions of vehicle tracking, illegal capture and traffic flow statistics.The field test shows that the system is reliable, stable and practical.
【學(xué)位授予單位】：鄭州大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：U495;TP391.41

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本文編號(hào)：1773176