本文關(guān)鍵詞： 視頻車輛檢測(cè) 光照陰影消除 運(yùn)動(dòng)位置跟蹤 車型識(shí)別　出處：《西南交通大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著社會(huì)經(jīng)濟(jì)的飛速發(fā)展以及交通運(yùn)輸量的日益提高,傳統(tǒng)的交通監(jiān)管方式已不再能滿足復(fù)雜多變的交通現(xiàn)狀,智能交通系統(tǒng)應(yīng)運(yùn)而生。本文課題來源于四川省科技廳科技支撐項(xiàng)目“智能交通安全監(jiān)測(cè)與流量控制系統(tǒng)重大關(guān)鍵技術(shù)研究”項(xiàng)目的子課題一：大型貨車占道行駛動(dòng)態(tài)檢測(cè)關(guān)鍵技術(shù)研究及監(jiān)控系統(tǒng)開發(fā)。針對(duì)高速公路這一特殊場(chǎng)景,研究車輛檢測(cè)與跟蹤、車型識(shí)別的方法,使能夠有效檢測(cè)和跟蹤高速公路行駛車輛,準(zhǔn)確識(shí)別大型貨車,為建立大型貨車違法占道判別模型提供有力支撐。首先詳細(xì)討論了各種道路信息采集方式的原理、應(yīng)用場(chǎng)景,并對(duì)各種道路信息采集方式的優(yōu)缺點(diǎn)進(jìn)行了比較,選擇了監(jiān)控效果直觀清晰、安裝維護(hù)方便、監(jiān)控范圍廣的視頻信息采集方式。分析了目標(biāo)檢測(cè)、跟蹤以及車型識(shí)別的基本方法,對(duì)各類方法進(jìn)行了原理介紹和優(yōu)劣比較。其次提出了在時(shí)空背景差分模型的檢測(cè)基礎(chǔ)上,加入了光照陰影消除和運(yùn)動(dòng)種子填充和運(yùn)動(dòng)目標(biāo)尾跡消除的新檢測(cè)方法,該方法使檢測(cè)目標(biāo)更加清晰完整。最后將該檢測(cè)方法進(jìn)行了相應(yīng)實(shí)驗(yàn),并將該方法的車輛檢測(cè)效果和混合高斯檢測(cè)模型進(jìn)行了二值差分圖的對(duì)比,實(shí)驗(yàn)結(jié)果表明該方法能達(dá)到較好的目標(biāo)正確識(shí)別率,同時(shí),還將錯(cuò)誤樣本進(jìn)行了歸類和錯(cuò)誤原因分析。結(jié)果證明,在不同密集程度的視頻中,車輛檢測(cè)的正確率都能達(dá)到90%以上。另外,根據(jù)高速公路上車輛運(yùn)動(dòng)軌跡方向基本不變的特性,采用了基于車輛的運(yùn)動(dòng)位置信息和顏色信息關(guān)聯(lián)相結(jié)合的車輛跟蹤方法,詳細(xì)介紹了跟蹤原理。最后通過分析車輛面積在視頻中的非線性關(guān)系設(shè)定閡值以及車輛本身的紋理信息和輪廓信息,實(shí)現(xiàn)了大小車區(qū)分和客貨車區(qū)分。通過選擇大量樣本對(duì)本文中的車輛檢測(cè)跟蹤及車型識(shí)別方法進(jìn)行實(shí)驗(yàn)。證明可以應(yīng)用在大型貨車占道行駛動(dòng)態(tài)檢測(cè)關(guān)鍵技術(shù)研究及監(jiān)控系統(tǒng)開發(fā)中,為建立違法占道判別模型提供依據(jù)。
[Abstract]:With the rapid development of social economy and the increasing traffic volume, the traditional traffic supervision can no longer meet the complex and changeable traffic situation. Intelligent transportation system arises at the historic moment. This paper comes from the project of science and technology support project of Sichuan science and technology department, "research on the key technology of intelligent traffic safety monitoring and flow control system" Research on key Technologies of driving dynamic Detection and Development of Monitoring system. The method of vehicle detection and tracking and vehicle type identification is studied so as to effectively detect and track motorway moving vehicles and accurately identify large trucks. This paper provides a powerful support for the establishment of the model for judging the illegal occupation of large freight cars. Firstly, the principle and application scene of various road information collection methods are discussed in detail, and the advantages and disadvantages of various road information collection methods are compared. The method of video information acquisition with visual effect, convenient installation and maintenance and wide monitoring range is selected. The basic methods of target detection, tracking and vehicle identification are analyzed. The principle of each method is introduced and the advantages and disadvantages are compared. Secondly, a new detection method of light shadow elimination, moving seed filling and moving object wake cancellation is proposed based on the space-time background difference model. This method makes the detection target more clear and complete. Finally, the corresponding experiments are carried out, and the vehicle detection effect of this method is compared with the mixed Gao Si detection model. The experimental results show that the method can achieve a good target recognition rate. At the same time, the error samples are classified and the error causes are analyzed. The accuracy rate of vehicle detection can reach more than 90%. In addition, according to the characteristics of the moving track direction of the freeway, the vehicle tracking method based on the association of the vehicle motion position information and the color information is adopted. The tracking principle is introduced in detail. Finally, by analyzing the nonlinear relationship between the vehicle area and the video, the threshold value, the texture information and the contour information of the vehicle itself are analyzed. By selecting a large number of samples, the vehicle detection and tracking and vehicle identification methods in this paper are tested. It is proved that it can be applied to the research of key technologies of dynamic detection of large freight cars on the road. Research and monitoring system development, It provides the basis for establishing the discrimination model of illegal occupation.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：U495;TP391.41

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本文編號(hào)：1512146