智慧型交通監控系統中多車道車輛之偵測與追蹤

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姓名

陳炳富(Bing-Fu Chen) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

智慧型交通監控系統中多車道車輛之偵測與追蹤
(Detection and Tracking of Multi-lane Vehicles for Intelligent Traffic Monitoring)

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摘要(中)

隨著科技社會的成形，在社會安全與電腦科技密不可分的關係下，追蹤系統成為一種不可缺少的角色，除了以通訊方式為基礎，利用互動的方式，不斷的聯繫以追蹤的方式外，另一種則可被歸類於單方面監視系統的追蹤。單方面的追蹤方式必須使用監視的錄影設備與圖形識別的追蹤技術互相的配合，然而以錄影取像的方式所得到的資訊有限，因此後端圖形識別的追蹤方式也就顯的格外的重要。
本論文主要的目的在於提出一個智慧型交通即時監控系統中多車道的車輛追蹤系統，並使用此系統觀察此路段的交通狀況。在此系統中，除了在影像前處理上將運用各種動態影像技術來建立可靠的背景影像與陰影去除外，並提出以動態多邊型(active contour)的機制來描述車體外形，以及利用線性預測(linear prediction)動態物體的方式做為系統的追蹤模式，並以此為基礎做為主要的系統架構，以期能達到即時且正確的效果。
在實驗部份將會截取高速公路車流量影像，利用所提出的方法加以驗證該系統是可靠且有效的。

摘要(英)

With the advancement of modernized society, the relationship between social security and computer technologies is getting closer and closer. Computer technologies can provide more comfortable and secure environment and improve the living standard of human beings. Tracking and monitoring systems gradually become an indispensable part in current society, which can be realized by utilizing image processing and pattern recognition techniques. They constitute the essential part of a video surveillance system.
In this thesis, an intelligent traffic monitoring system which can track vehicles in multi-lanes highway. The proposed system can also extract many important traffic parameters to reflect the real time traffic situation in highways. In the proposed system, the task of image preprocessing is first performed to construct reliable image background and eliminate shadows caused by the vehicles. Then, the mechanism of active contour is devised to describe the shape of vehicles. Last, the vehicle tracking model is built by utilizing the linear prediction model of dynamic objects.
Experiments were conducted on several image sequences captured in highways. Experimental results verify the validity of the proposed approach in successfully tracking vehicles.

關鍵字(中)

★ 動態多邊型
★ 車輛偵測
★ 車輛追蹤

關鍵字(英)

★ active contour
★ vehicle tracking
★ vehicle detection

論文目次

Abstract III
摘要 IV
附圖目錄 VI
表格目錄 VII
第一章緒論 1
1.1 研究動機 1
1.2 相關研究 3
1.2.1 前景物體偵測 4
1.2.2 前景描述 6
1.2.3 動態物體追蹤模式 8
1.3 系統架構 9
1.4 論文架構 11
第二章前景區塊萃取 12
2.1背景影像建立與背景相減 12
2.2陰影去除 17
3.3邊緣能量的強化 21
3.4區塊填充與利用形態學雜訊去除 22
第三章車輛描述 25
3.1 動態多邊型(active contour) 26
3.2 改良式動態多邊型(improved active contour model) 30
3.3 動態多邊型於監視系統之應用 33
第四章車輛追蹤模式與系統整合 36
4.1車輛追蹤模式 36
4.2參數萃取 40
第五章實驗結果與討論 42
5.1 實驗視訊 42
5.2 前處理結果 43
5.3 交通參數萃取結果 47
5.4錯誤類型分析與討論 49
第六章結論與未來工作 51
6.1結論 51
6.2未來工作 52
Reference 54

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指導教授

范國清(Kuo-Chin Fan)

審核日期

2003-6-30

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