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  • 學位論文

影像處理技術於多型態路口交通參數之擷取研究

A Study on Traffic Parameter Extraction at Various Intersection via Image Processing

指導教授 : 張堂賢
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摘要


路口交通參數對於交通控制是非常重要的,它不僅可以做為道路設計的基礎,亦可做為號誌時制設定的指標,以往路口交通參數收集往往是以人工調查,近年來越來越多領域研究如何以影像偵測系統來收集交通參數,由於影像有大量資訊,故可利用影像處理(Image processing)及電腦視覺(Computer vison)技術將影像中的相關訊息擷取出來,有許多研究以固定式攝影機影像(CCTV),擷取交通影像並透過後端影像處理程式分析影像資料,已有相當的成果,然一般的研究多著重於高速公路及高架道路的偵測,對於市區路段及路口的交通參數偵測之研究則較少,推究其原因乃是由於高速公路及高架道路,沒有機車及行人的干擾因素,環境相對單純,偵測不易有誤差;反之,市區路口交通環境複雜,不僅存在大型車,小客車,機車,甚至存在著許多動向不定的行人,交通參數收集的難度因此大為提高。 本研究之研究核心主要包括了:(1)影像前處理、(2)前景分割、(3)陰影移除、(4)車輛追蹤、及(5)交通參數擷取,等五大項。本研究所開發之系統可由影像前處理獲得路段和路口之幾何型態,以及攝影機之初始設定參數。經影像前處理後,即可進行輸入影像之移動車輛擷取及陰影移除。目前本研究所開發之系統程式可進行一般市區路段、十字路口及五岔路口的交通參數擷取,透過參數擷取可計算各路口大車、小車、及機車之車流量參數,並可繪出各移動車輛之軌跡線,透過統計分析其結果,所擷取參數之準確率可達80%以上。

並列摘要


The traffic parameter at intersection is very important issue to traffic control. It is not only a basis of the road design, but a setting standard of the traffic signal. In recent years, more and more people research about how to develop an image detector system to collect traffic parameters. Since there is much information in the image, we can extract traffic parameter by image processing and computer vision technology. The study of image detector on highway had been developed mature enough that it could extract traffic parameter with highly accurate rate. However, the researches about data collection at intersection are rare. The possible reason may be that intersections are more complex than highways; vehicles are difficult to be tracked well at intersections. In Taiwan, there are many motorcycles and pedestrians at intersection. Because of some characteristics of it, motorcycles are difficult detect at intersections. It becomes a challenge for image detector system to have reliable ability of vehicle detection. This study is mainly composed of five stages: (1)pre-processing, (2)foreground segmentation,(3)shadow removal, (4)vehicle tracking and (5)traffic parameters extraction. The pre-processing is developed to obtain the information of road geometry and calibrate the camera. After the preprocessing is done, the foreground segmentation and shadow removal continue to segment the moving vehicles from the input images. According to the results, the average success rates of different vehicles counting are higher than 80%. Moreover, it shows that this system is capable of successfully extracting the traffic parameters, including trajectory of the moving vehicle at road and various intersections.

參考文獻


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