交通號誌辨識

Traffic Light Recognition

呂國豪(Kuo-Hao Lu)

指導教授 ： 陳淑媛 ； 王照明

元智大學/資訊學院/資訊工程學系/碩士(2004年)

摘要

由於現代化運輸工具技術的不斷精進，使得加強感應器對周遭環境的偵測，以提供駕駛者充分資訊，進而建構一個迅速、安全和方便的駕駛環境已非遙不可及的夢想。
本論文即在提出一自動化的交通號誌辨識系統，以提供充分的訊息，讓駕駛者可正確判斷道路環境，進而協助智慧型運輸系統的建置完成。所提方法可適用於固定式或移動式攝影機，故有其方便性及實用性。
所提方法主要分為三個階段:交通號誌的偵測、擷取及分類。這三階段的設計原理分別是根基於色彩資訊、區塊資訊和幾何特性。在偵測階段，首先將色彩空間RGB轉為HSI，以偵測出具有號誌特定色彩的區塊，接著利用形態學的方法補強區塊的缺損及去除雜訊。在擷取階段，主要是利用區塊標記技巧偵測出號誌可能的位置，接著使用邊緣偵測法將區塊邊緣特徵擷取出來，以利後續分類階段利用號誌幾何外型特徵達成分類目的，亦即辨識出圓形號誌燈和箭頭號誌燈。
最後，經由眾多實驗證實所提方法確實有效且可行。

關鍵字

智慧型運輸系統 ； 交通號誌偵測 ； 交通號誌擷取 ； 通號誌辨識 ； 顏色辨識

並列摘要

Advanced technology improves the capabilities of modern vehicles. The innovations of senor-based systems support surrounding survey of the vehicle and display relevant information to the driver. Thus, construction of a safety, convenient and efficiency driving environment can be achieved.
This paper is to propose an automatic traffic light recognition system so that car drivers have sufficient information to make a correct decision. This in turn facilitates the construction of ITS (Intelligent Transportation System). The proposed method can be applied not only to fixed camera but also to movable camera.
Our method consists of three phases: traffic light detection, extraction and classification. The three phases are based on color information, region information and geometric and appearance constraints. In the detection stage, the RGB color space is first converted into HSI color space to detect those regions with specific colors of traffic lights. The morphology technology is then employed to remove hole and noise. In the extraction stage, region labeling is involved to detect candidate regions of traffic lights. Border detection is then employed to obtain region border. In the classification stage, geometric and appearance constrains are derived respectively from traffic light shape and color and used for classification. In this study, traffic lights of circle and arrow shape can both be coped with.
Various experiments have been conducted to demonstrate the effectiveness and practicability of proposed method.

並列關鍵字

Intelligent transportation system ； traffic light detection ； traffic light extraction ； traffic light recognition ； color identification

參考文獻

[3] G. Piccioli, E.D. Michel, P. Parodi, and M. Campani, “Robust method for road sign detection and recognition,” Image and Vision Computing, vol. 14, no. 3 , pp. 209-223, 1996.

[4] A.D.L. Escalera, E. Moreno, M.A. Salichs, and J.M. Armingol, “Road traffic sign detection and classification,” IEEE Transactions on Industrial Electronics, vol. 44, no. 6, 1997.

[5] S.H. Hsu and C.L. Huang, “Road sign detection and recognition using matching pursuit method,” Image and Vision Computing, vol. 19, no. 3, pp. 119-129, 2001.

[6] A.M. Landraud, “Image restoration and enhancement of characters using convex projection methods,” Computer Vision, Graphics and Image Processing, vol. 3, pp. 85-92, 1991.

[7] C.S. Fuh and H.B. Liu, “Projection for pattern recognition,” Image and Vision Computing, vol. 16, no. 9-10, pp. 677-687, 1998.