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研究生: 鐘國豪
Kuo-Hao Chung
論文名稱: 以FPGA實現即時前車偵測系統和路標偵測系統
A Real-Time Preceding Vehicle Detection System and Road Signs Detection System Implemented on FPGA
指導教授: 王乃堅
Nai-Jian Wang
口試委員: 鍾順平
Shun-Ping Chung
方劭云
Shao-Yun Fang
郭景明
Jing-Ming Guo
莊季高
Jih-Gau Juang
學位類別: 碩士
Master
系所名稱: 電資學院 - 電機工程系
Department of Electrical Engineering
論文出版年: 2017
畢業學年度: 105
語文別: 中文
論文頁數: 54
中文關鍵詞: 即時前車偵測路標偵測現場可程式邏輯閘陣列影像處理物件連通標記
外文關鍵詞: Real-time, Preceding vehicle detection, Road signs detection, FPGA, Image process, Fast connected-component labeling
相關次數: 點閱:624下載:6
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近年來,人民生活素質提昇,所以對行車的安全也越來越重視,因此車輛安全駕駛的研究也變得越重要。現在智慧型運輸系統發展的一部分即是智慧型車輛,而智慧型車輛的發展又以安全駕駛為其最重要的一項,所以我們提出這套系統去提醒駕駛在道路上的安全。
本論文提出一個以純硬體的數位電路設計出即時前車和路標偵測系統,系統分為兩部分:(1)前車偵測系統,(2)路標偵測系統。在這前車系統的六個步驟為:(1)影像裁切,(2)陰影偵測,(3)膨脹與侵蝕,(4)物件連通標記法,(5)車輛檢查,(6)定位。路標偵測系統的六步驟為: (1)影像裁切,(2)路標顏色偵測,(3)膨脹與侵蝕,(4)物件連通標記法,(5)濾除器,(6)定位。將這些步驟分別設計成硬體電路模組,此系統是用Verilog硬體描述語言(Hardware Description Language)以純硬體的方式設計並在Altera DE2-70多媒體開發平台實現。
實驗結果顯示此系統使用了39,872(58%)個邏輯元件(logic elements)、系統功率消耗為694.33mW,前車偵測系統偵測率為90%而路標偵測系統偵測率為87%,且處理速度為每秒達30張影像(NTSC Input)。


Recently, intelligent transportation systems have been grown rapidly and become a very popular topic. With the enhancement of the living quality, the safety driving becomes more and more important. The safety driving of intelligent vehicles plays an important role and draws lots of attention in the intelligent transportation system. Many researches are proposed to provide information concerning the safety driving to the driver and decrease the dangerous driving accidents.
In this thesis, we proposed a real-time preceding vehicle detection and road signs detection system implemented on hardware design. Our system is composed of two parts: (1)Preceding vehicle detection system, (2)Road signs detection system. There are six steps in preceding vehicle detection system: (1)Image cropped, (2)Shadow detection, (3)Morphology, (4)Labeling, (5)Vehicle extraction, (6)Location. There are six steps in road signs detection system: (1)Image cropped, (2)Road signs color detection, (3)Morphology, (4)Labeling, (5)Filterings, (6)Location. Each step is designed by a hardware circuit module written in Verilog HDL. Finally, the proposed hardware architecture is implemented in the Altera DE2-70 development board to test the feasibility of our hardware design. Experimental results show that our system is achievable by 39,872 logic elements and 694.33mW in power dissipation. The detection rate of the preceding vehicle detection system is 90% and that of road signs detection system is 87%. It can operate in real-time at a frame rate of 30fps.

摘要 I ABSTRACT II 誌謝 III 目錄 IV 圖目錄 VII 表目錄 IX 第一章 緒論 1 1.1 研究動機 1 1.2 文獻回顧 2 1.3 研究方法 4 1.4 論文組織 4 第二章 開發環境與系統架構 5 2.1 演算法驗證環境 5 2.2 FPGA驗證環境 6 2.3 DE2-70開發平台簡介 6 2.4 USB DVD播放器介紹 8 2.5 NTSC介紹 9 2.6 視訊解碼晶片 9 2.7 ITU-R BT.656規格介紹 10 第三章 前車和路標偵測系統 12 3.1 車輛陰影偵測 12 3.2 路標顏色提取 12 3.3 偵測區定義 13 3.4 車輛陰影門檻值計算 14 3.5 形態學 15 3.5.1 膨脹 15 3.5.2 侵蝕 16 3.6 快速連通標記法 17 3.7 車輛陰影過濾 20 3.8 車輛長寬比例調整 20 3.9 車輛垂直與水平邊緣偵測 21 3.10 車輛車尾燈偵測 22 3.11 路標候選區過濾 23 3.11.1 路標大小濾除 23 3.11.2 路標長寬比濾除 24 3.11.3 路標顏色分部濾除 24 第四章 系統硬體實現 25 4.1 影像縮放硬體設計 27 4.2 YCBCR轉RGB硬體設計 28 4.3 陰影偵測硬體設計 28 4.4 路標顏色提取硬體設計 29 4.5 型態學與邊緣偵測硬體設計 30 4.5.1 侵蝕硬體設計 31 4.5.2 膨脹硬體設計 31 4.5.3 垂直邊緣偵測硬體設計 33 4.5.4 水平邊緣偵測硬體設計 33 4.6 物件連通標記法硬體設計 34 4.7 網格萃取法硬體設計 36 4.8 車輛門檻值硬體設計 37 第五章 實驗結果與分析 41 5.1 演算法驗證 41 5.1.1 影像序列一之實驗結果 42 5.1.2 影像序列二之實驗結果 43 5.1.3 影像序列三之實驗結果 44 5.1.4 影像序列四之實驗結果 45 5.1.5 影像序列五之實驗結果 47 5.2 DE2-70開發平台驗證 48 5.2.1 FPGA硬體資源使用 50 5.2.2 系統功耗分析表 51 5.2.3 系統Latency 51 第六章 結論與未來研究方向 52 6.1 結論 52 6.2 未來研究方向 52 參考文獻 53

[1] A. Kanitkar, B. Bharti, U.N Hivarkar, “Vision-based Preceding Vehicle Detection Using Self Shadows and Structural Edge Features,” International Conference on Image Information Processing, 2011.
[2] A. Bensrhair, M. Bertozzi, A. Broggi, P. Mich’e, S. Mousset, and G. Toulminet, “A Cooperative Approach to Vision-based Vehicle Detection,” IEEE Intelligent Transportation Systems Conference Proceedings, pp. 207-212, 2001.
[3] M. Bertozzi, A. Broggi, “A Aparallel Real-time Stereo Vision System for Generic Obstacle and Lane Detection,” IEEE Transactions on Image Processing, vol. 7, no. 1, pp. 62-81, 1998.
[4] T. Naito, T. Ito, Y. Kaneda, “The Obstacle Detection Method Using Optical Flow Estimation at the Edge Image,” Intelligent Vehicles Symposium Istanbul, pp. 817-822, 2007.
[5] T. Jin, L. Xiong, X. Bin, C. Fangyan, and L. Bo, “A Method for Traffic Sign Detection Tracking and Recognition,” The 5th International Conference on Computer Science and Education, pp. 189-194, 2010.
[6] R. Malik, J. Khurshid, and S.N. Ahmad, “Road Sign Detection and Recognition Using Color Segmentation, Shape Analysis and Template Matching,” Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, pp. 3556-3560, 2007.
[7] M. Benallal, and J. Meunier, “Real-time Color Segmentation of Road Signs,” IEEE Canadian Conference on Electrical and Computer Engineering, vol. 3, pp. 1823-1826, 2003.
[8] H. Fleyeh, “Color Detection and Segmentation for Road and Traffic Signs,” IEEE Conference in Cybernetic and Intelligence Systems, pp. 809-814, 2004.
[9] L. He, Y. Chao, K. Suzuki, “A Run-based Two-scan Labeling Algorithm,” IEEE Transactions on Image Processing, vol. 17, no. 5, pp. 749-756, 2008.
[10] L. He, Y. Chao, K. Suzuki, and K. Wu, “Fast Connected-component Labeling,” Pattern Recognition, vol. 42, pp. 1977-1987, 2009.
[11] Z. Sun, R.Miller, G. Bebis, and D. DiMeo, “A Real-time Precrash Vehicle Detection System,” IEEE Workshop of Computer Vision, pp. 171-176, 2002.
[12] A. Bensrhair, M. Bertozzi, A. Broggi, P. Mic’e, S. Mousset, and G. Toulminet, “A Cooperative Approach to Vision-based Vehicle Detection,” IEEE Intelligent Transportation Systems Conference Proceedings, pp. 209-214, 2001.
[13] Z. Cui, S. Yang, H. Tsai, “A Vision-based Hierarchical Framework for Autonomous Front Vehicle Taillights Detection and Signal Recognition,” IEEE 18th International Conference on Intelligent Transportation Systems, pp. 931-937, 2015.
[14] E. Onat, “FPGA Implementation of Real-time Video Signal Processing Using Sobel, Robert, and Laplacian Filters,” The 20th Signal Processing and Communications Applications Conference, 2017.
[15] 許維仁,基於SVM之即時路標偵測與提取系統,國立台灣科技大學電機工程系碩士論文,民國一百零五年。
[16] Terasic, Altera DE2-70 datasheet.
URL:https://www.terasic.com.tw/
[17] USB DVD 268 技術手冊,
URL:https://www.momoshop.com.tw/goods/GoodsDetail.jspi_code=2821237/

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