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研究生： 游重賢
Chung-Hsien, Yu
論文名稱： 採用改良式橢圓形感興趣區域與Sobel邊緣偵測之低躁動車道線偵測
A Low-vibration Lane Detection Using an Improved Elliptical ROI and Sobel Edge Detection
指導教授： 蘇崇彥
Su, Chung-Yen
學位類別： 碩士
Master
系所名稱： 電機工程學系
Department of Electrical Engineering
論文出版年： 2013
畢業學年度： 101
語文別： 中文
論文頁數： 66
中文關鍵詞： 車道線偵測 、邊緣偵測 、橢圓形感興趣區域 、霍夫轉換
英文關鍵詞： Lane detection, Edge detection, Elliptical ROI, Hough transform
論文種類： 學術論文
相關次數： 點閱：164  下載：16 
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    • 本論文使用垂直方向的Sobel邊緣偵測和雜訊濾波器來改善車道線追蹤時所產生的躁動問題。因為改善了躁動問題，準確率也獲得了改善。此外透過縮減影像空間處理的區域和合理的縮減橢圓形感興趣區域的大小，進而有效地提升了車道線偵測系統的處理速度。

    透過實驗分析比較結果，在晴天、夜晚與雨天的情況底下皆能獲得有效的改善。實驗使用640 × 480大小的影片測試，每秒約可處理55~60張畫面，提升了約71%左右，整體的準確率方面也由原先的96.19%，提升至97.07%。

    In the paper, we use the vertical Sobel edge detection and a noise filter to solve the problem of by pulse for the tracking mode of lane detection. Since the problem of by pulse is effectively solved, the lane detection accuracy is increased. Furthermore, we can effectively improve the processing speed of lane detection system, by reducing the image space and the elliptical ROI size.

    In experiment results, the proposed method can effectively solve the problem of by pulse in daytime, night and rain situations. The test video size is 640 × 480. The processing speed is about 55~60 frames per second. Compared with the previous method, the proposed algorithm can speed the processing of frames up to 71%, and the total accuracy is increased from 96.19% to 97.07%.

    中文摘要..................................................................i 英文摘要..................................................................ii 誌 謝..................................................................iii 目 錄..................................................................iv 圖 目 錄..................................................................vi 表 目 錄.................................................................viii 第一章 緒論............................................................- 1 - 1.1. 研究背景與動機....................................................- 1 - 1.2. 文獻回顧.........................................................- 3 - 1.3. 研究目的.........................................................- 5 - 第二章 影像處理.........................................................- 7 - 2.1. 邊緣偵測.........................................................- 7 - 2.1.1. Canny邊緣偵測....................................................- 7 - 2.1.2. Sobel邊緣偵測....................................................- 9 - 2.2. 霍夫轉換.........................................................- 10 - 第三章 適應性橢圓形ROI車道線偵測演算法......................................- 13 - 3.1. 研究作法.........................................................- 13 - 3.2. 前處理...........................................................- 15 - 3.3. 濾除雜訊遮罩......................................................- 19 - 3.4. 車道線偵測........................................................- 21 - 3.4.1. 初始畫面模式......................................................- 21 - 3.4.2. 快速追蹤模式......................................................- 23 - 3.5. 適應性的橢圓形ROI大小設定...........................................- 25 - 3.6. 限制影像空間中處理的範圍............................................- 28 - 3.7. 躁動問題的改善....................................................- 29 - 第四章 數值分析與實驗結果.................................................- 32 - 4.1. 實驗器材與環境架設.................................................- 32 - 4.2. 雜訊濾波器分析與比較................................................- 33 - 4.3. 躁動分析與討論.....................................................- 35 - 4.4. 橢圓形ROI縮減分析與比較.............................................- 38 - 4.5. 影像空間縮減分析...................................................- 41 - 4.6. 白天車道線偵測結果比較..............................................- 43 - 4.7. 夜間車道線偵測結果比較..............................................- 49 - 4.8. 雨天車道線偵測結果比較..............................................- 53 - 4.9. 實驗結果總結......................................................- 57 - 第五章 結論與未來展望....................................................- 60 - 參考文獻.................................................................- 61 - 自 傳.................................................................- 65 - 學術成就.................................................................- 66 -

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