博碩士論文 103552002 詳細資訊




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姓名 吳祈寬(Chi-Kuan Wu)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 嵌入式車道偏移警示系統設計與實作
(Design and Implementation of an Embedded Lane Departure Warning System)
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摘要(中) 車道偏移警示系統是防範交通事故的主要駕駛輔助系統之一。本研究設計了一個嵌入式車道偏移警示系統,其作法包含影像前置處理、車道標記特徵分析、和左右車道線擷取、車道偏移判斷等四個主要功能模組。其中,車道標記特徵分析採用決策樹特徵分析,來篩選出候選車道標記,候選車道可進一步透過最小平方差進行直線參數偵測,以取得候選車道之直線模型,再以幾何特徵配對方式來找出最終車道線標記,最後再根據左右車道線來估計目前偏移量,在偏移量超過設定門檻值時,系統判定即將發生偏移,將發出警示提醒駕駛。對於真實環境的高雜訊道路影像,此一方法具有良好的強健性。本研究將系統實現於Raspberry Pi3嵌入式平台,以各種不同道路場景實際錄製之連續影像進行測試,實驗結果顯示出我們系統具有良好的可靠度,車道偵測正確率平均有84%以上,並且運作效能可達每秒30張即時需求。
摘要(英)
The lane departure warning system is one of the main driving assistance systems to prevent traffic accidents. This study designed an embedded lane departure warning system, including image pre-processing, lane mark feature analysis, and left and right lane line extract, lane offset judgment and other four main functional modules. In this paper, the feature analysis of the lane mark is used to analyze the characteristics of the decision tree to select the candidate lane mark. The candidate lane can be further detected by the minimum squared difference to obtain the linear model of the candidate lane, and then the geometric characteristic pairing method The final lane mark, and finally according to the left and right lane line to estimate the current offset, the offset exceeds the set threshold, the system is about to be offset, the system will issue a warning to remind the driver. This method is robust in the real environment of high noise road image. In this study, the system is implemented on the Raspberry Pi3 embedded platform. The experimental results show that our system has good reliability, and the average correct rate of lane detection is more than 84% and operational efficiency of up to 30 real-time requirements per second.
關鍵字(中) ★ 車道偏移警示系統
★ 車道偏移
★ 車道偵測
★ 決策樹
★ 特徵分析
★ 嵌入式
關鍵字(英) ★ LDWS
★ Lane Departure Warning
★ Lane Detection
★ Decision Tree
★ feature analysis
★ Embedded
論文目次
摘要 i
Abstract ii
誌謝 iii
目錄 iv
圖目錄 vii
表目錄 x
第一章、緒論 1
1.1研究背景 1
1.2研究目的 2
1.3論文架構 2
第二章、文獻回顧 3
2.1影像前置處理 4
2.1.1色彩空間轉換 4
2.1.2影像分割 4
2.1.3影像邊緣強度計算 5
2.2車道特徵分析 6
2.2.1輪廓跟蹤連通元件標記法 6
2.2.3特徵分析 8
2.3直線參數偵測 9
2.4偏移判斷與警示 11
第三章、車道偏移警示系統設計 13
3.1 MIAT系統設計方法論 13
3.2系統架構設計 14
3.2.1影像前置處理 14
3.2.2車道標記特徵分析 15
3.2.3左右車道線擷取 16
3.3演算法離散事件建模 17
3.3.1影像前置處理離散事件建模 18
3.3.2車道標記特徵分析離散事件建模 19
3.3.3左右車道線擷取離散事件建模 21
3.4高階軟體合成 22
3.4.1車輛偏移警示系統軟體合成 24
3.4.2影像前置處理離散事件軟體合成 25
3.4.3車道標記特徵分析離散事件軟體合成 26
3.4.4左右車道擷取離散事件軟體合成 27
第四章、系統實作與整合驗證 28
4.1實驗平台 28
4.2車道偏移警示系統軟體設計與實作 33
4.3系統驗證與實驗 38
4.3.1車道偵測正確率驗證 39
4.3.2車輛偏移警示驗證 40
4.3.3處理效能驗證 41
4.4實驗結果討論 42
第五章、結論 44
5.1結論 44
5.2未來研究方向 45
參考文獻 46
參考文獻
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指導教授 陳慶瀚(Ching-Han Chen) 審核日期 2017-7-24
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