臺灣博碩士論文加值系統

本研究目的是在目前手機市占率最高的Android作業系統上，描述如何在利用影像處理技術偵測車道線與前方車輛偵測，判斷車道線與前車位置對駕駛提出警報。在實現系統時，必須考慮硬體運算限制，我們透過手持式設備拍攝車輛在道路上行進間影像，經過降低畫面維度與取ROI(Region of Interest, ROI)概念，只針對特定區域做運算，可大幅降低運算量，車道線偵測部分先劃分偵測範圍後，對屬於同一車道線的邊緣點做連結，取出車道線位置。偵測前車部分利用車道線位置定義成偵測前方車輛的空間，並由車輛強烈邊緣特性，偵測前方車輛位置。最後，實驗結果表明，本系統能夠在手持式移動設備上有效實現且準確的提出警報。

This article reports our experience in the design and implementation of an image-processing based driving support system targeted at smart phones. The low computing power of hand hold devices is the primary design concern. Several measures had been taken to cope with the limitations. In lane departure detection, focusing only on region of interesting after down sampling of raw image frame can greatly reduce the computational complexity. In the detection of vehicle ahead, after edge detection, domain knowledge is incorporated into the system to further improve the speed and accuracy of the detection. Measured data from onsite test reveal that the proposed system outperforms previous approaches in both speed and reliability.

目 錄

摘　要 II
ABSTRACT III
目 錄 IV
表目錄 VI
圖目錄 VII
第一章 緒論 1
1.1 前言 1
1.2 研究動機與目的 2
1.3 論文架構 4
第二章 相關研究 6
2.1 機器視覺 6
2.2 行車安全輔助系統 7
2.3 車道偵測 9
2.4 前車偵測 12
第三章 系統實作 15
3.1 系統架構 15
3.2 車道線偵測 16
3.2.1 降低維度 17
3.2.2 邊緣偵測 18
3.2.3強化車道線邊緣特徵 20
3.2.4車道邊緣提取 21
3.2.5 邊緣點標記 21
3.2.6 車道線擷取 22
3.2.7 車道偏移決策 27
3.3 前車偵測 30
3.3.1 平滑處理 31
3.3.2 垂直水平邊緣偵測 32
3.3.3 車輛底邊偵測 34
3.3.4 碰撞預警決策 37
第四章 系統結果 40
4.1 實驗設備與環境 40
4.2 車道偵測 42
4.3 實作成果比較與效能分析 45
4.4 前車偵測 52
4.5 系統呈現與警報分析 54
第五章 結論與未來展望 59
5.1 研究結論 59
5.2 未來展望 61
參考文獻 63

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