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研究生:陳世祥
研究生(外文):SHI-XIANG CHEN
論文名稱:擴增實境應用於車載物聯網之設計與實現
論文名稱(外文):Design and Implementation of the Augmented Reality Applied to the Internet of Vehicles
指導教授:白能勝白能勝引用關係
指導教授(外文):Neng-Sheng Pai
學位類別:碩士
校院名稱:國立勤益科技大學
系所名稱:電機工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:中文
論文頁數:79
中文關鍵詞:擴增實境車載物聯網霍夫轉換卡爾曼濾波器Sobel邊緣檢測Harris角點偵測支持向量機RSA演算法
外文關鍵詞:Augmented RealityInternet of VehicleHough TransformKalman FilterSobel Edge DetectorHarris Corner DetectorSupport Vector MachineRSA Algorithm
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本論文旨在開發一具有擴增實境技術之車載物聯網系統,系統主要可分為車道線偏移警示、前車偵測防撞警示以及車載物聯網三部分。首先,本論文透過霍夫轉換在影像感興趣區域中,找出可能為車道線的位置,並利用卡爾曼濾波器去除道路雜訊,預測實際車道線之位置,最後利用偏移決策來判斷車輛是否發生偏移之情況。前車偵測防撞警示部分,則是分別利用Sobel邊緣檢測以及偵測車輛尾燈方法,找出車輛假定區域,並利用Harris角點偵測法取得假定區域內之特徵參數。驗證假定區域之方法則是使用支持向量機進行車輛辨識,最後利用碰撞決策判斷是否與前車距離過近。車載物聯網部分,本論文加入RSA加密演算法,藉由公鑰與私鑰來加密與解密正確訊息並辨認是否為車主。當車主取得車輛控制之權限後,即可使用行車輔助系統以及取得車輛當前資訊。最後本論文藉由上述之方法,將智能眼鏡結合擴增實境應用於車載物聯網,讓駕駛能夠輕易地透過智能眼鏡獲得車輛資訊以及警告資訊,這不僅提高駕駛操作的便利性,同時也提升行車的安全性。
The goal of this study is to develop an Internet of Vehicle (IoV) system with Augmented Reality (AR) technology. The system deals mainly with three subjects: Lane Departure Warning, Forward Collision Detection and Warning, and IoV. Firstly, to deal with the subject of lane departure warning, Hough Transform is used in this study to extract likely the position of lane lines in the region of interest of an image. Kalman Filter is further employed to remove noises and estimate the actual positions of lane lines. Lane departure decision is then performed to determine if a lane departure situation occurs. Secondly, Sobel Edge Detector and Vehicle Taillight Detection method are used to locate the hypothetical generation of the vehicle. The characteristic parameters within the hypothetical generation can also be obtained with Harris Corner Detection method. To verify hypothetical generation, Support Vector Machine (SVM) is used to identify vehicles in this study. Collision decision is then applied to determine if the distance between two vehicles is too short and thus fulfills the goal of forward collision detection and warning. In addition, a secure and easy-to-use IoV is realized with the use of RSA encryption algorithm, which uses public keys and private keys to encrypt and decrypt messages in order to achieve the task of user identification. Upon gaining the control of the vehicle, the driver has full access to the most up-to-date information provided by the driver assistance system. Lastly, the study incorporating the above methods, to realize the smart glasses combined with augmented reality applied to the internet of vehicles in this study. Smart glasses can provide the vehicle drivers easy access to the information about the vehicle and warnings, which helps enhance driver convenience and safety greatly.
摘要 I
Abstract II
致謝 III
目錄 IV
圖目錄 VI
表目錄 VIII
第一章 緒論 1
1.1 研究動機與背景 1
1.2 文獻回顧 4
1.3 論文目標 7
1.4 論文架構 7
第二章 系統架構與硬體介紹 9
2.1 系統架構 9
2.2 硬體介紹 10
2.2.1 影像處理端硬體 10
2.2.2 車載物聯網端 11
2.2.3 客戶端 15
第三章 車道線偏移警示 17
3.1概述 17
3.2影像前處理 18
3.2.1 感興趣區域與轉換色彩空間(ROI and Convert Color Space) 18
3.2.2 均值濾波(Mean Filter) 20
3.2.3 邊緣檢測(Edge Detection) 21
3.3 車道線偵測 22
3.3.1 霍夫轉換(Hough Transform) 22
3.3.2 卡爾曼濾波器(Kalman Filter) 24
3.3.2車道線偏移決策 28
第四章 前車偵測防撞警示 29
4.1 概述 29
4.2 產生假設區域(Hypothesis Generation, HG) 30
4.2.1 消失點偵測與車道遮罩 30
4.2.2 日間前景目標擷取 31
4.2.3 路面雜訊濾除 34
4.2.4 夜間前景目標擷取 36
4.2.5 車輛邊緣特徵提取 37
4.3 驗證假設區域(Hypothesis Verification, HV) 40
4.3.1 Harris角點偵測(Harris Conner Detection) 40
4.3.2 支持向量機(Support Vector Machine, SVM) 43
4.3.2.1 線性SVM 44
4.3.2.2 線性不可分SVM 47
4.3.2.3 非線性SVM 48
4.3.2.4 交叉驗證 51
4.3.3 前車碰撞決策 52
第五章 物聯網資訊安全 53
5.1概述 53
5.2公開金鑰密碼系統 55
5.3 RSA加密演算法 56
第六章 實驗結果 59
6.1 概述 59
6.2 霍夫轉換進行車道線偵測之結果 62
6.3 加入卡爾曼濾波進行車道線偵測之實驗結果 63
6.4 車道偏移警示之實驗結果 65
6.5 SVM前車辨識及防碰撞警示之實驗結果 66
6.6 車載物聯網應用之實驗結果 68
第七章 結論與未來展望 73
7.1 結論 73
7.2 未來展望 74
參考文獻 75
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