跳到主要內容

臺灣博碩士論文加值系統

(18.97.14.87) 您好!臺灣時間:2025/01/13 04:25
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:廖士元
研究生(外文):Shi-Yuan Liao
論文名稱:以分段式二次曲線作道路偵測
論文名稱(外文):Using Two-Segments Quadratic Polynomial Curve Approximation for Road Boundary Detection
指導教授:陳明揚
指導教授(外文):Ming-Yang Chen
學位類別:碩士
校院名稱:國立中正大學
系所名稱:電機工程所
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:2009
畢業學年度:97
語文別:中文
論文頁數:38
中文關鍵詞:道路偵測誤差平方和近似曲線分段點分段式二次曲線
外文關鍵詞:sum of squared errorroad detectiondemarcation pointpiecewise quadratic polynomial curve
相關次數:
  • 被引用被引用:0
  • 點閱點閱:313
  • 評分評分:
  • 下載下載:28
  • 收藏至我的研究室書目清單書目收藏:0
本論文提出一套道路偵測的方式,以求更貼切標示出彎路之道路線。首先將一條二次曲線方程式,以所偵測到的邊緣點座標值代入,而找出其誤差平方和為最小之多項式係數解,能得到道路線的近似曲線。而本研究乃是搜尋出最適當的邊緣點當作分段點,接著分別求出此點所區分出的上、下兩部份邊緣點之近似二次曲線,此兩部份的誤差平方和,合併計算後為最小。最後結合此兩部份的近似曲線,即為分段式二次曲線。
藉由在不同情況的影像中,採取本研究所提出的偵測方法來測試,能發現在某些難以準確描述道路線的路段,均可由我們所提出的方法適當地標示出來,顯示本研究於道路偵測時,能夠達到不錯的成果。
In this thesis, we propose a new way to describe the road boundary more accurately. Originally, based on the 2nd–order polynomial equation, we can substitute the coordinates of the boundary points into the equation and minimize the sum of square errors to obtain the polynomial solution and hence the approximate curve. However, the quadratic polynomial curve cannot fit all road boundary curves well, especially when the road has abrupt turning point. In these cases, even though the higher order polynomial can be applied yet too complicated to solve.
In this research, we try to find a boundary point which separates the whole curve into two segments, and the total sum of square errors of the two curve segments must be minimized. According to our experiments, the curves turned out are definitely more accurate, especially the road has sharper turning point. The time needed to spend for this is to be considered next.
致謝詞 .................................................. I
中文摘要................................................ II
英文摘要 .............................................. III
目錄.................................................... IV
圖目錄 ................................................. VI
表目錄 ................................................. IX
第一章 簡介 ............................................. 1
1.1 動機與目的 .......................................... 1
1.1.1 動機 .............................................. 1
1.1.2 目的 .............................................. 1
1.2 相關研究 ............................................ 2
1.3 系統之基本功能與架構 ................................ 3
1.3.1系統之基本功能 ..................................... 3
1.3.2系統之架構 ......................................... 3
第二章 道路偵測之影像前置處理 ........................... 6
2.1 影像強化 ............................................ 6
2.2 影像邊緣點之偵測 .................................... 7
2.3 影像之相連成標記法 .................................. 9
第三章 分段式二次曲線近似法 ............................ 10
3.1 不分段二次曲線 ..................................... 10
3.2 分段式二次曲線 ..................................... 12
3.2.1 下半段二次曲線 ................................... 13
3.2.2 上半段二次曲線 ................................... 14
3.2.3 產生分段式二次曲線 ............................... 16
3.3 誤差均方根 ......................................... 17
第四章 道路偵測之分段式二次曲線程序 .................... 18
4.1 不分段二次曲線 ..................................... 18
4.2 分段點的決定 ....................................... 18
4.2.1 逐一比較法 ....................................... 18
4.2.2 縮減搜尋範圍比較法 ............................... 18
4.3 分段式二次曲線 ..................................... 20
4.4 近似曲線圖的比較與採用 ............................. 20
第五章 實驗結果與分析 .................................. 21
5.1 實驗設備與環境 ..................................... 21
5.2 實驗結果 ........................................... 22
5.3 成果分析 ........................................... 30
第六章 結論與未來展望 .................................. 32
6.1 研究結論 ........................................... 32
6.2 未來展望 ........................................... 32
參考文獻 ............................................... 34
附錄一 ................................................. 37
作者簡介 ............................................... 38
[1] R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice-Hall, New Jersey, Second Edition,2002.
[2] 井上誠喜、八木伸行、林 正樹、中頇英輔、三谷公二、奧井誠人, ”C 語言數位影像處理”, 全華科技圖書股份有限公司, Taipei, Second Edition, 2007.
[3] Z. Jia, A. Balasuriya, and S. Challa, “Recent Developments in Vision Based Target Tracking for Autonomous Vehicles Navigation”, ITSC ''06. IEEE
Intelligent Transportation Systems Conference, pp. 765-770, 2006.
[4] B. Zheng, B. Tian, J. Duan, and D. Gao, “Automatic Detection Technique of Preceding Lane and Vehicle”, ICAL IEEE International Conference on Automation and Logistics, pp. 1370-1375, 2008.
[5] E. Y. Chung, H. C. Jung, E. Chang, and I. S. Lee, “Vision Based for Lane Change Decision Aid System”, The 1st International Forum on Strategic Technology, pp.10-13, 2006.
[6] J. Lan and Y. Shi, “Vehicle Detection and Recognition Based on A MEMS Magnetic Sensor”, NEMS 4th IEEE International Conference on Nano/Micro Engineered and Molecular Systems, pp 404-408, 2009.
[7] J. Cao and L. Li, “Vehicle Objects Detection of Video Images Based on Gray-Scale Characteristics”, ETCS ''09. First International Workshop on Education Technology and Computer Science, Vol. 2, pp. 936-940, 2009.
[8] T. Kato, Y. Ninomiya, and I. Masaki, “An Obstacle Detection Method by Fusion of Radar and Motion Stereo”, IEEE Transactions on Intelligent Transportation Systems, Vol. 3, No. 3, pp. 182-188, 2002.
[9] K. Yamaguchi, T. Kato, and Y. Ninomiya, “Moving Obstacle Detection Using Monocular Vision”, IEEE Intelligent Vehicles Symposium, pp. 288-293, 2006.
[10] H. C. Moon, H. C. Lee, and J. H. Kim, “Obstacle Detecting System of Unmanned Ground Vehicle”, International Joint Conference SICE-ICASE, pp. 1295-1299,
2006.
[11] A. A. Assidiq, O. O. Khalifa, M. R. Islam, and S. Khan, “Real Time Lane Detection for Autonomous Vehicles”, ICCCE International Conference on Computer and Communication Engineering, pp. 82-88, 2008.
[12] L.-W. Tsai, J.-W. Hsieh, C.-H. Chuang, Y.-J. Tseng, K.-C. Fan, C.-C. Lee, “Road Sign Detection Using Eigen Colour”, IET Computer Vision, Vol. 2, No.3, pp. 164-177, 2008.
[13] J. Park, J. Lee, Y. Park, and S. W. Kim, “AGV Parking System Based on Tracking Landmark”, ECTICON 6th International Conference on Electrical engineering/Eectronics, Computer, Telecommunications and Information Technology, Vo. 1, pp. 340-343, 2009.
[14] Y. Wang, D. Chen, C. Shi, “Vision-Based Road Detection by Adaptive Region Segmentation and Edge Constraint”, IITA ''08. Second International Symposium on Intelligent Information Technology Appication, Vol. 1, pp. 342-346, 2008.
[15] H. Kurihata, T. Takahashi, I. Ide, Y.o Mekada, H. Murase, Y. Tamatsu, T. Miyahara, “Rainy Weather Recognition from In-Vehicle Camera Images for Driver Assistance”, IEEE Intelligent Vehicles Symposium, pp. 205-210, 2005.
[16] M.-Y. Chern and P.-C. Hou, “The Lane Recognition and Vehicle Detection at Night for A Camera-Assisted Car on Highway”, ICRA ''03. IEEE International Conference on Robotics and Automation, Vol. 2, pp. 2110-2115, 2003.
[17] Y.-L. Chen, C.-T. Lin, C.-J. Fan, C.-M. Hsieh, and B.-F. Wu, “Vision-Based Nighttime Vehicle Detection and Range Estimation for Driver Assistance”, SMC IEEE International Conference on Systems, Man and Cybernetics, pp. 2988-2993,2008.
[18] K. Kluge and S. Lakshmanan, “A Deformable-Template Approach to Lane Detection”, the Intelligent Vehicles ''95 Symposium, pp. 54-59.
[19] D. J. Kang, J. W. Choi, and I. S. Kweon, “Finding and Tracking Road Lanes Using “Line-Snakes””, IEEE Intelligent Vehicles Symposium, pp. 189-194, 1996.
[20] F. Guichard and J.-P. Tarel, “Curve Finder Combining Perceptual Grouping and A Kalman Like Fitting”, The Seventh IEEE International Conference on Computer Vision, Vol. 2, pp. 1003-1008, 1999.
[21] Y. Wang, E. K. Teoh, and D. Shen, “Lane Detection Using B-Snake”, International Conference on Information Intelligence and Systems, pp. 438-443,1999.
[22] Z. Kim, “Realtime Lane Tracking of Curved Local Road”, ITSC ''06. IEEE Intelligent Transportation Systems Conference, pp. 1149-1155, 2006.
[23] J. Canny, “A Computational Approach to Edge Detection”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-8, No. 6, pp. 679-698,
1986.
[24] 美國聯邦航空管理局(FAA),http://www.faa.gov/.
[25] D. M. Gavrila, U. Franke, C. Wohler, and S. Gorzig, “Real Time Vision for Intelligent Vehicles”, IEEE Instrumentation & Measurement Magazine, Vol. 4, No. 2, pp. 22-27, 2001.
[26] 王壽云,「飛機導航技術的變革」,通訊雜誌,第8 期,July 1994.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top