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研究生:吳孟儒
研究生(外文):WU,MENG-JU
論文名稱:使用循序式模擬退火演算法之車道偵測系統
論文名稱(外文):A Lane Detection System Based on Sequential Simulated Annealing Algorithm
指導教授:蘇建焜
指導教授(外文):SU,CHIEN-KUN
口試委員:辛錫進陳肇業
口試委員(外文):HSIN,HSI-CHINCHEN,TSAO-YEH
口試日期:2016-06-29
學位類別:碩士
校院名稱:中華大學
系所名稱:電機工程學系
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:2016
畢業學年度:104
語文別:中文
論文頁數:67
中文關鍵詞:模擬退火霍夫演算法二值化車道偵測
外文關鍵詞:simulated annealing algorithmHough transformbinarizationlane detection
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本論文提出一種使用循序式模擬退火演算法的偵測系統來偵測車道,實驗證明循序式模擬退火演算法偵測車道準確度可達90%,此方法能節省大量記憶體空間,其使用之記憶體空間僅為現行常用的霍夫轉換(Hough transform)演算法的二分之一,可改善現有許多商品記憶體需求過大之缺點,極具商業應用潛力。

我們使用一支架設於車上的行車紀錄器,擷取前方道路影像及行車狀況。主要研究針對白天、夜晚高速公路上如何有效偵測車道,達到安全的輔助車輛駕駛。在偵測車道中,前置處理方法如下:彩色影像轉灰階影像、二值化、Sobel 邊緣偵測、影像侵蝕與膨脹、雜訊的消除等技術達到影像清晰化,經過前處理之後可得到含少數雜訊之車道影像。接著使用循序式模擬退火圖形偵測方法偵測車道位置,此方法可搜尋到一組圖形參數,使得影像上的點到這組圖形的距離為最小,接下來將偵測到的圖形所包含的點移除,再對剩餘的資料重複偵測,直到全部圖形偵測完畢。



A lane detection system that is based on the sequential simulated annealing algorithm is proposed in the thesis. Experimental results show that the correct recognition rate of the sequential simulated-annealing-algorithm-based lane detection system can reach 90%. Compared to the popular Hough transform algorithm, the simulated annealing algorithm uses fewer memories. It consumes about half of the memories used in the Hough transform method. Therefore, the proposed system can alleviate the problem of a large memory demand in Hough-transform-based systems, and it is of much potential in commercial applications.

In our research, a dash cam installed in a car was used to record the road images in front of the car. Day-time and night-time still color images on freeways are used as the inputs of the proposed system. The research goal is to effectively detect the lane side lines to be used for improving driving safety. The pre-processing technique in the proposed system includes color to gray-level transformation, binarization, Sobel edge detection, morphology operations (erosion and dilation), and noise removal. After pre-processing, a binary lane image with some noise is obtained, and the sequential simulated annealing pattern detection method is applied for detecting lane position. The sequential simulated annealing pattern detection method can determine a set of parameter vectors with global minimal error. The detected patterns are removed from the binary image, and the remaining binary image is continue to be processed by using the sequential simulated annealing pattern detection method until all patterns are processed completely.


中文摘要.................................................................................................................................i
英文摘要................................................................................................................................ii
誌謝.......................................................................................................................................iii
目錄.......................................................................................................................................iv
表目錄...................................................................................................................................vi
圖目錄..................................................................................................................................vii
第一章 緒論......................................................................................................................1
1.1 研究動機與背景.................................................................................................1
1.2 研究方法及目的.................................................................................................3
1.3 章節概要.............................................................................................................4
第二章 車道偵測相關技術文獻......................................................................................8
2.1 色彩空間.............................................................................................................8
2.1.1 RGB色彩模型.........................................................................................8
2.1.2 YIQ色彩模型........................................................................................11
2.1.3 YUV與YCbCr色彩模型.....................................................................12
2.1.4 HSV色彩模型.......................................................................................14
2.2 抓取車道線特徵...............................................................................................16
2.2.1 灰階轉換................................................................................................16
2.2.2 二值化....................................................................................................16
2.2.3 自動門檻二值化....................................................................................18
2.2.3.1 百分比法.................................................................................18
2.2.3.2 平均灰階法.............................................................................18
2.2.3.3 歐蘇法.....................................................................................19
2.3 邊緣偵測...........................................................................................................21
2.4 形態學...............................................................................................................23
2.4.1 膨脹........................................................................................................23
2.4.2 侵蝕........................................................................................................26
2.5 自動目標物擷取...............................................................................................29
2.6 霍夫轉換...........................................................................................................32
第三章 研究及實驗方法................................................................................................37
3.1 前置處理...........................................................................................................37
3.1.1 灰階轉換...............................................................................................38
3.1.2 二值化影像...........................................................................................39
3.1.3 邊緣偵測...............................................................................................41
3.1.4 侵蝕與膨脹...........................................................................................43
3.1.5 八連通...................................................................................................45
3.2 循序式模擬退火演算法...................................................................................47
3.2.1 定義圖形參數.......................................................................................47
3.2.2 定義降溫公式.......................................................................................47
3.2.3 定義誤差...............................................................................................47
3.2.4 使用模擬退火演算法尋找直線參數...................................................48
3.2.5 循序式圖形偵測系統...........................................................................51
第四章 實驗結果與討論................................................................................................56
4.1 環境描述...........................................................................................................56
4.2 實驗結果...........................................................................................................57
第五章 結論與未來展望................................................................................................64
參考文獻..............................................................................................................................65


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