博碩士論文 101322049 詳細資訊




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姓名 陳林君(Lin-jyun Chen)  查詢紙本館藏   畢業系所 土木工程學系
論文名稱 影像辨識技術應用於鋪面破壞調查之研究
(A Study of Image Recognition Technology Applying to Pavement Distress)
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摘要(中) 巡查為道路養護的基本工作,鋪面破壞易造成用路人行車安全;而鋪面破壞也間接的影響鋪面平整度,而國內各級道路主管機關也積極推動道路齊平,為了有效落實巡查作業,近年來國內外均有研發道路檢測設備;將檢測設備搭載於車輛執行巡查作業,而設備中影像擷取器使用最新科技產品,如智慧型手機、平板電腦、CCD Camera等影像擷取設備,以影像方式蒐集鋪面影像,故本研究為以影像為基礎,研擬自動化巡查與辨識系統,將巡查蒐集的鋪面影像,利用影像處理技術將鋪面破壞特徵擷取,並將破壞影像進行量測,以鋪面狀況指標將破壞類型之嚴重程度作判定。
本研究為利用CCD Camera進行鋪面影像拍攝,將蒐集之鋪面影像進行破壞特徵辨識。相機架設於車輛中所拍攝為傾斜影像,使用形態校正轉為正投影。界定鋪面破壞特徵辨識範圍,使用直線與車道偵測方法偵測車道標線;以標線內作為辨識範圍界定,裁切辨識範圍以外的影像背景。接著以影像處理技術將影像進行光源校正、影像二值化及形態學中的侵蝕與膨脹、邊框刪除、填滿等方法進行破壞特徵擷取。最後將破壞特徵使用影像量測方式將鋪面破壞結果計算出。
研究結果將影像形態校正後之影像進行驗證,經距離及面積測試實驗結果,定義出鋪面影像擷取距離為2.5公尺,完整擷取檢測之鋪面影像。使用影像處理技術將鋪面影像中的坑洞、人手孔、縱橫向裂縫特徵擷取出來,以影像量測方式將破壞面積、長度、寬度進行量測。最後將量測結果依據鋪面狀況指標判定破壞程度之等級,並將此技術導入道路巡查流程,將蒐集之破壞資料匯入鋪面維護管理系統,作為未來鋪面工程生命週期評估及維護週期判定使用。
摘要(英) Road inspection is the groundwork for road maintenance. Pavement distress tends to put the safety of the road-users are at risk and impact the pavement smoothness indirectly. In addition to the efforts made by domestic road authorities in actively implementing the plan of road smoothness, R&D of road testing equipment, which are built in vehicles, has been made at home and abroad for the past few years in order to facilitate road inspection. Image capture devices featuring the latest technologies, such as smart phones, tablets and CCD Cameras, are installed in the testing equipment to collect photographic images of the pavement. Therefore, in this study, images are used as the basis. An automatic inspection and recognition system is developed to capture pavement images. An image processing technology is then used to capture pavement distress feature, measure the distress images and judge the severity of damage with the pavement condition index.
This study involves using CCD Cameras to take pictures of the pavement and recognizing the pavement distress feature out of them. The photographic images captured by the cameras in the vehicle are slant and then corrected orthographically. The straight line and lane detection is employed to detect the lane markings which are taken as the limits of the recognition scope of pavement distress feature. The image background outside of the scope is cropped. Then the pavement distress feature is captured through illumination adjustment made with image processing technology, image binary processing, and methodology used in morphology such as erosion and dilation, border removal and hole filling. Finally, the pavement distress feature is calculated with image measurements.
This research result is then verified against the calibrated images. With distance and area measurements, it is determined that the distance for capturing complete pavement image for detection is 2.5 meters. The feature of potholes, manhole, longitudinal / transverse cracking is cropped out of the pavement images with image process technology. The area, length and width of the pavement distress is measured with image measuring technology. At last, the measurements are used to severity of the pavement distress, compared against the pavement condition index. This technology is incorporated into the road inspection procedure by importing the collected data for pavement distress into the Pavement Management System as the reference in assessing the pavement engineering life cycle and determining the maintenance cycles in the future.
關鍵字(中) ★ 鋪面狀況指標
★ 道路巡查
★ 影像形態校正
★ 直線與車道偵測
關鍵字(英) ★ pavement condition index
★ road inspection
★ image morphological adjustment
★ straight line and lane detection
論文目次 目錄I
圖目錄V
表目錄XIII
第一章 緒論1
1.1 研究背景1
1.2 研究目的2
1.3 研究內容與方法3
1.4 研究流程4
第二章 文獻回顧7
2.1 國內各級道路巡查方式7
2.1.1 國道巡查7
2.1.2 省道巡查12
2.1.3 鄉縣道巡查15
2.1.4 市區道路巡查 18
2.2 柔性鋪面評級方式22
2.2.1 人工評級22
2.2.2 自動化影像評級31
2.3 國內外鋪面影像辨識技術35
2.3.1 國內歷年研究蒐集整理36
2.3.2 國外歷年研究蒐集整理42
2.3.3 國內外影像辨識技術與結果分析比較71
第三章 研究方法75
3.1 鋪面影像處理流程75
3.1.1 影像雜訊處理 75
3.1.2 影像形態校正 80
3.1.3 直線與道路偵測84
3.1.4 鋪面破壞特徵值擷取106
3.2 鋪面破壞影像量測112
3.2.1 坑洞量測113
3.2.2 縱橫向裂縫量測114
3.2.3 人手孔量測115
3.3 柔性鋪面破壞程度評級116
3.3.1 裂縫量測與影像品質規範 117
3.3.2 破壞類型與等級判定方式 120
第四章 自動化道路巡查與辨識系統125
4.1 影像自動化擷取與定位設備125
4.1.1 距離感測器125
4.1.2 CCD Camera128
4.1.3 GPS133
4.2 系統軟體設計137
4.2.1 道路基本資料建立138
4.2.2 鋪面影像處理 140
4.2.3 鋪面影像分析結果與資訊匯出145
4.3 自動化道路巡查與辨識系統成效分析147
4.3.1 影像形態校正量測檢核147
4.3.2 鋪面影像量測檢核149
4.3.3 鋪面破壞影像辨識結果150
4.4 自動化道路巡查流程與管理機制153
4.4.1 巡查人員配置與巡查制度 154
4.4.2 辨識系統軟體操作155
4.4.3 鋪面破壞資訊管理與應用 158
第五章 結論與建議161
5.1 結論161
5.2 建議162
參考文獻163
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廖子凱(1994),影像處理應用於鋪面破壞辨識之研究,碩士論文,國立台灣大學
鄭進源(2013),自動化鋪面破壞影像辨識系統導入鋪面破壞維護管理系統之研究,碩士論文,國立中央大學
戴志旭(2006),應用PSO演算法在即時車道追蹤,碩士論文,義守大學
蔡鎮宇(2011),鋪面雷射掃描儀之鋪面績效分析,博士論文,國立台灣大學
鍾國亮,影像處理與電腦視覺導論,臺灣東華, 2012
鍾閎文(2012),高解析二維雷射整合於智慧型檢測車量測平坦度之可行性評估,碩士論文,國立中央大學
蘇宗安(2010),智慧代理人應用於交通十字路口連鎖號誌管理,碩士論文,逢甲大學
指導教授 林志棟、陳建達
(Jyh-dong Lin、Chien-ta Chen)
審核日期 2014-7-21
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