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研究生:白博升
研究生(外文):Bo-Sheng Bai
論文名稱:結合擴增虛擬實境與即時影像辨識之工程應用---以鋼橋鏽蝕辨識為例
論文名稱(外文):Combining AR/VR and Real-Time Image Recognition for Engineering Applications – Taking Steel Bridge Rust Recognition for Example
指導教授:陳柏翰陳柏翰引用關係
指導教授(外文):Po-Han Chen
口試日期:2017-07-01
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:土木工程學研究所
學門:工程學門
學類:土木工程學類
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:72
中文關鍵詞:擴增實境(Augmented RealityAR)虛擬實境(Virtual RealityVR)即時影像辨識(Real-Time Image Recognition)頭戴式顯示器(Head-Mounted DisplayHMD)
外文關鍵詞:Augmented Reality (AR)Virtual Reality (VR)Real-Time Image RecognitionHead-Mounted Display (HMD)
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近年來,擴增實境(Augmented Reality, AR)與虛擬實境(Virtual Reality, VR)的技術逐漸成熟,市面上越來越多商業化的相關設備,例如:Microsoft HoloLens (AR)與HTC Vive (VR)。此類頭戴式顯示器(Head-Mounted Display, HMD) 能提供使用者良好的沉浸式體驗,使數位資訊有機會以更符合資料視覺化效益的方式呈現。

由於台灣的氣候普遍濕熱,鋼結構鏽蝕成為一種常見的現象。因此本研究決定以「輔助鋼橋樑鏽蝕檢測」為目標,結合即時影像辨識(Real-Time Image Recognition)與AR/VR開發一套示範系統,包含創新的鏽蝕辨識演算法及容易擴充的虛擬框架,作為探討以上技術導入土木領域的案例。
Augmented Reality (AR) & Virtual Reality (VR) is becoming further mature in recent years; there is a lot of commercialized equipment in the market, such as Microsoft HoloLens (AR), HTC Vive (VR) and so on. This kind of Head-Mounted Display (HMD) could provide user a very good immersive experience, and make it more possible to display the digital information in a better data visualizing way.

Because the weather in Taiwan is usually hot and wet, steel getting rust is a common phenomenon. Thus, this research decided to choose “Helping Rust Inspection of Steel Bridge” as target; combined Real-Time Image Recognition with AR/VR to develop a demo system, which contains a new algorithm for rust recognition & an easy-edit virtual frame; as an example to discuss the influence when those technologies mentioned above are brought into Civil Engineering.
口試委員會審定書 #
誌謝 i
中文摘要 ii
ABSTRACT iii
目錄 iv
圖目錄 vii
表目錄 ix

第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 2
1.3 研究目的 3
1.4 研究範圍&限制 3
1.5 研究方法&流程 4
1.6 論文架構 5

第二章 文獻回顧 6
2.1 影像辨識演算法 6
2.2 鋼橋樑鏽蝕檢測 12
2.3 工具類軟體資源 12

第三章 系統開發 13
3.1 環境工具 13
3.1.1 硬體清單 14
3.1.2 軟體清單 14
3.2 系統架構 15
3.3 影像辨識演算法 16
3.3.1 辨識流程 16
3.3.2 函數介紹 17
3.4 擴增虛擬框架 19
3.4.1 物件架構 19
3.4.2 控制器 (手把) 23
3.4.3 屏幕 (HMD) 24
3.5 函數參數測試 26
3.6 系統展示 30

第四章 成果分析 33
4.1 鏽蝕樣圖介紹 33
4.2 辨識效果討論 35
4.2.1 圖片 (靜態) 40
4.2.2 串流 (動態) 47

第五章 結論與建議 51
5.1 結論 & 研究貢獻 51
5.2 建議 & 後續方向 52

參考文獻 57
附件一《My Method (Picture)_with Runtime.cpp》 61
附件二《ChangeVarsOfImageRecognition.cs》 65
附件三《WebCamAsTextureWithRecognitionOutput.cs》67
附件四《InsideOut.shader》 71
附件五《InsideOutTransparent.shader》 72
《網站Website》
[1]Wikipedia. On-Line: https://www.wikipedia.org/
, Accessed: May 26, 2017.

《手冊Guide》
[2]中華民國交通部,「公路鋼結構橋梁之檢測及補強規範」,初版,交通部,2008。

《論文Thesis》 (依年份排列)
[3]黃世昌,「智慧型影像處理於橋樑維護與檢驗技術之研究」,行政院國家科學委員會專題研究計畫成果報告,2000。
[4]戴佳信,「小波理論於智慧型影像處理在鋼構橋梁表面銹蝕面積檢測之應用」,國立交通大學土木工程系所碩士論文,2004。
[5]楊雅晴,「運用智慧型彩色影像辨識於鋼橋生鏽檢測」,國立臺灣大學工學院土木工程學研究所碩士論文,2008。
[6]Heng-Kuang Shen, "Automatic Color Image Recognition for Steel Bridge Rust Defects Assessment", Department of Civil Engineering College of Engineering National Taiwan University Doctoral Dissertation, 2013.
[7]尹昱翰,「鋼構件鏽蝕影片運用雲端辨識系統之初步開發」,國立臺灣大學工學院土木工程學研究所碩士論文,2014。
[8]李奕霆,「鋼橋鏽蝕區域之數位影像辨識」,國立臺灣科技大學營建工程系研究所碩士論文,2014。
[9]劉韋村,「以手持裝置進行鋼材鏽蝕即時影像辨識之系統開發」,國立臺灣大學工學院土木工程學研究所碩士論文,2016。

《期刊Paper》 (依主題排列)
[10]Heng-Kuang Shen, Po-Han Chen, and Luh-Maan Chang, "Automated Steel Bridge Coating Rust Defect Recognition Method Based on Color and Texture Feature", Automation in Construction, Vol.4, pp.338-356, 2013.
[11]Heng-Kuang Shen, Po-Han Chen, and Luh-Maan Chang, "Support-Vector-Machine-Based Method for Automated Steel Bridge Rust Assessment", Automation in Construction, Vol.23, pp.9-19, 2012.
[12]Po-Han Chen, and Luh-Maan Chang, "Intelligent Steel Bridge Coating Assessment Using Neuro-Fuzzy Recognition Approach", Computer-Aided Civil and Infrastructure Engineering, Vol.17, pp.307-319, 2002.
[13]Po-Han Chen, Yuh-Chin Chang, and Luh-Maan Chang, "Application of Multiresolution Pattern Classification to Steel Bridge Coating Assessment", Journal of Computing in Civil Engineering, Vol.16(4), pp.244-251, 2002.
[14]Po-Han Chen, Ya-Ching Yang, Chi-Yang Lei, and Luh-Maan Chang, "Automated Bridge Coating Defect Recognition Using Adaptive Ellipse Approach", Automation in Construction, Vol.18, pp.632-643, 2009.
[15]Sangwook Lee, Luh-Maan Chang, and Miroslaw Skibniewski, "Automated Recognition of Surface Defects Using Digital Color Image Processing", Automation in Construction, Vol.15, pp.540-549, 2006.
[16]Sangwook Lee, "Digital Image Processing Methods for Bridge Coating Management and Their Limitations", Journal of Civil Engineering and Architecture, Vol.1 (38), pp.39-47, 2011.
[17]Qing-Yuan He, and Chuan-Jiu Han, "Image Thresholding Segmentation with Otsu Based on Particle Swarm Optimization Algorithm", Journal of Guilin University of Electronic Technology, May 2006.
[18]賴玉霞, 劉建平,「K-means算法的初始聚類中心的優化」,Computer Engineering and Application,Vol.44 (10),pp.147-149,2008。
[19]R. Medina-Carnicer, A. Carmona-Poyato, Rafael Muñoz-Salinas, and Francisco José Madrid-Cuevas, "Determining Hysteresis Thresholds for Edge Detection by Combining the Advantages and Disadvantages of Thresholding Methods", IEEE Transactions on Image Processing, Vol.19 (1), pp.165-173, 2010.
[20]Raman Maini, and Himanshu Aggarwal, "Study and Comparison of Various Image Edge Detection Techniques", International Journal of Image Processing, Vol.3, pp.1-11, 2009.
[21]G.T. Shrivakshan, and C. Chandrasekar, "A Comparison of Various Edge Detection Techniques Used in Image Processing", International Journal of Computer Science Issues, Vol.9 (5), pp.272-276, 2012.
[22]Li Bin, and Mehdi Samiei Yeganeh, "Comparison for Image Edge Detection Algorithms", IOSR Journal of Computer Engineering, Vol.2, pp.1-4, 2012.
[23]Susanta Mukhopadhyay, "Multiscale Morphological Segmentation of Gray-Scale Images", IEEE Transactions on Image Processing, Vol.12 (5), pp.533-549, 2003.
[24]Hugo Hedberg, Fredrik Kristensen, Peter Nilsson, and Viktor Owall, "A Low Complexity Architecture for Binary Image Erosion and Dilation Using Structuring Element Decomposition, Circuits and System", International Symposium on Circuits and Systems, Vol.4, pp.3431 – 3434, 2002.
[25]F. Ortiz, "Real-Time Elimination of Brightness in Color Images by MS Diagram and Mathematical Morphology", Computer Analysis of Images and Patterns, pp.458-465, 2007.
[26]F. Ortiz, and F. Torres, "Vectorial Morphological Reconstruction for Brightness Elimination in Colour Images", Real-Time Imaging, Vol.10 (6), pp.379-387, 2004.
[27]F. Ortiz, and F. Torres, "A New Inpainting Method for Highlights Elimination by Colour Morphology", Pattern Recognition and Image Analysis, pp.368-376, 2005.
[28]J. Kasperek, "Real-Time Morphological Image Contrast Enhancement in Virtex FPGA", Field-Programmable Logic and Applications, pp.430-440, 2001.
[29]Robert M. Haralick, "Image Analysis Using Mathematical Morphology", IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol.PAMI-9(4), pp.532-550, 1987.
[30]L. Vincent, "Morphological Gray-Scale Reconstruction in Image Analysis: Applications and Efficient Algorithms", IEEE Transactions on Image Processing, Vol.2 (2), pp.176-201, 1993.

《書籍&網站Book & Website》
[31]張右緯,「Unity實戰教學」,佳魁資訊,June 2016.
[32]Unity. On-Line: https://unity3d.com/
, Accessed: May 26, 2017.
[33]OneV’s Den. On-Line: https://onevcat.com/2013/07/shader-tutorial-1/
, Accessed: May 26, 2017.
[34]OpenCV. On-Line: http://opencv.org/
, Accessed: May 26, 2017.
[35]OpenCV for Unity. On-Line: https://enoxsoftware.com/opencvforunity/
, Accessed: May 26, 2017.
[36]SteamVR. On-Line: https://support.steampowered.com/kb_cat.php?id=111
, Accessed: May 26, 2017.
[37]Julie Steele, and Noah Iliinsky, "Beautiful Visualization: Looking at Data through the Eyes of Experts", Publisher: O''Reilly Media, 1st Edition, April 23, 2010.
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