由於台灣屬於多山地形，許多公路、鐵路仰賴隧道做為穿越障礙物之手段，且土地面積狹小，都市地區在有限的土地面積下，常以地下隧道的方式建立捷運、管線、給排水系統，因此隧道在台灣是非常重要的基本建設。若隧道發生結構損毀，將會影響交通、民生甚至用路人安全等問題，所以需要不斷的對隧道進行定期檢查與紀錄，針對觀察到的異狀及可能產生之問題進行檢測與修補。而在隧道的維護與管理工作中，目視檢測為最直接有效的檢測法，但目視檢測時所需之位置資訊，卻沒有與其相配之快速低成本的方法。
本研究建立一套透過電腦視覺於隧道內取得位置資訊之流程與相關之演算法，以C++作為程式語言撰寫，在電腦視覺部分使用OpenCV函式庫，透過雙攝影機模擬人類視覺，利用左右眼視野內景物之視差計算特定點之距離，並根據視野中物體之移動來計算自身之相對位移，取得自身座標集姿態後可計算視野中其他點座標供下一次計算使用。如此重複以上流程，即可計算系統相對於開始點之所在位置，達成在隧道內定位之目的。
除此之外本研究根據電腦視覺定位之流程，建立一個便於測試、驗證演算法之研究平台，並利用此研究平台開發、驗證電腦視覺於隧道內定位之系統。透過VTK視覺化工具產生3D隧道，並模擬一對立體攝影機於隧道內行走，如此一來我們得到一個可控制之隧道與攝影機環境，我們可以依研究需求產生不同隧道，或是自行調整攝影機參數來測試演算法。
使用本研究平台測試本研究之隧道內定位之演算法，在直線隧道的狀況下結果尚可接受，但套用實際隧道之曲線線型後誤差仍過大，若要投入實務中使用仍有改進的空間。

Taiwan is a mountainous island. It is thus necessary to use tunnels to meet transportation demands. Tunnels are also constructed in metropolitan areas for rapid transit system and pipelines. It is fair to say tunnels are fundamental and important infrastructure in Taiwan. Tunnels may endanger its users or cause inconvenience to people’s daily life. Therefore, it is crucial to conduct regular inspection and record issues for tunnels. These recorded issues may need further investigation or conduct repair work. Currently, the only viable regular inspection method is visual inspection. Unfortunately, there is no convenient and low cost solution to automatically obtain locations of found issues in tunnels.
This study developed a general procedure and implemented associated algorithms in C++ to obtain location information via computer vision. For the computer vision part, open source OpenCV library is used. By capturing images from dual cameras, disparity between this pair of image can be used to derive depth information for every interested point. By tracking how images change between frames, displacements of cameras can be found. Using this concept, the location can be inferred in tunnels.
In addition, this study established a research platform to conduct researches on localization in tunnels. This platform enables easy testing and validating algorithms for localization in tunnels. It can also be used to analyze related issues and accuracy of a particular localization algorithm. The platform uses VTK visualization toolkit to construct virtual tunnels in three-dimension. Then, a pair of camera is put into the virtual tunnel to obtain virtual stereo images. Thus, the platform creates a controlled virtual environment to study localization algorithms.
The localization algorithm implemented in this study achieves good accuracy for straight tunnels. However, the accuracy for curved tunnels is too big to be used in practice. Further studies are necessary to improve the localization algorithm.

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