利用多軸無人機影像萃取橋梁劣化區三維空間資訊

橋梁為民生重要的交通基礎建設，橋梁表面的裂縫與剝落是橋梁安全的重要指標。傳統橋樑檢測方法主要是目視檢測，某些過程會相當危險、耗時且判斷較主觀。本研究中，利用物件導向影像分析對無人機影像進行自動化裂縫檢測，大部分的案例生產者精度（Producer Accuracy）與使用者精度（User Accuracy）分別達到90%及80%以上。偵測出裂縫位於相片上的位置後，將原始相片轉成核影像，再透過影像匹配得到裂縫的共軛點，即可透過前方交會得到裂縫的三維空間資訊。剝落區部份，可以人工於影像上圈選剝落區粗略位置，再利用立體對影像密集匹配產生三維點雲，並將其與擬合的平面相減得到所有點雲與平面之高度差，轉換及製作成數值表面模型（Digital Surface Model），藉由高度差偵測剝落區位置，再計算出剝落區的體積。未來研究可繼續透過前後兩期橋梁裂縫三維空間資訊，進行變異偵測與分析，以達橋梁檢測的目的。

關鍵字

裂縫偵測；物件導向分析(OBIA) ；無人機影像

並列摘要

Bridge is an important infrastructure construction for human living. Its surface's crack and concrete delamination are important indicators that can reflect its safety status. In conventional, the bridge inspection was mainly conduct visually. Some of the process are dangerous and time-consuming to the inspector. Meanwhile, the judgement is subjective. In this research, we utilize object-based image analysis for automatic crack detection from UAV acquired images. Most case studies present more than 90% producer accuracy and more than 80% user accuracy. Later, based on the detected crack position on the image, we convert the original image into epipor one. Then, utilize image matching to detect conjugate point and perform space forward intersection to obtain the three-dimensional information of crack. For the concrete delamination, the approximate location of concrete delamination is manual selected. Then, we conduct dense image matching to obtain 3D point cloud and convert to a digital surface model (DSM) by subtract a fitted plane. By means of the elevation difference, we can detect the delamination area and calculate its volume. In the future works, the change detection and analysis of crack's three-dimensional information between two different times can assist the safety inspection of bridges.

並列關鍵字

Crack detection ； OBIA ； UAV Imagery

國際替代計量

利用多軸無人機影像萃取橋梁劣化區三維空間資訊

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