水下相關研究對地球的認識和探索至關重要，使水下載具需求增加，也讓水下探測技術更加成熟，而以無人水下載具建構水下環境也逐漸展現其重要性，使用其影像技術和相關設備來獲取水下物體、結構和環境的資訊，本研究希望透過結構光與聲納解析獲取水下目標物輪廓並進行相對位置計算，以此來得到目標物座標訊息。本研究以攝影機(Webcam)與前向掃描聲納(Forward Scan Sonar)作為主要研究設備並使用LabVIEW軟體來進行水下目標物的掃描與建構，在掃描過程可能因載具位移造成掃描誤差，我們利用都卜勒測速儀(Doppler Velocity Log , DVL)，將結構光或聲納掃描出的輪廓進行座標補償。本研究在結構光或聲納的影像處理中以濾波的方式消除其雜點，再透過形態學的影像處理，使圖像更清晰、更易於觀察和分析，最後結合ROV載具中的感測器進行水下目標物的建構並儲存其資料，實驗完成掃描出小型船體、圓桶與箱子大致輪廓形狀，並取得外形座標，驗證其可行性與精確度。

Underwater research plays a crucial role in understanding and exploring our planet. The demand for underwater vehicles has increased, leading to the maturation of underwater exploration technologies. Unmanned underwater vehicles have gradually demonstrated their importance in constructing underwater environments, using imaging techniques and related equipment to gather information about underwater objects, structures, and environments. This study aims to obtain the coordinates of underwater targets by analyzing the contours of underwater objects using structured light and sonar resolution, along with relative position calculations. The research utilizes a Webcam and Forward Scan Sonar on a Remotely Operated Underwater Vehicle (ROV) as the primary research equipment and employs LabVIEW software for underwater target scanning and reconstruction. Using the Doppler Velocity Log (DVL) to measure the ROV’s position and feedback position data to compensate for scanning errors. This study employs filtering techniques to remove noise in structured light or sonar images to improve image quality and facilitate observation and analysis. Morphological image processing is then applied to enhance image clarity. Finally, the research integrates ROV sensors to construct underwater target objects and store their data. The experimental results demonstrate successful scanning and rough contour reconstruction of small boat hulls, cylindrical buckets, and boxes, obtaining their respective coordinates and verifying the feasibility and accuracy of the approach.

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