本論文提出在室內環境中保全防災機器人之即時人臉偵測與追蹤及自我定位與自動充電系統之設計，同時可透過網際網路監控機器人畫面以了解現場情況。整個影像系統不僅可以在巡邏過程自動偵測環境中之可疑人物而且可透過辨識環境特徵來獲得機器人本身之位置，以供保全防災機器人團隊做任務之安排。本論文結合了數種影像處理技術，包括膚色分析、侵蝕及擴張、邊緣偵測等方法，因人臉經影像處理後為近似橢圓形，所以再用隨機式的橢圓測法求得橢圓之中心與長短軸，利用該資訊來追蹤人臉之位置。在環境定位系統中，結合RFID資訊與視覺辨識環境中的條碼特徵，我們可以完成自我定位與巡邏工作。另外，使用者能透過回傳畫面了解現場情況。最後，我們將藉由實驗之結果，來驗證所提方法之效能及適用性。

This thesis proposes a real-time image processing approach for face detection and tracking, self-localization, and design of auto-recharge system of a surveillance and security robot in an indoor environment. Moreover, the remote scene could be monitored by webcam equipped on the robot. The robots not only detect stranger automatically of the environment in the patrol routine but also get the self-localization by recognizing environmental features to arrange assignments. This thesis combines with several image processing techniques including the complexion analysis, erosion and dilation, and edge-detection. Because face is similar to an ellipsoid after image processing, we use the randomized algorithms for ellipses detection to obtain the center, major and short axis of ellipse, then using the data to detect face region and track it. By combining RFID data with the vision system to recognize the bar-code characteristics in the environment, we can complete the self-localization and the patrol routine. Users recognize the sensed condition by the data transmitted from accompanied robots. Finally, the practical experiments demonstrate the feasibility and effectiveness of the proposed schemes.

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