本論文的主要目的是建立ㄧ套自動化手部特徵辨識系統，以辨識出的特徵點為基礎，建立簡潔的手部資料結構。首先從全身掃描點搜尋腋下點及肩端點分割出手部點群，並依手部各特徵點的幾何特性定義出其數學模式，利用影像編碼技術將三維點群轉為影像平面，並使用影像處理技巧搜尋手部特徵，加速演算速度。可萃取出手部各關節及其他重要特徵點位置。最後以特徵點為基準，建立手部資料結構，以少數的資料點描述完整的手部外形，並保留手部特徵資訊，可應用於人體計測與服裝設計等方面。此手部資料結構取自真實手部的三維外形，並以解剖學的觀點建構而成。不但可用於量測手部，並適用於建立手部動態模型，重現手部動作。

　　The purpose of the thesis is to establish a automatic hand features extraction method and to reconstruct a digital hand model based on the hand features. The point cloud of hand is obtained from the segmented body scanning data. Then the descriptions of hand geometric features are translated into mathematical definitions. By employing the image encoding method, the point cloud is transformed into range image format. The hand features are extracted from the image using image processing techniques. The result of feature extraction includes joints and other important features of the hand. Finally, the 3D digital hand model is completely reconstructed by very concise point set that contains various information for various applications, such as anthropometry and human factor design.

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