本研究旨在開發出一套供划拳機器人計算玩家手指數目的高可靠度影像辨識系統。該影像辨識系統採用Kinect感測器，並結合指尖偵測程式，用以即時辨識出玩家所出的拳（即計算手指數目）。
影像辨識的策略，首先利用Kinect感測器所擷取的場景深度資訊濾除玩家手部後方的所有影像以節省分析時間。接著搜尋手部輪廓並運用指尖角度計算法依序偵測出輪廓序列中的指尖點，以便合計出手指數目。
為建立高可靠度的辨識系統，將Kinect感測器裝設在9個可能的裝配位置，並分別針對玩家的6個出拳位置和每個位置上的5個不同手掌角度，測試8種台灣划拳慣用手勢。最後，將所得測試結果彙整建立成數據庫後，交叉統計並探討各種情況下的最佳辨識率，進而找到系統在使用兩台Kinect感測器下的最佳辨識組合，其辨識率超過94%。

This research aims to develop a high reliability image-based system for finger gaming robot to count the fingers of the competitor. The image-based system includes the use of Kinect sensors and fingertip detection program so as to identify the exposed finger numbers of the competitor in the game real time.
The image recognition strategy starts with the use of Kinect sensor to screen out the image part behind the hand using depth information to save time. Afterwards, the hand contour will be searched and then detect all fingertips using fingertip-angle computation method so as to make a finger count.
In order to generate a high reliable recognition system, Kinect sensors are installed in 9 different locations. For each location the competitor's hand will present in 6 different positions, and for each hand position the hand will appear in 5 different angles. Finally, for each combination, 8 common finger postures are shown for recognition testing. After the large set of experiment data went through an extensive analysis process, the overall best combination with two Kinect sets is revealed, with a 94%+ correct recognition performance.

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