本文提出了一個光學圖像穩定的方法來解決因手震所產生的影像模糊問題，本系統的目的是要判斷手震訊號以及修正模糊影像。本文主要是以Move Camera Module的觀念為基礎，進而延伸出不同的修正概念。利用本方法不需要耗費半按快門的時間以及又可以精確修正。而且透過Fuzzy理論的運用，進而去判斷使用者的目前狀態，判斷是否為手震訊號，若為手震訊號，即輸出修正訊號修正，以達到即時且精確的目標。我們成功地利用此方法使的圖像品質更加穩定，在實驗成果中顯示，當不使用此系統時，影像模糊平均為73.8個像素，使用了此方法，則影像模糊平均減至為33.4667個像素，平均修正了40.333個像素，手震造成的影響減少了平均54.64%。

This paper proposed an optical image stabilization methodology to solve blurring image problem created by hand-shake. The aim of this system is to determine hand-shake and correct the blurring image. This paper is based on Move Camera Module concept, and moreover, we also extended different correction methodologies. This method of the study makes us save the time of half-press the shutter and increases accuracy and precision. And then through fuzzy theory, we determine user's state and predicts whether hand-shaking signal or not. If there is the hand-shaking signal, as soon as, it outputs correction signals to correct the image in real-time. Successfully, this method can make image quality more blur insensitive. The average shake without using this method is 73.8 pixels, the average shake with this method is 33.4667 pixels, the average shake reduction is 40.333 pixels and the average percentage of shake reduction is 54.64%.

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