臺灣博碩士論文加值系統

在本研究中，利用離散餘弦轉換 (Discrete Cosine Transform)
對影像做運算，然後取運算後特定單一頻率的振幅作為對焦值(focus value)。對焦值可用來判斷影像的品質，並結合非線性迴歸法(nonlinear regression)推算出對焦最好的位置。實驗中利用四種不同測試圖來測試比較各個演算法的效果，和結合非線性迴歸法推算的結果。實驗發現利用FM33結合非線性迴歸法應用在自動對焦上有最好的效果。這些成果可應用於相機、電腦視覺、顯微鏡、光學檢測的自動對焦程序。

This research presents a fast and accurate real-time optical auto-focusing system, which utilizes a frequency component of the discrete cosine transform (DCT) as the focus measure. Besides, a nonlinear regression routine is combined in the algorithm to quickly move a rotational stepper motor to the best focus. The concise and effective algorithm can be applied to digital cameras, microscopes and optical inspection instruments.

目 錄
中文摘要 i
英文摘要 ii
致謝 iii
目錄 iv
圖目錄 vii
表目錄 x

第一章 緒論 1
1.1 研究背景與文獻回顧 1
1.2 研究目的 3
1.3 論文結構 3
第二章 演算法及原理 4
2.1 對焦原理 4
2.2 Focus Measure演算法 6
2.3 非線性迴歸法原理 11
2.4 高斯擬合曲線 12
第三章 實驗儀器架構與程式 16
3.1 LabVIEW 16
3.1.1 LabVIEW簡介 16
3.1.2 LabVIEW工作環境 16
3.1.3 LabVIEW特色 18
3.2 步進馬達控制/驅動器 19
3.3 精密旋轉台 20
3.4 鏡頭與CCD攝影機 21
3.5 影像擷取卡 21
3.6 自動對焦實驗架構 21
3.7 測試圖像 23
第四章 實驗結果 25
4.1 旋轉角度與鏡片移動距離的換算 25
4.2 FM33演算法與各演算法的比較 25
4.2.1 DCT各頻率比較 26
4.2.2 FM33與空間域演算法比較 28
4.3 演算法運算速度比較 31
4.4 非線性迴歸法搭配各演算法之結果 32
4.5 非線性迴歸法準確率 37
4.6 非線性迴歸法迴圈數比較 37
4.7 不同起始值與對焦重複率 38
4.8 截止值設定 39
第五章 結論與未來展望 40
5.1 結論 40
5.2 未來展望 40
參考文獻 42

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