臺灣博碩士論文加值系統

本研究利用結構光投影法 (Structured Light Projection)，執行待測物體的三維量測。傳統結構光法以正弦條紋結構光投影在待測物上，再以 CCD 相機取像，並搭配相位移 (phase shift) 技術量測物體表面的三維結構。在本研究中，為了達到快速量測的目的，我們使用取像張數最少的三步相位移技術，並且加入 CUDA (Compute Unified Device Architecture) 平行處理演算法，提高量測的速度。另外，為了將來能將本技術應用在連續移動的生產線上，我們推導任意固定相位差的三步相位移演算法；經由投影一張固定的正弦條紋結構光，利用生產線本身的移動速度換算成相對相移量，以量測物體的高度。
由於三步相位移方法的取像較少，對於相位的誤差就變得較為敏感；對此我們先針對數位條紋投影法中，連續函數轉離散灰階造成的誤差、投影機非線性輸出造成的誤差、相機量化灰階造成的誤差和灰階跳動造成的誤差進行分析，並利用電腦模擬產生各項誤差數據，將數據製表後提供給後續實驗做相位補償。因為本研究是使用數位投影機來投射條紋，因此我們把 CCD 相機與投影機的非線性投射取像建立關係，由上述關係對拍攝的影像作校正，以校正非線性投射取像造成的相位誤差。另外，為了將來能應用在移動生產線上，我們必須去除待測物在影像中因為不同位置而造成不同扭曲程度所導致的相位錯誤。對此我們先以棋盤格校正板做相機校正 (camera calibration)；利用所求得的相機內外部及扭曲參數還原影像成未扭曲影像，藉以提高量測的精度。
總結，我們先把三張影像還原成未扭曲影像，對相位進行補償，經由三步相位移公式計算出相位差，再經由相位展開，最後以相位與高度的關係，將展開後的相位換算成物體的高度。在實驗中，針對我們所推導的任意固定相位差的三步相位移演算法進行驗證，對同一待測物進行量測，在投影時，投影的條紋換成與原三步相位移理論相移量不同的三張正弦波，做完相位展開和相位補償後計算出高度，再和原三步相位移做高度數據的比較，並討論可能造成量測結果不同的原因。
經由實際量測，目前精準度可達 mm，但仍有相當大的誤差仍需克服。將可變動相位的三步相位移演算法導入 CUDA 平行計算，平均處理時間約為 4.9ms，將其相較於 CPU 計算，可以獲得 38.7 倍效能的提升，若加入記憶體搬移的時間，整體效能提升了約 3.3 倍。

In this study, we use structured light to measure three-dimensional information of objects. Traditional structured light project sinusoidal fringe structured light onto the objects, capturing images with CCD cameras, and measure their three-dimensional structure with a phase shift technology. In order to achieve the purpose of fast measurement, we use the three-phase shift technology and CUDA (Compute Unified Device Architecture) parallel processing algorithms to improve measurement speed. Further, for future application of continuous motion production line, we derive an arbitrary fixed phase difference of the three-step phase shift algorithm. Via projecting a fixed sinusoidal fringes structured light, we convert the moving speed of the production line itself to the relative phase shift amount so as to measure the height of the object.
Since three-step phase shift method takes less images, the phase error becomes more sensitive. Thus, we use computer simulation to generate the error data, then tabulate them for the follow-up experiments. Because this study uses a digital projector to project stripe, so we build relationships between the CCD camera capture and the non-linear projection of the projector. Through the relationship we calibrate the captured images to correct the phase error caused by nonlinear projection. For future application of motion production line, moreover, we have to remove the phase errors of objects caused by different degrees of distortion from different positions on the images. We first calibrate the camera with a checkerboard plate, and use intrinsic and extrinsic parameters as well as distortion coefficient to restore the distorted image to undistorted one. By this way we increase the accuracy of measurement.
After actual measurement, our accuracy can achieve millimeter, but we still have to conquer the large amount of error. We apply CUDA parallel computing algorithms to the three-phase shift technology and the average processing time is about 4.9ms. Compared with calculation in CPU, the performance is 38.7 times faster. If we consider the memory access time from memory to GPU, the overall performance increased roughly 3.3 times.

摘要 i
誌謝 v
目錄 vi
圖目錄 ix
表目錄 xiii
第一章 緒論 1
1.1 研究背景與動機 1
1.2 系統流程 3
1.3 論文架構 4
第二章 相關研究探討 6
2.1 使用正弦條紋搭配相位移解相位之研究 6
2.2 使用正弦條紋搭配其他解相位法之研究 9
2.3 使用其他類型條紋與其他解相位法之研究 11
2.4 相位誤差之探討與校正之研究 14
2.5 三步相位移之研究 17
第三章 結構光投影法原理 20
3.1 數位條紋投影法原理 20
3.2 相位移演算法 22
3.3 相位展開技術 23
3.4 相位與高度之轉換 25
3.5 任意固定相位差的三步相位移演算法 26
第四章 GPU 平行處理演算法的技術發展並搭配三步相位移演算法 28
4.1 GPU平行處理演算法技術發展歷史 28
4.2 部份影像平行處理演算法 30
第五章 從誤差來源探討結構光特性與非線性投射校正 32
5.1 數位條紋投影法誤差來源 32
5.1.1 函數連續轉離散灰階造成的誤差 33
5.1.2 投影機非線性輸出造成的誤差 34
5.1.3 量化灰階造成的誤差 35
5.1.4 相機鏡頭的扭曲問題 35
5.1.5 其他誤差來源產生的灰階跳動現象 37
5.2 利用電腦模擬誤差來源 38
5.2.1 模擬函數波形連續轉離散灰階造成的誤差 38
5.2.2 模擬投影機非線性輸出造成的誤差 38
5.2.3 模擬量化灰階產生的誤差 40
5.2.4 模擬灰階跳動產生的誤差 41
5.3 條紋投射與取像系統的非線性校正 42
5.3.1 相位補償 42
5.3.2 亮度補償 44
5.3.3 投射校正 45
5.4 條紋光迭代校正法 46
5.5 校正結果之比較 50
第六章 硬體架構與實物量測 51
6.1 硬體架構 51
6.2 影像前處理及校正建立 53
6.3 量測流程 54
6.4 量測結果 56
6.4.1 相位移理論的實驗結果 56
6.4.2 平行處理的實驗結果 71
6.5 實驗討論 71
第七章 結論及建議 73
7.1 結論 73
7.2 未來工作 74
參考文獻 75

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