• 沒有找到結果。

五、 結論與未來展望

5.2 未來展望

經過本論文之研究,可以快速、準確的完成三維點資料之整合與對位,對於 條紋投射法取得之三維點資料以可以非常有效率的進行後處理的動作,期望本論 文研究能夠在逆向工程之三維外形量測與醫學工程之胸腔外形取得方面盡一份心 力。然而本研究尚有許多值得發展的方向與需要改進的地方,未來展望如下:

1. 本論文使用 Visual C++ 控制 AutoCAD 2002 之方法,礙於記憶體空間宣 告限制問題,宣告指令 ads_point 僅能宣告小於[200][200]之變數,必須 將變數寫入硬碟中,再將其讀取出來,於整合計算過程中需要的運算時間 仍過於冗長;若能破除記憶體宣告之限制,將其所有三維點資料寫入隨機 存取記憶體中,便可大幅改善對位過程所需之等待時間。

2. 可以嘗試多拍攝一張不投射條紋圖樣之影像,並且由此影像擷取物體表面 之顏色資訊,於後處理部分重建三維外形之色彩貼圖,使得量測系統能有 更廣泛的應用範圍。

3. 目前本論文使用兩台相機進行拍攝,可量測角度大約 180°,進行整合與 對位之角度也大約是 180°;若於取像技術與對位技術兩方面一同進行突 破,則有機會達到 360°量測之要求。

4. 可針對條紋投射法之特色於校正樣本的部分著手進行改良初步對位之流 程。

5. 將取得之三維點資料與剖面圖與實際尺寸之間作一個尺寸比例換算與實 際尺寸標記,以便將手術改良成果量化。

參考文獻

[1] J. Salvi, J. Pages, J. Battle, “Pattern codification strategies in structured light systems," Pattern Recognition, 37(4), pp. 827-849, April 2004.

[2] Y. S. Chen, B. T. Chen, “Measuring of a three-dimensional surface by use of a spatial distance computation," Applied Optics, 42(11), pp. 1958-1972, 2003.

[3] P. S. Huang, F. Jin, and F. P. Chiang, “Quantitative evaluation of corrosion by a digital fringe projection technique," Optics and Lasers in Engineering, 31(5), pp. 371-380, 1999.

[4] C. S. Chua, and R. Jarvis, “Point signatures: a new representation for 3D object recognition," International Journal of Computer Vision, Vol.25, No.1, pp.63-85, 1997.

[5] R. Benjemaa, and F. Schmitt, “Fast global registration of 3D sampled surfaces using a multi-z-buffer technique," International Conference on 3-D Digital Imaging and Modeling, pp.113-120, 1997.

[6] H. Hügli, and C. Schütz, “Geometric matching of 3D Objects: assessing the range of successful initial configurations," International Conference on 3-D Digital Imaging and Modeling, pp.101-106, 1997.

[7] C. Schütz, T. Jost, and H. Hügli, “Multi-feature matching algorithm for free-form 3D surface registration," International Conference on Pattern Recognition, Vol.2, pp.982-984, 1998.

[8] K. S. Arun, T. S. Huang, and S. D. Blostein, “Least-squares fitting of two 3-D point sets," IEEE Transactions on Pattern Analysis and Machine

Intelligence, Vol.9, No.5, pp.587-700, 1987.

[9] H. T. Yau, C. Y. Chen, and R. G. Wilhelm, “Registration and integration of multiple laser scanned data for reverse engineering of complex 3D models," International Journal of Production Research, Vol.38, No.2, pp.269-285, 2000.

[10]P. J. Besl, and N. D. McKay, “A method for registration of 3-D shapes,"

IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.14, No.2, pp.239-256, 1992.

[11]T. Masuda, and N. Yokoya, “A robust method for registration and segmentation of multiple range images," Computer Vision and Image Understanding, Vol.61, No.3, pp.295-307, 1995.

[12]S. Rusinkiewicz, and M. Levoy, “Efficient variants of the ICP algorithm,"

International Conference on 3D Digital Imaging and Modeling, 2001.

[13]L. Zagorchev, and A. Goshtasby, “A mechanism for range image integration without image registration," 3-D Digital Imaging and Modeling (3DIM), pp.126-133, 2005.

[14]S. S. Parasnis, “Four point calibration and a comparison of optical modeling and neural networks for robot guidance," Master of Science thesis, University of Cincinnati, 1999.

[15]P. Hebert, “A self-referenced hand-held range sensor," 3-D Digital Imaging and Modeling (3DIM), pp.5-12, 2001.

[16]W. Niem, and J. Wingbermuhle, “Automatic reconstruction of 3D objects using a mobile monoscopic camera," 3-D Digital Imaging and Modeling (3DIM), pp.173-180, 1997.

[17]R. Sitnik, M. Kujawiska, and Jerzy Wonicki, “Digital fringe projection system for large-volume 360-deg shape measurement," Optical Engineering,

Vol. 41, Issue 2, pp.443-449, 2002.

[18]L. C. Chen, and C. C. Liao, “Calibration of 3D surface profilometry using digital fringe projection," Measurement Science and Technology, Vol.16, No.8, pp.1554-1566, 2005.

[19]陳俊諺, “利用 3D 多重掃瞄資料建構多面體架構之實體模型,"國立中正大學機 械工程研究所碩士論文, 2000.

[20]黃文昭, “三維外形量測之非線性數位條文誤差校正,"國立台灣大學機械工程 學研究所碩士論文, 2006.

[21]T. Masuda, K. Sakaue, and N. Yokoya, “Registration and integration of multiple range images for 3-D model construction," International Conference on Pattern Recognition, Vol.1, No.1, pp.879-885, 1996.

[22]J. Y. Lai, W. D. Ueng, and C. Y. Yao, “Registration and data merging for multiple sets of scan data," The International Journal of Advanced Manufacturing Technology, Vol.15, pp.54-63, 1999.

[23]M. Soucy, and D. Laurendeau, “A general surface approach to the integration of a set of range views," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.17, No.4, pp.344-358, 1995.

[24]G. Turk, and M. Levoy, “Zippered polygon meshes from range images,"

Annual Conference Series on Computer Graphics, pp.311-318, 1994.

[25]張北葉, “嬰兒頭型維護─長庚兒童醫院", 國立交通大學機械工程學系醫學工 程課堂講義, 2005.

[26]賴勁堯, “漏斗胸簡介", 長庚醫院兒童外科病例簡介, 2005.

[27]Jasbir S. Arora, “Introduction to optimum design-Second Edition", Elsevier Academic Press, pp.143-148, 2004.

[28]Niloy J. Mitra, An Nguyen, “Estimating Surface Normals in Noisy Point Cloud Data", SoCG'03, June 8-10, San Diego, California, USA, 2003.

[29]David Eberly, "Least Squares Fitting of Data", Geometric Tools, Inc.

http://www.geometrictools.com, 2001.

[30]Adam Huang, Ronald M. Summers, and Amy K. Hara, "Surface curvature estimation for automatic colonic polyp detection", Proceedings of SPIE Vol.

5746, Bellingham, WA, pp.393-402, 2005.

[31]Tatiana Surazhsky, Evgeny Magid, Octavian Soldea, Gershon Elber, and Ehud Rivlin, "A Comparison of Gaussian and Mean Curvatures Estimation Methods on Triangular Meshes", Center for Graphics and Geometric Computing, Technion, Israel Institute of Technology, Haifa 32000, Israel, 2003.

[32]Craig M. Shakarji, "Least-Squares Fitting Algorithms of the NIST Algorithm Testing System", Journal of Research of the National Institute of Standards and Technology, Volume 103, Number 6, November–December 1998.

[33]D. L. Page, Y. Sun, A. F. Koschan, J. Paik, and M. A. Abidi, “Normal Vector Voting: Crease Detection and Curvature Estimation on Large, Noisy Meshes", Graphical Models, Volume 64, pp.199-229, 2002.

[34]Kunwoo Lee, “Principles of CAD/CAM/CAE Systems," Addison-Wesley, pp.54-65, 1999.

[35]Ibrahim Zeid, “CAD/CAM Theory and Practice", McGraw-Hill, pp.481-525, 1991.

[36]Ibrahim Zeid, “Mastering CAD/CAM", McGraw-Hill, pp.461-500, 2005.

[37]徐偉盛, “三維外形量測之 N 步彩色相位移法,"國立台灣大學機械工程學研究所 碩士論文, 2006.

[38]Seth D. Force, “ACS Surgery: Principles and Practice CH 6 CHEST WALL PROCEDURES", WedMD, Inc, 2005.

附錄 A 程式 Color Fringe Projection System 使用步驟

取相技術使用『彩色數位條紋投射十五步相位移法』,由於彩色數位條紋投射法一 次可投射 RGB(紅、綠、藍)三種顏色之條紋光柵,故只需擷取五張圖像即可滿足十 五步相位移法之處理與運算所需。

執行使用程式 Color Fringe Projection System 開始進行三維取相。圖 A.1 與圖 A.2 分別為左邊視角相機與右邊視角相機對於漏斗胸兒童病患胸腔取相之照片。

圖 A.1 漏斗胸兒童病患(左) 圖 A.2 漏斗胸兒童病患(右)

使用軟體 Color Fringe Projection System 步驟為:

1. 點選按鈕『Capture Model』,並選擇條紋影像檔儲存資料夾位置。如圖 A.3 所示。

2. 按『確定』開始取相。取相時間約 15 秒,其間投射五組不同相位移角度之彩 色條紋光柵,並分別於左、右兩側進行左、右側相機取相。

3. 取相完畢。左、右側視角相機分別取得五張彩色數位條紋投射之不同相位移角 度照片。圖 A.4~圖 A.8 為左側相機所取得之五張圖像檔;圖 A.9~圖 A.13 為右側相機所取得之五張圖像檔。

4. 『Data Set』先選至『R』的位置,點選按鈕『Load Image』,載入右邊相機取 得的五張照片,如圖 A.14 所示。

5. 點選按鈕『Select Region』,選擇要需要轉換相位值計算三維外形點資料之資 料範圍,如圖 A.15 所示。

6. 點選按鈕『Auto Execut』,自動完成下列步驟,並將右側視角相機經過運算取 得之三維點資料儲存於 Test0.tst 資料檔中。完成後畫面如圖 A.16 所示。

7. 更動『Data Set』選項,選至『L』的位置,重複步驟 4~6。將左側相機視角 取得之三維點資料儲存於 Test1.tst 資料檔中。

8. 完成使用軟體 Color Fringe Projection System 取得漏斗胸兒童病患胸腔外 形之三維點資料步驟。

圖 A.3 擇條紋影像檔儲存資料夾位置 圖 A.4 左邊相機所取得之圖檔(一)

圖 A.5 左邊相機所取得之圖檔(二) 圖 A.6 左邊相機所取得之圖檔(三)

圖 A.7 左邊相機所取得之圖檔(四) 圖 A.8 左邊相機所取得之圖檔(五)

圖 A.9 右邊相機所取得之圖檔(一) 圖 A.10 右邊相機所取得之圖檔(二)

圖 A.11 右邊相機所取得之圖檔(三) 圖 A.12 右邊相機所取得之圖檔(四)

圖 A.13 右邊相機所取得之圖檔(五) 圖 A.14 Load Image

圖 A.15 Select Region 圖 A.16 完成畫面

附錄 B 程式 Data registration and

integration for 3D shape measurement system

主程式碼