本文的主旨在於整合本實驗室所研發之雷射掃描模組，從實驗室內的運作模式，精進為實用之儀器系統。該系統為本實驗室(水下機電實驗室)
經過多屆碩士班學生所研發出來的，但是在使用時，
影像資料擷取、攝影機校正、資料後處理及分析軟體，均建構在不同的軟體上，導致每次實驗需花費許多程序與時間才能獲得最後結果。
雷射掃描系統分為硬體與軟體兩大部分。
硬體部分，修改原本設計讓掃描模組可以簡易搭配在一個水下線性平台上。
軟體則統一其作業介面，方便後續資料分析。
雷射掃描模組採用結構光法，透過CCD(Couple Charged Device)擷取雷射光照射物體所產生的形變量，由於鏡頭會讓影像扭曲變形，
因此必須透過一校正系統來獲得雷射線真正的形變量。為了達到次圖素解析，
提出三種雷射線亮度中心偵測方式，即亮度重心法、多項式近似法、高斯曲線擬合法。
為了取得均勻的格點資料我們把所擷取到的雷射亮點，以最鄰近權重插值法去內插出結果，同時繪出3D模型與頻譜圖。
最後以四次實驗來證實系統的穩定性與可擴性。第一次為空氣中掃描，掛載平台為海下所研發的採泥器，將人為操作
的部份降為最低；第二次為實驗室水槽中，證實系統於水中的穩定性；第三次將儀器掛載於美國華盛頓大學應用物理實
驗室設計的四公尺長的水下滑軌（In situ Measurement of Porosity, 2nd generation , 簡稱IMP2）進行人造沙坡掃描；
最後一次時間於美國西雅圖外海佈放。
使用四顆鋰電池可讓系統持續擷取影像一個小時。

This work reports the system integration of the underwater seafloor laser scanner, designed and fabricated by Institute of Undersea Technology, National Sun Yat-sen University, with the in situ porosity measurement system, known as IMP2, developed by Applied Physics Lab, University of Washington. Our original prototype underwater seafloor laser scanner worked more like an indoor experimental setup rather than an instrument. It is the goal of this work to modify the detail design of hardware and software of the system such that the operation of the scanner and the data analysis of the results can be done like a commercial instrument. Our laser scanning module adopts structural light method with a single camera approach. The calibration of the camera is achieved with a template board on which sets of grid points are laid with numerical control milling machine. These grid points are used to create longitudinal and latitudinal lines for pixel-to-coordinate conversion. Three sub-pixel sampling methods, namely, intensity weighted centroid, second order polynomial intensity fitting and Gaussian intensity fitting, are developed to locate the center of the laser light strip on pixel plane and to be converted into engineering coordinates. For the convenience of post-processing, grid point meshing and spectrum analysis packages are built-in to provide standard output for further studies.
The overall performance of the system was validated by four tests in indoor tanks and field as well. One scanning in air was undertaken to verify if synchronization signal between the laser scanner and the motion of the linear track was correct; several models of known dimension were placed in the water tank for scanning to see if the system reaches the desired accuracy; an integration of the laser scanner and the IMP2 was tested prior to the deployment in the sea, and a scanning a artificial seafloor model of known spatial spectra indicated the proper functioning of the combined system; finally a successful 20-meter deep field deployment and retrieve assured the bases for the acquisition of seafloor roughness field for acoustics related research.

第一章 緒論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1
1.1 研究動機與目的. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 文獻回顧. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 論文架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
第二章 結構光量測法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1 結構光法簡介. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2 攝影機校正. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.3 轉換範例. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
第三章 系統整合. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10
3.1 硬體元件. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10
3.2 系統架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12
3.3 支援軟體. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14
3.3.1 校正板格點搜尋自動化. . . . . . . . . . . . . . . . . . . . . . 14
3.3.2 影像資料儲存格式. . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.3.3 影像處理. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3.3.4 影像重組. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.3.5 頻譜分析. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
第四章 實驗規劃. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.1 Laser scanning 與採泥器結合. . . . . . . . . . . . . . . . . . . 27
4.2 水槽實驗. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.3 Laser scanning與IMP2結合. . . . . . . . . . . . . . . . . . . . . 31
4.4 Seattle外海實地掃描. . . . . . . . . . . . . . . . . . . . . . . . . . .31
第五章 討論與結論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33
5.1 討論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.2 結論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
附錄A 雷射掃描資料處理軟體使用說明. . . . . . . . . . . . . 40

[1] S.T. Barnard and M.A. Fischler. Computational stereo. Computing Surveys,
14(4):553–572, 1982.
[2] E. Trucco and R. B. Fisher. Acquisition of consistent range data using local calibration.
In Proc. IEEE International Conference on Robotics and Automation, pages
3410–3415, 1994.
[3] R.Y. Tsai. A Versatile Camera Calibration Technique for High-Accuracy 3d Machine
Vision Metrology Using Off-the-Shelf TV Cameras and Lenses. IEEE Journal of
Robotics and Automation, 3(4):323–344, 1987.
[4] M. Levoy, K. Pulli, B. Curless, S. Rusinkiewicz, D. Koller, L. Pereira, M. Ginzton,
S. Anderson, J. Davis, J. Ginsberg, J. Shade, and D. Fulk. The digital michelangelo
project: 3D scanning of large statues. In Kurt Akeley, editor, Siggraph 2000,
Computer Graphics Proceedings, pages 131–144. ACM Press / ACM SIGGRAPH /
Addison Wesley Longman, 2000.
[5] R. Li, H. Li, W. Zou, R.G. Smith, and T.A. Curran. Quantitative Photogrammetric
Analysis of Digital Underwater Video Imagery. IEEE Journal of Oceanic Engineering,
22(2):364–375, 1997.
[6] L. Rocher and A. Keissling. Methods for Analyzing Three-Dimensional Scenes. In
Proc. 4th Intl. Joint Conf. Artificial Intelligence, pages 669–673, 1975.
[7] W. Myers. Industry Begins to Use Visual Pattern Recognition. Computer, 13(5):21–
31, 1980.
[8] R.C. Gonzalez K.S. Fu and C.S.G. Lee. Robotics: Control, Sensing, Vision and
Intelligence. McGRAW Hill, New York, 1987.
[9] C.H. Chen and A.C. Kak. Modeling and calibration of a structured light scanner for
3-D robot vision. In Proceedings of 1987 International Conference on Robotics and
Automation, volume 4, pages 807–815, 1989.
[10] J. Davis and X. Chen. A Laser Range Scanner Designed for Minimum Calibration
Complexity. IEEE Proceedings of the Third International Conference on 3D Digital
Imaging and Modeling, 3DIM 2001., 2001.
[11] A.D. Belegundu and T.R. Chandrupatla. Optimization Concepts and Applications
in Engineering. Prentice Hall, 1999.
[12] C.S. Yang, S.P. Kao, F.B. Lee, and P.S Hung. Twelve Different Interpolation Methods:
A Case Study of SURFER 8.0. Proceedings of the XXth ISPRS Congress, pages
778–785, 2004.