臺灣博碩士論文加值系統

本論文延續先前之研究，利用全像光學元件(Holographic optical element, HOE建議所有英文除非是專有名詞，不然第一個字母全部以小寫來表示，全文檢查)取代Kinect 感應器中紅外線發射系統的二維繞射光學元件(Diffractive optical elements,DOE)，將原本投射出來有明顯畸變且強度不均的光場進行修正。此外，本研究採用創新的深度量測方法，以空間頻率 (Spatial frequency)對物體進行深度量測，並探討其架設方式與量測精度。
首先，根據 Kinect 感應器的紅外線模組進行分析，了解元件組成與運作機制。
由於透過二維繞射光學元所投射出的光場會有嚴重的畸變與強度不均勻在，本研究藉由設計全像光學元件第一繞射階光場形狀與控制元件蝕刻深度來改善之問題。在分析 Kinect 系統投影出的光場範圍之後，利用光學模擬軟體設計 HOE，分別用兩個面的相位多項式(Phase polynomial)設計 HOE 的繞射位置與光場大小，再將相位多項式合併描述出 HOE 的自由曲面。利用曲線擬合(Curve fitting)及二階化取樣的方式近似此自由曲面，並繪出 HOE 表面上的結構圖形。
接著，利用微影、蝕刻製程在玻璃上製作 HOE。由於設計出的圖案是一個線寬由粗到細依序由下往上排列的漸層弧形，以一般乾式蝕刻製程會導致做出來的 HOE結構深度不一致，在繞射上無法達到良好的效率。因此，本研究中嘗試更高真空度的蝕刻方式，使氣體分子在腔體內自由路徑更長、減少碰撞，能更垂直的入射試片使線寬不同之處產生相同的深度。
在深度量測上，將 Kinect 紅外線模組投射出來的斑點圖案轉換成空間頻率分佈進行量測。藉由建立數學關係式將實際結果和估算值進行比較，驗證其正確性。另外，從相機畫素、對焦位置以及影像擷取面積所帶來的影響做了整理。以目前的條件，深度量測精度已可以達到 1cm。

Based on previous studies, this study utilizes a holographic optical element(HOE) to replace the two dimensional diffractive optical element (DOE) of the
infrared emission system inside the Kinect sensor, so as to correct the projected light field with obvious distortion and uneven intensity distribution. Besides, this study adopts a novel depth measuring method by using spatial frequency to perform the depth measure of an object and discusses the its setup and measuring precision.
First, the infrared module of the Kinect sensor was analyzed to realize the element composition and operating mechanism. Owing to serious distortion and uneven intensity distribution in the light field after being projected through the two-dimensional DOE this study improves the problems by designing the light field
shape of the first diffraction order and controlling its etching depth of the HOE. After analyzing the light field range projected by the Kinect system, the optical simulation software was applied to the HOE design. Two phase polynomials were separately designed for the diffraction position and light field size, respectively. They were then merged as one to describe the free-form surface of the HOE. The curve fitting and binary sampling were used to approximate the free-form surface and depict the structural pattern on the HOE surface.
Then, the lithographic and etching processes were utilized to fabricate the HOE on glass. Since the designed pattern is a layered arc shape with lines of wide to thin from bottom to top, it will make the HOE have different structural depths and unable to get better diffraction efficiencies by using common dry etching processes.
Therefore, the research attempts an etching process under higher vacuum to provide the gas molecules longer free-path within the cavity to reduce the molecular collision,
and makes the incident ions more vertical to get consistent depths at different widths.
On the depth measuring, the speckle patterns projected by the Kinect infrared module were converted to the spatial frequency distribution for measuring. By establishing the mathematical relationship, the experimental results were compared with the estimated values for testing the validity. Furthermore, the influences from the images resolution, focus position and capturing area were also summarized. Under current conditions, the depth measuring accuracy of 1 cm could be well achieved.

致謝............................................................................................................................... II

摘要............................................................................................................................. III

ABSTRACT............................................................................................................... IV
目錄............................................................................................................................... V

圖目錄 ....................................................................................................................... VII

表目錄 ........................................................................................................................ XI

第一章 緒論 ................................................................................................................. 1
1.1 研究動機 ............................................................................................................. 1
1.2 文獻回顧 ............................................................................................................. 2
1.2.1 結構光(Structured Light)............................................................................ 2
1.2.2 Kinect 相關研究........................................................................................... 7
1.3 KINECT 感測系統介紹....................................................................................... 10
1.4 研究目的 ........................................................................................................... 12

第二章 理論基礎 ..................................................................................................... 16
2.1 空間頻率 ........................................................................................................... 16
2.2 繞射光柵(Diffraction grating)………………………………………………..18
2.3 全像光學元件(HOE)......................................................................................... 20

第三章 系統分析與元件設計 ................................................................................. 22
3.1 KINECT 系統分析............................................................................................... 22
3.1.1. 光源分析................................................................................................... 22
3.1.2. 光學元件量測........................................................................................... 23
3.1.3. Kinect 感測器量測分析............................................................................ 25
3.2 全像光學元件設計 ........................................................................................... 29
3.2.1 全像光學元件區域設計............................................................................ 33
3.2.2 光場大小設計............................................................................................ 34
3.2.3 二元光學面相位多項式設計.................................................................... 38
3.3 對先前研究設計之優化 ................................................................................... 41

第四章 元件製作與量測 ......................................................................................... 45
4.1 微影製程(Lithography)………………………………………………………47
4.2 蝕刻製程(Etching)………………………………………………………...….50
4.3 元件量測 ........................................................................................................... 53
第五章 系統量測與驗證 ......................................................................................... 56
5.1 相機參數與空間頻率之關係 ........................................................................... 56
5.1.1 對焦位置.................................................................................................... 56
5.1.2 影像解析度................................................................................................ 58
5.2 實驗架設與精度之關係 ................................................................................... 60
5.3 KINECT 感測器做空間頻率量測....................................................................... 66
5.4 全像光學元件搭配散斑元件做空間頻率量測 ............................................... 73

六、結果與討論 ......................................................................................................... 75
6.1 結論 ................................................................................................................... 75
6.2 未來展望：........................................................................................................ 76

參考文獻 ..................................................................................................................... 77

[1] J. Pages, J. Salvi, R. Garcia, C. Matabosch, “Overview of coded light projection techniques for automatic 3D profiling,” IEEE International Conference on Robotics & Automation (ICRA), vol 1, p 133-138, 2003.

[2] Jason. Geng, “Structured-light 3D surface imaging: a tutorial,” Advances in Optics and Photonics, vol 3, n 2, p 128-160, 2011.

[3] J. Salvi, J. Pages, J. Batlle, “Pattern codication strategies in structured light systems,” Pattern Recognition, vol 37, n 4, p 827-849, 2004.

[4] J. Posdamer, M. Altschuler, “Surface measurement by space-encoded projected beam systems,” Computer Graphics and Image Processing, vol 18, n 1, p 1-17, 1982.

[5] I. Ishii, K. Yamamoto, K. Doi, and T. Tsuji, “High-speed 3D image acquisition using coded structured light projection,” IEEE International Conference on Intelligent Robots and Systems, p 925-930, 2007.

[6] S. Jordan, M. Greenspan, “Projector Optical Distortion Calibration UsingGray Code Patterns,” 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, p 72-79, 2010.

[7] V. Srinivasan, H. Liu, M. Halious, “Automated phase-measuring profilometry: a phase mapping approach,” AppliedOptics, vol 24, p 185-188,1985

[8] P. S. Huang and S. Zhang, “A fast three-step phase shifting algorithm,” Appl. Opt. vol 45, n 21, p 5086–5091, 2006.

[9] J. Geng, “Method and apparatus for 3D imaging using light pattern having multiple sub-patterns,” U.S. patent 6 700 669, 2004.

[10] S. Fernandez, J. Salvi, and T. Pribanic, “Absolute phase mapping for one-shot dense pattern projection,” 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, p 64-71, 2010.

[11] N. G. Durdle, J. Thayyoor, and V. J. Raso, “An improved structured light technique for surface reconstruction of the human trunk,” IEEE Canadian Conference on Electrical and Computer Engineering, vol. 2, pp. 874–877, 1998.

[12] L. Zhang, B. Curless, and S. M. Seitz, “Rapid shape acquisition using color structured light and multi-pass dynamic programming,” First International Symposium on 3D Data Processing Visualization and Transmission, p. 24–36, 2002.

[13] P. Payeur and D. Desjardins, “Structured light stereoscopic imaging with dynamic pseudo-random patterns,” Image Analysis and Recognition, Lecture Notes in Computer Science, vol. 5627, p 687–696, 2009.

[14] J. Pag`es, J. Salvi, and C. Matabosch, “Robust segmentation and decoding of a grid pattern for structured light,” Pattern Recognition and Image Analysis, Lecture Notes in Computer Science, vol. 2652, p 689–696, 2003.

[15] D. Desjardins and P. Payeur, “Dense stereo range sensing with marching pseudo-random patterns,” Fourth Canadian Conference on Computer and Robot Vision, p 216–226, 2007.

[16] Z. Li, B. Curless, and S.-M. Seitz, “Rapid Shape Acquisition Using Color Structured Light and Multi-pass Dynamic Programming,” In Proceedings of the 1st International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT), p 24-36, June 2002.

[17] D. Scharstein, R. Szeliski, “High-accuracy stereo depth maps using structured light,” Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference, vol 1, p 195-202, June 2003.

[18] D. Desjardins, P. Payeur, “Dense Stereo Range Sensing with Marching Pseudo-Random Patterns,” Computer and Robot Vision, 2007. CRV ''07. Fourth Canadian Conference, p 216-226, May 2007.

[19] T. Pribanic, S. Mrvoš, J. Salvi, “Efficient multiple phase shift patterns for dense 3D acquisition in structured light scanning,” Image and Vision Computing, vol 28, n 8, p 1255-1266, August 2010.

[20] Microsoft Developer Network, “Kinect for Windows 開發,” http://msdn.microsoft.com/zh-tw/hh367958.aspx

[21] L. Xia, C.C. Chen and J. K. Aggarwal, “Human Detection Using Depth Information by Kinect,” Computer Vision and Pattern Recognition Workshops (CVPRW), 2011 IEEE Computer Society Conference, p 15-22, June 2011.

[22] K. Khoshelham, “Accuracy analysis of Kinect depth data,” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, ISPRS Calgary 2011 Workshop, vol 37, n 5, p113-138, August 2011.

[23] P. Henry, M. Krainin, E. Herbst, X. Ren and Dieter Fox, “RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments,” The international journal of robotics research, vol 31, n 5, p 647-663, April 2012.

[24] R.A. El-laithy, J. Huang, M. Yeh, “Study on the use of Microsoft Kinect for robotics applications,” Position Location and Navigation Symposium (PLANS), 2012 IEEE, p 1280-1288, April 2012

[25] A. Uckermann, C. Elbrechter, R. Haschke and H. Ritter, “3D Scene Segmentation for Autonomous Robot Grasping,” Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference, p 1734-1740, October 2012.

[26] Z. Ren, J. Meng, J. Yuan and Z. Zhang, “Robust Part-Based Hand Gesture Recognition Using Kinect Sensor,” IEEE Transactions on Multimedia, vol 15, n 5, p 1110-1120, August 2013.

[27] Microsoft Developer Network, “Kinect for Windows 開發,” http://msdn.microsoft.com/zh-tw/hh367958.aspx

[28] A. Shpunt, B. Pesach, “Optical pattern projection,” Primesense Ltd, U.S. Patent, NO. 8384997 B2, 2013.

[29] A. Shpunt, “Optical designs for zero order reduction,” Primesense Ltd, U.S. Patent, NO. 20090185274 A1, 2009.

[30] J. Garcia, Z. Zalevsky, “Range mapping using speckle decorrelation,” Primesense Ltd, U.S. Patent, NO. 7433024 B2, 2008.

[31] 黃韋閔。應用於 Kinect 立體感測器之新式投影元件設計。碩士論文。台中：中興大學機械工程學系。2012。

[32] 龍俊霖。以全像光學元件與空間頻率為基礎之立體量測系統。碩士論文。台中：中興大學機械工程學系。2013。

[33] M. Sheik-Bahae, “Fourier Optics,” Experimental Techniques of optic, University of New Mexico, 2014.

[34] T. S. Meese, “A Tutorial Essay on Spatial Filtering and Spatial Vision,” Neurosciences of Aston University, 2009

[35] E. Hecht, Optics. 4 ed. Addison-Wesley, 2001.

[36] G. Tricoles, “Computer generated holograms: an historical review,” Applied Optics, vol 26, n 20, p 4351-4360, 1987.

[37] ZEMAX 光學設計程式使用手冊。台北：訊連科技股份有限公司。2003。

[38] W. Goodman Joseph, Introduction to Fourier optics, Roberts & Company Publishers, 2005.

[39] R.C. Fairchild, J.R. Fienup, “Computer- originated aspheric holographic optical elements,” Optical Engineering, vol 21, n 1, page 133-140, 1982.

[40] Kinect for Windows, Microsoft.http://www.microsoft.com/en-us/kinectforwindows/

[41]OpenNI 2 SDK, Occipital, Inc.(PrimeSense).http://structure.io/openni

[42] AZ-1500 Series Photoresists, MicroChemicals.http://www.microchemicals.com/products/photoresists/az_1518.html

[43] OAI-500 mask aligner systems, Optical Associates, Inc.http://www.oainet.com/maskaligners-gate.html

[44] Handycam HDR-PJ790V 攝影機, Sony 台灣公司.http://goo.gl/XI6xfm