3D影像重建隨著3D列印技術的迅速發展，已成為另一項研究發展的趨勢。3D掃描儀可以將實際物體透過光資訊蒐集與處理，將原樣的形狀與顏色等，重建為3D的數位模型。這些數位模型有涉及許多領域的用途，包含3D列印、工業檢測、缺陷檢測、機器視覺、地貌量測等皆可以看見它的應用。此外，智慧型手機具備完好的照相機，廣受使用者喜好.簡單便利的影像擷取設備，因此可搭配於桌上型光學系統或光學元件，光學成像結果成為許多研究用途；如手機顯微鏡可整合為重點照護診斷 (Point Of Care) 的手持式裝置，應用在成為細胞、生物、DNA等醫學檢驗與治療。近年來，有許多新創公司結合手機或平板的照相機影像與雷射掃描做3D影像重建，如Bevel3D、iSence3D等。這類型隨身式掃描裝置可對於臉部或大型物體的表面做3D影像的重建，並可做成3D立體影像與數位模型的輸出。因此，本論文使用薄透鏡結合手機而成以光學方式改變其焦距效果與放大倍率，並搭配雷射掃描輔助成為一個微型3D掃描儀，手機採二次光學的搭配薄透鏡，影像放大倍率0.85x，改變其原手機工作距離從67mm到35.4mm。實驗目標有別於臉部輪廓掃描等大型尺度的物體，設定為小物體尺度範圍做設定約為XY平面10mm x 10mm，因為其光學系統景深與雷射有效掃描的限制，Z有效區間範圍為5-7mm。最後經由手機App以720P錄影後擷取多張圖像檔，透過雷射掃描輔助，傳送至PC端MATLAB軟體的演算做3D影像的重建，輸出3D影像點圖(Point Of Cloud)。

3D image reconstruction hast been developed in recent years due to the 3D print technology. It is a new trend in 3D image technology industrial. 3D scanner is the device to reconstruct a 3D image. It translates the source light to 3D image or 3D models by image processing. These models reach many applications such as 3D print, industrial design, defect detection, robotic-optical image and so on. Smartphone is a user friendly image capture device. Therefore, many optical systems combine with smartphone to many research. The goal of the thesis research is to combining a smartphone with a simple lens becoming portable microscope, after 2D image optimization, assisted with an economical laser showing the 3D reconstruction image as result. Normally, 3D scanner is on big object such as face, motion detection. The system is under a small scale (10mmx10mm), thickness under 5-7mm. We use M6 screw as a standard object which shows measurement in x , y , z direction showing point of cloud figure as 3D model to result.

[1] O. Wulf and B. Wagner, "Fast 3D scanning methods for laser measurement systems," International conference on control systems and computer science, pp. 2-5,(2003).
[2] T. Stuyck, D. Vandermeulen, D. Smeets, and P. Claes, "HR-Kinect-High-Resolution Dynamic 3D Scanning for Facial Expression Analysis", (2014).
[3] M. Ares, S. Royo, J. Vidal, L. Campderrós, D. Panyella, F. Pérez, et al., "3D Scanning System for In-Vivo Imaging of Human Body," pp. 899-902, (2014).
[4] K. Carlsson, P.-E. Danielsson, A. Liljeborg, L. Majlöf, R. Lenz, and N. Åslund, "Three-dimensional microscopy using a confocal laser scanning microscope," Optics letters, vol. 10, pp. 53-55, (1985).
[5] T. G. Brown, C. J. Cogswell, T. Wilson, M. Duocastella, G. Vicidomini, and A. Diaspro, "Simultaneous multiplane imaging for 3D confocal microscopy using high-speed z-scanning multiplexing," vol. 9330, pp. 93300Q, (2015).
[6] 日商台灣基恩斯，http://www.keyence.com.tw/
[7] N. A. Borghese, G. Ferrigno, G. Baroni, A. Pedotti, S. Ferrari, and R. Savare, "Autoscan: a flexible and portable 3D scanner," IEEE Computer Graphics and Applications, vol. 18, pp. 38-41, (1998).
[8] J. Smisek, M. Jancosek, and T. Pajdla, "3D with Kinect," in 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops),, pp. 1154-1160, (2011).
[9] ITRI，https://www.itri.org.tw/
[10] Z. Zhang, "Microsoft Kinect Sensor and Its Effect," in IEEE MultiMedia, vol. 19, no. 2, pp. 4-10, (2012).
[11] ITRI，https://www.itri.org.tw/eng/DM/PublicationsPeriods/
[12] T. Pribanić, T. Petković, M. Đonlić, V. Angladon, and S. Gasparini, "3D Structured Light Scanner on the Smartphone," in International Conference Image Analysis and Recognition, pp. 443-450, (2016).
[13] ITRI，https://www.itri.org.tw/eng/DM/PublicationsPeriods/
[14] BEVEL3D，https://bevel3d.net
[15] 3D Object Reconstruction from Uncalibrated Images Using an Off-the-Shelf Camera - Scientific Figure on ResearchGate.
[16] D. Gilstrap, "Ericsson Mobility Report", (2013).
[17] N. A. Switz, M. V. D'Ambrosio, and D. A. Fletcher, "Low-cost mobile phone microscopy with a reversed mobile phone camera lens," PLoS One, vol. 9, pp. e95330, (2014).
[18] X. Liu, T. Y. Lin, and P. B. Lillehoj, "Smartphones for cell and biomolecular detection," Ann Biomed Eng, vol. 42, pp. 2205-17, (2014).
[19] A. Skandarajah, C. D. Reber, N. A. Switz, and D. A. Fletcher, "Quantitative imaging with a mobile phone microscope,"PLoS One, Public Library of Science, (2014).
[20] R. R. Jahan-Tigh, G. M. Chinn, and R. P. Rapini, "A Comparative Study Between Smartphone-Based Microscopy and Conventional Light Microscopy in 1021 Dermatopathology Specimens," Archives of pathology & laboratory medicine, vol. 140, pp. 86-90, (2016).
[21] J. Apolinar and M. Rodríguez, "Three-dimensional microscope vision system based on micro laser line scanning and adaptive genetic algorithms," Optics Communications, vol. 385, pp. 1-8, (2017).
[22] C. Rocchini, P. Cignoni, C. Montani, P. Pingi, and R. Scopigno, "A low cost 3D scanner based on structured light," Computer Graphics Forum, vol. 20, pp. 299-308, (2001).
[23] L. Zhang and W. J. Tam, "Stereoscopic Image Generation Based on Depth 70 Images for 3D TV," IEEE Transactions on Broadcasting, vol. 51, pp. 191-199, (2005).
[24] J. Shotton, T. Sharp, A. Kipman, A. Fitzgibbon, M. Finocchio, A. Blake, et al., "Real-time human pose recognition in parts from single depth images," Communications of the ACM, vol. 56, pp. 116-124, (2013).
[25] A. Saxena, S. H. Chung, and A. Y. Ng, "3-D Depth Reconstruction from a Single Still Image," International Journal of Computer Vision, vol. 76, pp. 53-69, (2008).
[26] H. Kim, S. Leutenegger, and A. J. Davison, "Real-Time 3D Reconstruction and 6-DoF Tracking with an Event Camera," ECCV, pp. 349-364, (2016).
[27] ITRI，http://www.itrc.narl.org.tw/Publication/Newsletter/no115/p08.php
[28] Comparing 3D scanning，http://www.chromatographyonline.com/comparing-capabilities-time-flight-and-quadrupole-mass-spectrometers-0
[29] E. Hecht, "Optics, 4th," International edition, Addison-Wesley, San Francisco, vol. 3, (2002).
[30] Bruce Spatz, "Optics", second edition, Eugene Hecht Adelphi University, Oxford Illustrators, P.220～P.227, (1987).
[31] Courses Pages, Bristol Community College, Prof. Igor Kholodov webpage
[32] MATLAB CAMERA CALIBRATION TOOL BOX, http://www.vision.caltech.edu/bouguetj/calib_doc/htmls/ref.html