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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 楊佳玲 | |
| dc.contributor.author | Tai-Ta Chou | en |
| dc.contributor.author | 周台大 | zh_TW |
| dc.date.accessioned | 2021-06-13T02:16:41Z | - |
| dc.date.available | 2009-06-22 | |
| dc.date.copyright | 2007-02-27 | |
| dc.date.issued | 2007 | |
| dc.date.submitted | 2007-02-08 | |
| dc.identifier.citation | [1] A. K. Jain D. Gutchess and Sei-Wang., Automatic surveillance using omnidirectional and active cameras.,' In Asian Conference on Computer Vision (ACCV), Jan 2000.
[2] A. Gupta J. C. I. Tashev L. wei He A. Colburn Z. Zhang Z. Liu R. Cutler, Y. Rui and S. Silverberg., Distributed meetings: A meeting capture and broadcasting system.,' In ACM Multimedia,, 2002. [3] W. Yin A. Erkin P. Lewis C. Power T. Boult, C. Qian and R.Micheal., Applications of omnidirectional imaging: Multi-body tracking and remote reality.,' IEEE Workshop on Applications of Computer Vision,, Dec 1998. [4] P. Greguss., The tube peeper: A new concept in endoscopy.,' In Optics and Laser Technologies, pp. 41~45, 1985. [5] A. Basu and D. Southwell., Omni-directional sensor for pipe inspection.,' Proc. of IEEE Int. Conf. Systems, Man and Cybernetics, 1995. [6] R. Bunschoten and B. Krse., 3-d scene reconstruction from cylindrical panoramic images.,' Robotics and Autonomous Systems (special issue), 2002. [7] Hua H. Tan, K.-H. and N. Ahuja, Multiview Panoramic Cameras Using Mirror Pyramids.,' IEEE Trans. Pattern Anal. Mach. Intell., p. 941~946, July 2004. [8] Caihua Wang Yutaka Sato Hideki Tanahashi Yoshinori Niwa Sanae Shimizu, Kazuhiko Yamamoto, Moving Object Detection with Mobile Stereo Omni-directional System (SOS) based on Motion Compensatory Inter-frame Depth Subtraction,' International Conference on Pattern Recognition, 2004. [9] Ross Cutler Harsh Nanda, Practical Calibrations for a real-time digital omnidirectional camera,' Technical Sketches, Computer Vision and Pattern Recognition, Hawaii, US, Dec 2001. [10] S. B. Kang and R. Szeliski, 3-d scene data recovery using omnidirectional multi-baseline stereo.,' Int. J. Comput. Vision, p. 167~183, Oct 1997. [11] Yamamoto M. Ishiguro, H. and S. Tsuji, Omni-Directional Stereo.,' IEEE Trans. Pattern Anal. Mach. Intell., pp. 257~262, 1992. [12] Kaidan 360 one VR, http://www.kaidan.com/. [13] Sony RPU-C2512/C3522, http://www.sonybiz.net/vision. [14] Egg Solution, http://www.eggsolution.com. [15] J. F. Canny., Finding Edges and Lines In Images.,' Master's thesis, MIT. AI Lab.,1983. [16] J. F. Canny., A Computational Approach to Edge Detection.,' IEEE Trans. Pattern Analysis and Machine Intelligence., pp. 679~698, 1986. [17] Albovik, Handbook of Image and Video Processing, Academic Press, 2000. [18] C.Linquist M.Woodhall, New Edge Detection Algorithms Based on Adaptive Estimation Filters,' Conference Record of the 31st Asilomar IEEE Conference on Signals Systems & Computers,volume: 2, pp. 1695~1699, 1997. [19] Xilinx Corporation, http://www.xilinx.com/. [20] James Hwang and Jonathan Ballagh, Building custom fir filters using system generator,' 12th International Field-Programmable Logic and Applications Conference, September 2002. [21] The MathWorks Homepage, http://www.mathworks.com/. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/30813 | - |
| dc.description.abstract | Traditionally, image stitching allows users to combine multiple regular-sized images into a single wide-angle picture, often be named as a panoramic picture. In order to create such a panoramic picture, users usually need to take a lot of photographs, then upload them to a PC and stitch. Now, we only take one shot using an omnidirectional sensor, then we can get a 360-degree full environmental image. In this way, we can have a panoramic image easier and faster than before. Because of this reason, more and more researches and applications start to change traditional sensor to omnidirectional sensor. In recent year, mobile robot is an active research project, especially for robotic vision system. Eyes are the window of the soul. Hence, we believe that vision for mobile robot is as important as eye for human. Through omnidirectional sensor, mobile robots can receive more environmental information and then it will have more abilities for moving and locating. In this work, we will describe how to unwrap an omnidirectional image to a correctly panoramic image and use edge detection to get the whole environmental edge's information. Beside, we will implement the design into hardware to have a better computation performance. The experimental result will show out panoramic video output from an omnidirectional RGB camera input. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-13T02:16:41Z (GMT). No. of bitstreams: 1 ntu-96-J93922005-1.pdf: 3022992 bytes, checksum: 219721fd065d2812160f9870c48bc9cf (MD5) Previous issue date: 2007 | en |
| dc.description.tableofcontents | Abstract i
1 Introduction 1 2 Related Work 4 2.1 Omnidirectional Vision System . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Edge Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3 Unwrap 360-degree Omnidirectional Image and Edge Detection 10 3.1 Unwrapping 360-degree Omnidirectional Image . . . . . . . . . . . . . . . . . . 11 3.2 Sobel Edge Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4 Hardware Implementation 16 4.1 Hardware Design Platform . . . . . . . . . . . . . . . . . . . . . . . . . . 16 4.1.1 Virtex-4 ML402 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 4.1.2 Video I/O Daughter Card . . . . . . . . . . . . . . . . . . . . . . 17 4.1.3 LVDS RGB Camera . . . . . . . . . . . . . . . . . . . . . . . . . 17 4.1.4 Hardware Platform Diagram . . . . . . . . . . . . . . . . . . . . . 18 4.2 Hardware Implementation of Lens Correction for 360-degree Panorama . . . . . 19 4.3 Hardware Implementation of Edge Detection . . . . . . . . . . . . . . . . 21 4.4 Pipeline Flow of Hardware . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4.5 Xilinx Design Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 5 Experimental Results 25 6 Conclusion 34 | |
| dc.language.iso | en | |
| dc.subject | 可程式化邏輯閘陣列 | zh_TW |
| dc.subject | 全景影像 | zh_TW |
| dc.subject | 邊緣偵測 | zh_TW |
| dc.subject | Panorama | en |
| dc.subject | Edge Detection | en |
| dc.subject | FPGA | en |
| dc.title | 360度全景影像修正暨邊緣偵測之硬體實現 | zh_TW |
| dc.title | A Hardware Implementation of Edge Detection and Lens Correction for 360-degree Panorama | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 95-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 王傑智,顧孟愷,洪士灝 | |
| dc.subject.keyword | 全景影像,邊緣偵測,可程式化邏輯閘陣列, | zh_TW |
| dc.subject.keyword | Panorama,Edge Detection,FPGA, | en |
| dc.relation.page | 38 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2007-02-09 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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|---|---|---|---|
| ntu-96-1.pdf 未授權公開取用 | 2.95 MB | Adobe PDF |
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