請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/15908完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 顏嗣鈞 | |
| dc.contributor.author | Chun-Yeh Liao | en |
| dc.contributor.author | 廖均燁 | zh_TW |
| dc.date.accessioned | 2021-06-07T17:55:04Z | - |
| dc.date.copyright | 2012-08-19 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-08-16 | |
| dc.identifier.citation | [1] L. Ji Hyoun, O. Tsimhoni, and L. Yili, 'Investigation of Driver Performance With Night Vision and Pedestrian Detection Systems-Part I: Empirical Study on Visual Clutter and Glance Behavior,' Intelligent Transportation Systems, IEEE Transactions on, vol. 11, pp. 670-677, 2010.
[2] L. Ji Hyoun, L. Yili, and O. Tsimhoni, 'Investigation of Driver Performance With Night-Vision and Pedestrian-Detection Systems-Part 2: Queuing Network Human Performance Modeling,' Intelligent Transportation Systems, IEEE Transactions on, vol. 11, pp. 765-772, 2010. [3] L. Yun, J. Remillard, and D. Hoetzer, 'Pedestrian detection in near-infrared night vision system,' in Intelligent Vehicles Symposium (IV), 2010 IEEE, 2010, pp. 51-58. [4] J. Byrnes, Unexploded Ordnance Detection and Mitigation: Springer, 2008. [5] C. Starr, Biology : concepts and applications. Belmont, CA: Brooks/Cole-Thomson Learning, 2003. [6] H. Lietz, J. Thomanek, B. Fardi, and G. Wanielik, 'Improvement of the Classifier Performance of a Pedestrian Detection System by Pixel-Based Data Fusion AI*IA 2009: Emergent Perspectives in Artificial Intelligence.' vol. 5883, R. Serra and R. Cucchiara, Eds., ed: Springer Berlin / Heidelberg, 2009, pp. 122-130. [7] M. Enzweiler, P. Kanter, and D. M. Gavrila, 'Monocular pedestrian recognition using motion parallax,' in Intelligent Vehicles Symposium, 2008 IEEE, 2008, pp. 792-797. [8] Z. Xin, Y. Mao, Z. Yingying, Z. Chuanzhi, and Z. Jinglei, 'Real Time ROI Generation for Pedestrian Detection,' in Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on, 2009, pp. 1-4. [9] G. Junfeng, L. Yupin, and T. Gyomei, 'Real-Time Pedestrian Detection and Tracking at Nighttime for Driver-Assistance Systems,' Intelligent Transportation Systems, IEEE Transactions on, vol. 10, pp. 283-298, 2009. [10] N. Dalal and B. Triggs, 'Histograms of oriented gradients for human detection,' in Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, 2005, pp. 886-893 vol. 1. [11] Y. Wang, J. Xing, X. Luo, and J. Zhang, 'Pedestrian Detection Using Coarse-to-Fine Method with Haar-Like and Shapelet Features,' in Multimedia Technology (ICMT), 2010 International Conference on, 2010, pp. 1-4. [12] W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, 'Section 16.5. Support Vector Machines,' in Numerical Recipes 3rd Edition: The Art of Scientific Computing, ed: Cambridge University Press, 2007, p. 1256. [13] L. Juan, S. Chunfu, X. Wangtu, and Y. Hao, 'Real Time Tracking of Moving Pedestrians,' in Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on, 2009, pp. 811-815. [14] R. O'Malley, M. Glavin, and E. Jones, 'An Efficient Region of Interest Generation Technique for Far-Infrared Pedestrian Detection,' in Consumer Electronics, 2008. ICCE 2008. Digest of Technical Papers. International Conference on, 2008, pp. 1-2. [15] O. Nobuyuki, 'A Threshold Selection Method from Gray-Level Histograms,' Systems, Man and Cybernetics, IEEE Transactions on, vol. 9, pp. 62-66, 1979. [16] C. Shyang-Lih, Y. Fu-Tzu, W. Wen-Po, C. Yu-An, and C. Sei-Wang, 'Nighttime pedestrian detection using thermal imaging based on HOG feature,' in System Science and Engineering (ICSSE), 2011 International Conference on, 2011, pp. 694-698. [17] Morphology-Opening. Available: http://homepages.inf.ed.ac.uk/rbf/HIPR2/open.htm [18] Morphology-Closing. Available: http://homepages.inf.ed.ac.uk/rbf/HIPR2/close.htm [19] J. Canny, 'A Computational Approach to Edge Detection,' Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. PAMI-8, pp. 679-698, 1986. [20] M. Weng and M. He, 'Image Feature Detection and Matching Based on SUSAN Method,' in Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on, 2006, pp. 322-325. [21] S. M. Smith and J. M. Brady, 'SUSAN-A New Approach to Low Level Image Processing,' Int. J. Comput. Vision, vol. 23, pp. 45-78, 1997. [22] J. Thomanek, M. Ritter, H. Lietz, and G. Wanielik, 'Comparing Visual Data Fusion Techniques Using FIR and Visible Light Sensors to Improve Pedestrian Detection,' in Digital Image Computing Techniques and Applications (DICTA), 2011 International Conference on, 2011, pp. 119-125. [23] OpenCV. Available: http://opencv.willowgarage.com/wiki/ | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/15908 | - |
| dc.description.abstract | 智慧型車輛已逐漸成為汽車工業中主要的趨勢，駕駛輔助系統在車輛安全、防止碰撞上更扮演一個重要的角色。駕駛輔助系統透過電腦與額外的感測器架構輔助駕駛，協助駕駛辨別遠方即將接近的障礙物與行人。
行人辨識系統的架構方面，通常分為3個階段，即分別是影像待選區域(ROI)產生、區域特徵偵測、行人追跡三個部份。 本論文即在探討配備近紅外線與紅外線的智慧型車載輔助系統中，利用影像邊緣特性，設法找出叢集特徵，並對於邊緣線段加以延展，判斷其特性後，產生影像待選區域。 實驗結果顯示，當偵測階段提高到一定的精準度時，運用此方式可以有效降低系統計算時間，成功迴避近紅外線與遠紅外線的不足，發展出更為有效率、高可靠度的方法。 | zh_TW |
| dc.description.abstract | Intelligent vehicles have gradually become the main trend in the automotive industry. Driver assistance systems, part of an intelligent vehicle, play an important role in safety and anti-collision domain. It helps drivers to identify the distance of the pedestrians and obstacles close-to-be by the computer and the sensor architecture.
Pedestrian recognition system framework is usually divided into three stages, respectively. First is the Region of interest (ROI) generation; the second is regional detection; and the last is pedestrian tracking. This thesis is to study the intelligent vehicle auxiliary systems with near-infrared (NIR) and far-infrared (FIR) camera, focusing in the stage of ROI generation. We discover a method to find out the extending edges of existing cluster ones. So that , we could determine the feature and generate ROIs. Experiment results show that this method can decrease the computation time on a system with more accurate detection stage. The method successfully compensates the lacks from NIR and FIR, enhancing the system to be more efficient and more reliable. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-07T17:55:04Z (GMT). No. of bitstreams: 1 ntu-101-R99921089-1.pdf: 2284610 bytes, checksum: 5a7c8b9ad5e9a666d2900313b0ec8daa (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | 口試委員會審定書 #
誌謝 i 中文摘要 ii 英文摘要 iii 目錄 iv 圖目錄 vi 表目錄 viii Chapter 1 緒論 1 Chapter 2 相關研究 7 2.1 二元化 7 2.1.1 使用Otsu's 演算法 8 2.1.2 雙閾值與水平掃描方法 9 2.2 連續影像關係性 10 2.3 影像邊緣產生 12 2.4 影像融合 13 Chapter 3 系統架構 16 3.1 移動式網格掃描法(Sliding Window) 19 3.2 輪廓與邊緣化影像 20 3.2.1 在近紅外線影像中使用Canny 操作方法 20 3.2.2 在遠紅外線影像中使用Susan操作方法 22 3.3 擷取簡易特徵 24 3.3.1 輪廓延伸演算法 25 3.3.2 簡易特徵偵測 31 3.4 簡易式記號層級的影像融合 32 Chapter 4 實驗操作 34 4.1 開源碼影像程式庫 34 4.2 實驗操作環境 34 4.3 準確度評估 36 4.4 實驗數據評比 37 4.4.1 遠紅外線 37 4.4.2 近紅外線 42 Chapter 5 結論與未來改善方向 44 參考文獻 45 | |
| dc.language.iso | zh-TW | |
| dc.subject | 影像待選區 | zh_TW |
| dc.subject | 近紅外線 | zh_TW |
| dc.subject | 遠紅外線 | zh_TW |
| dc.subject | 智慧型車輛 | zh_TW |
| dc.subject | 駕駛輔助系統 | zh_TW |
| dc.subject | 融合 | zh_TW |
| dc.subject | infrared | en |
| dc.subject | Pedestrian detection | en |
| dc.subject | ROI | en |
| dc.title | 利用雙紅外線產生行人偵測系統中之影像待選區 | zh_TW |
| dc.title | A Region of Interest Generation Technique for Pedestrian Detection Using Far and Near Infrared | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 郭斯彥,雷欽隆,黃秋煌 | |
| dc.subject.keyword | 近紅外線,遠紅外線,智慧型車輛,駕駛輔助系統,融合,影像待選區, | zh_TW |
| dc.subject.keyword | Pedestrian detection,ROI,infrared, | en |
| dc.relation.page | 47 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2012-08-16 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| 顯示於系所單位： | 電機工程學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-101-1.pdf 未授權公開取用 | 2.23 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。