簡易檢索 / 詳目顯示

研究生: 蔡宗諭
Tsung-Yu Tsai
論文名稱: 即時車種分類與計數
Real-Time Vehicle Classifiaction and Counting
指導教授: 陳世旺
Chen, Sei-Wang
學位類別: 碩士
Master
系所名稱: 資訊教育研究所
Graduate Institute of Information and Computer Education
論文出版年: 2004
畢業學年度: 92
語文別: 中文
論文頁數: 120
中文關鍵詞: 累計曲線法漸進式背景影像建構EP影像隱藏式馬可夫鏈陰影去除模糊限制滿足技術遮掩處理
英文關鍵詞: Accumulative curve method, Progressive background image generation,, Epipolar-plane image, Hidden Markov model, Shadow removal, Fuzzy constraints satisfaction problem, Occlusion resolution
論文種類: 學術論文
相關次數: 點閱:195下載:7
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 本文利用視訊影像處理的技術,提出一利用累計曲線來從事車輛偵測、車種分類及計數的方法。在系統運作的過程中,主要可以分為三個步驟:ROI(region of interesting)的偵測、陰影的去除、及車輛遮掩的處理。首先自輸入的影像序列建立EP(epipolar-plane)影像,並同時利用累計曲線法快速地自EP影像中取出對應車輛的ROI;接下來利用隱藏式馬可夫模組(hidden Markov model)來去除ROI中屬於陰影的部分。之後結合累計曲線法及模糊限制滿足(fuzzy constraints satisfaction)技術,自可能有遮掩情形的ROI中分離出獨立的車輛,最後再將車輛分類與計數。實驗的結果顯示所提技術可以在無特殊輔助硬體的環境下,有效地即時執行車種分類與計數,並提供相當高的精確度。

    In this thesis, a system for vehicle classification and counting (VCC) is developed. The system consisting of a video camcorder, a host computer and a number of communication devices is easy to move, install and operate. There are three major modules involved in the proposed VCC process , they are region of interesting (ROI) detection, shadow removal, and occlusion resolution. First of all, an epipolar-plane (EP) image formed from the input video sequence is produced. ROI’s are then extracted from the EP image using an accumulative curve method. For each ROI, a hidden Markov model (HMM) is applied to examine whether there are shadows in the ROI. If shadows are found, they are eliminated. Afterward, a technique integrating the accumulative curve method and a fuzzy constraints satisfaction approach is invoked to separate (if occlusion exists) and count the vehicle within the ROI. The proposed system has been examined using a number of real image sequences. The experimental results have revealed that our proposed system has performed reasonably well during daytime. For rainy days and nighttime, the system should be further improved.

    目錄 圖表目錄………………………………………………………………ii 第一章 簡介…………………………………………………………1-1 1.1 相關研究……………………………………………………1-3 1.2 論文架構……………………………………………………1-8 第二章 系統架構與ROI偵測………………………………………2-1 2.1 系統流程……………………………………………………2-3 2.2 背景影像的建立與更新……………………………………2-3 2.3 累計曲線的建立……………………………………………2-4 2.4 累計曲線的特性……………………………………………2-4 2.5 ROI的偵測…………………………………………………2-6 2.6 ROI的修正……………………………………………………2-7 第三章 陰影去除……………………………………………………3-1 3.1隱藏式馬可夫模組……………………………………………3-1 3.2 陰影去除……………………………………………………3-14 3.3 陰影去除實驗………………………………………………3-19 第四章 車輛的分類與計數…………………………………………4-1 4.1 系統流程………………………………………………………4-1 4.2 ROI累計曲線的建立…………………………………………4-2 4.3 車輛的遮掩偵測………………………………………………4-2 4.4 FCSP的概念……………………………………………………4-3 4.5 遮掩偵測與遮掩處理………………………………………4-12 第五章 實驗結果……………………………………………………5-1 第六章 結論與未來方向……………………………………………6-1 參考文獻………………………………………………………………7-1

    [Joh89]B. Johns, A. Brown-Kenyon and T. Sullivan, “Traffic data collection – automation of the national core census and the incorporation of dynamic axle weighting,” Road Traffic Monitoring, 1989.
    [Li99]C. Li, K. Ikeuchi and M. Sakauchi, “Acquisition of traffic information using a video camera with 2d spatio-temporal image transformation technique,” ITSC'99 Conference Program, 1999
    [Law02]W. Lawrence and A. Y. Kuo, “Development of a Fuzzy Neural Network Color Image Vehicular Detection (FNNCIVD) System,” IEEE 5th International Conference on Intelligent Transportation Systems, pp. 88-93, 2002.
    [Zhu96]Z. Zhu, G. Xu, B. Yang, "Automatic traffic monitoring system using 2D spatio-temporal images," Journal of Image and Graphics, vol 1, pp. 107-113, 1996.
    [Bre76]L. E. Brennan, J. D. Mallett, and I. S. Reed, "Adaptive Ar-rays in Airborne MTI Radar," IEEE Trans. on Antennas andPropagation, Vol. AP-24, 1976, pp. 607-615, 1976.
    [Gir01]R. GIRET , S. MERIC , G. CHASSAY, " Radar images of vehicles based on SAR/ISAR Processing," IEEE AP-S INTERNATIONAL SYMPOSIUM AND USNC/URSI NATIONAL RADIO SCIENCE MEETING , 2001.
    [Kag00]M. Kagesawa, A. Nakamura, K. Ikeuchi, and H. Saito, “Local-feature Based Vehicle Class Recognition in Infra-red Image Using IMAP Parallel Vision Board,” IEEE Inteligent Transportation Systems Conference Proceedings , 2000.
    [Fur97]N. Furstenau, H. Horack, W. Schmidt, “Extrinsic Fabry-Perot Interferometer Fiber – Optic Microphone,” IEEE Insrrumentation and Measurement Technology Conference, 1997.
    [Gup02]S. Gupte, O. Masoud, R. F. K. Martin,and N. P. Papanikolopoulos, “Detection and classification of Vehicles,” IEEE Transactions on Intelligent Transportation Systems, vol.3,no.1, 2002.
    [Gaj01]J. Gajda, R. Sroka, M. Stencel, A. Wajda and T. Zeglen, “A Vehicle Classification Based on Inductive Loop Detectors,” IEEE Instrumentation and Measurement Technology Conference, 2001.
    [Mic93]P. G.. Michalopoulos, R. D. Jacobson, C. A. Anderson, and T. B. BeBruycker, “Automatic Incident Detection Through Video Image Processing”, Traffic Engineering and Control, 1993.
    [Mic91]P. G. Michalopoulos, ”Vehicle Detection Through Video Image Processing: The AUTOSCOPE System,” IEEE Transactions on Vehicular Technology, Vol. 40,No. 1, pp.21-29, 1991.
    [Kil92]J. Kilger, “A shadow handler in a video-based realtime traffic monitoring system," Proc. IEEE Workshop on Applications of Computer Vision, pp. 11-18, 1992.
    [Dub95]M. Dubuisson and A. K. Jain, “Contour extraction of moving objects in complex outdoor scenes,” International Journal of Computer Vision,vol. 14, pp. 83-105, 1995
    [Yea92]L. Yean-Jyc, ”Vehicle classification using infrared image,” Journal of Transportation Engineering, vol. 118, no. 2, pp. 223-240,1992.
    [Alt98]Y. Altunbasak, P. E. Eren and A. M. Tekalp, “Region-Based Parametric Motion Segmentation Using Color Information,” Graphical Models and Images Processing,vol. 60, no.1,pp.13-23, 1998.
    [Bak92]K. D. Baker and G. D. Sullivian, “Performance assessment of model-based tracking,” Proc. Of IEEE Workshop on Application of Computer Vision, pp. 28-35, 1992.
    [Bad98]J. Badenas and F. Pla,”Segmentation Based on Region-Tracking in Image Sequences for Traffic Monitoring,”Proc. Of 14th Int’l Conf. On Pattern Recognition,vol. 2, pp.999-1001, 1998.
    [Bey97]D. Beymer, P. McLauchlan, B. Coifman, and J. Malik, “A Real-Time Computer Vision System for Measuring Traffic Parameters,” Proc. Of IEEE Conf. On Computer Vision and Pattern Recognition,pp. 495-501, 1997.
    [Cha02]C. J. Chang, W. F. Hu, J. W. Hsieh, and Y. S. Chen, “An Automatic Traffic Surveillance System for Tracking and Classifying Vehicles,” Proc. Of 15th IPPR Conf. On Computer Vision, Graphics and Image Processing, pp. 382-387,2002.
    [Cha02]C. J. Chang, W. F. Hu, J. W. Hsieh, and Y. S. Chen, “Shadow Elimination for Effective Object Detection,” Proc. Of 15th IPPR Conf. On Computer Vision, Graphics and Image Processing, pp. 185-192, 2002.
    [Chu01]J. H. Chun, “Automatic Traffic Monitoring System,” MS Thesis, Dept. of Information and Computer Education, National Taiwan Normal University, 2001.
    [Chu02]Y. C. Chung, J. M. Wang and S. W. Chen, “A Vision-Based Traffic Light Detection System at Intersections,” Journal of Taiwan Normal University: Mathematics,Science & Technology, vol. 47, no.1,pp. 67-86,2002.
    [Cuc00]R. Cucchiara, M. Piccardi and P. Mello, “Image Analysis and Rule-Based Reasoning for a Traffic Monitoring System,” IEEE Trans. On Intelligent Transportation System, vol. 1, no. 2, pp. 119-130, June 2000.
    [Dai99]D. J. Dailey, L. Li, “An algorithm to estimate vehicle speed using uncalibrated cameras,” Proc. Of IEEE/IEEJ/JSAI International Conference on Inteligent Transportation System, pp. 441-446, 1999.
    [Der90]R. Deriche and O. D. Faugeras, “Tracking Line Segments,” Image and Vision Computing, vol. 8, no. 4, pp. 261-270, 1990.
    [Fat95]M. Fathy and M. Y. Siyal, “An Image Detection Technique Based on Morphological Edge Detection and Background Differencing for Real-Time Traffic Analysis,” Pattern Recognition, vol. 16, pp. 1321-1330,1995.
    [Fer98]J. M. Ferryman, S. J. Maybank and A. D. Worrall, “Visual Surveillance for Moving Vehicles,” Proc. Of IEEE Workshop on Visual Surveillance, pp. 73-80, 1998.
    [Gam97]P. Gamba, M. Lilla and A. Mecocci, “A Fast Algorithm for Target Shadow Removal in Monocular Colour Sequences,”Proc. Of Int’l Conf. On Image Processing, vol.1 ,pp. 436-447, 1997.
    [Gar96]W. F. Gardner and D. T. Lawton, “Interactive Model-Based Vehicle Tracking,” IEEE Trans. On Pattern Analysis and Machine Intelligence, vol. 18, pp.1115-1121, 1996.
    [Gru91]D. Gruyer and V. B. Cherfaoui, “Matching and Decision for Vehicle Tracking inRoad Situation,” Proc. Of IEEE Int’l Conf. On Intelligent Robots and System, vol. 1,pp. 29-34, 1991.
    [Gup00]S. Gupte, O. Masoud and N. P. Papanikolopoulos, “Vision-Based Vehicle Classification,” Proc. Of IEEE Conf. On Intelligent Transportation Systems, pp. 46-51, 2000.
    [Gup02]S. Gupte, O. Masoud, R. F. K. Martin, and N. P. Papanikolopoulos, “Detection and Classification of Vehicles,” IEEE Trans. On Intelligent Transportation Systems, vol. 3,no. 1, pp. 37-47. March 2002.
    [Jia92]C. Jiang and M. O. Ward, “Shadow Indentification,” Proc. Of IEEE Conf. On Computer Vision and Pattern Recognition, pp. 606-612, 1992.
    [Yun99]Y. K. Jung and Y. S. Ho, “Traffic Parameter Extraction Using Video-Based Vehicle Tracking,” Proc. Of IEEE Int’l Conf. On Intelligent Transportation Systems, pp. 764-769, 1999.
    [Kam00]S. Kamijo, Y. Matsushita, K. Ikeuchi, and M. Sakauchi, “Traffic Monitoring and Accident Detection at Intersections,” IEEE Trans. On Intelligent Transportation Systems, vol. 1,no. 2, pp. 108-118, 2000.
    [Kim01]J. B. Kim, C. W. Lee, K. M. Lee, T. S. Yun, and H. J. Kim, “Wavelet-Based Vehicle Tracking for Automatic Traffic Surveillance,” Proc. Of IEEE Int’l Conf. On Electrical and Electronic Technology, vol. 1,pp. 313-316, 2001.
    [Kle01]L. A. Klein, Sensor Technologies and Data Requirements for ITS, Artech House, 2001.
    [Kol93]D. Koller, J. Daniilidis and H. H. Nagel, “Model-Based Object Tracking in Monocular Image Sequences of Road Traffic Scenes,” Int’l J. Computer Vision, vol. 10, pp. 257-281, 1993.
    [Lai98]A. H. S. Lai and N. H. C. Yung, “A Fast and Accurate Scoreboard Algorithm for Estimating Stationary Background in an Image Sequence,” Proc. Of IEEE Int’l Symp. On Circuits and Systems, vol. 4, pp. 241-244, 1998.
    [Lai98]A. H. S. Lai and N. H. C. Yung and C. Zhang, “An Intelligent Framework for Spatio-Temporal Vehicle Tracking,” Proc. Of IEEE Int’l Symp. On Circuits and Systems, vol. 4, pp. 241-244, 1998.
    [Lai00]A. H. S. Lai and N. H. C. Yung, ”Lane Detection by Orientation and Length Discrimmination,” IEEE Trans. On System, Man and Cybernetics, Part B, vol. 30,no. 4, pp. 539-548, 2000.
    [Lee02]I. Lee, H. Ko and D. K. Han, “Multiple Vehicle Tracking Based on Regional Estimation in Nighttime CCD Images,” Proc. Of IEEE Int’l Conf. On Acoustics, Speech, and Signal, vol. 4, pp. 3712-3715, 2002.
    [Leu01]H. Leuck and H. H. Nagel, “Model-Based Initialization of Vehicle Tracking:Dependency on Illumination,” Proc. Of Int’l Conf. On Computer Vision,Vancouver, B.C., Canada, pp. 309-314, July 2001.
    [Leu93]J. ven Leuven, M. B. ven Leeuwen and F. C. A. Groen, “Real-Time Vehicle Tracking in Image Sequences,” Proc. Of 18th IEEE Conf. On Instrumentation and Measurement Technology, vol. 3, pp. 2049-2054, 2001.
    [Ley93]F. Leymarie and M. D. Levine, “Tracking Deformable Objects in the Plane Using an Active Contour Model,” IEEE Trans. On Pattern Analysis and Machine Intelligence, vol. 15,no. 6, pp.617-634, 1993.
    [Lil92]M. Lilger, “A Shadow Handler in a Video-Based Real-Time Traffic Monitoring System,” Proc of IEEE Workshop on Application of Computer Vision, pp. 11-18, 1992.
    [Lim02]D. W. Lim, S. H. Choi and J. S. Jun, “Automated Detection of all Kinds of Violations at a Street Intersection Using Real-Time Indivisual Vehicle Tracking,” Proc. Of Fifth IEEE Southwest Syposium on Image Analysis and Interpretation, pp. 126-129, 2002.
    [Lip98]A. J. Lipton, H. Fujiyoshi and R. S. Patil, “Moving Target Classification and Tracking From Real-Time Video,” Proc. Of Fourth IEEE Workshop on Application of Computer Vision, pp. 8-4, 1998.
    [Liu01]X. Liu, D. Yao, L. Cao, L. Peng, and Z. Zhang, “A Feature-Based Real-Time Traffic Tracking System Using Spatial Filtering,” Proc. Of IEEE Inteligent Transportation Systems, pp. 514-518, 2001.
    [Liu01]Z. Q. Liu, L. T. Bruton, J. C. Bezdek, J. M. Keller, S. Dance, N. R. Bartley, and C. Zhang, “Dynamic Image Sequence Analysis Using Fuzzy Measures,” IEEE Trans. On Systems, Man and Cybernetics, Part B, vol. 31, no. 4, pp. 557-572, 2001.
    [Lon90]W. Long and Y. H. Yang, “Stationary Background Generation: an Alternative to the Difference of Two Images,” Pattern Recognition, vol 23, no. 12, pp. 1351-1359, 1990.
    [Mae96]Y. Mae, Y. Shirai, J. Miura, and Y. Kuno, “Object Tracking in Cluttered Background Based on Optical Flow and Edges,” Proc. Of 13th Int’l Conf. On Pattern Recognition, vol. 1,pp. 196-200, 1996.
    [Mal89]S. G. Mallat, “Multi-Frequency Channel Decomposition of Images and Wavelet Models,” IEEE Trans. On Acoustic, Speech and Signal Processing, vol. 37, no. 12,pp. 2091-2110, 1989.
    [Mas99]O. Masoud, N. P. Papanikolopoulos and E. Kwon, “Vision-Based Monitoring of Weaving Sections,” IEEE/IEEJ/JSAI International Conference on Inteligent Transportation Systems, pp. 770-775, 1999.
    [Nak92]T. Nakanishi, K. Ishii, “Automatic vehicle image extraction based on spatio-temporal image analysis,” Proc. Of 11th IAPR International Conference on Pattern Recognition, Vol. 1, Conference A: Computer Vision and Applications, pp. 500-504, 1992.
    [Oro99]E. Oron, “Motion Estimation and Image Difference for Multi-Object Tracking,” Proc. Of IEEE Conf. On Aerospace, vol. 4,pp. 401-409, 1999.
    [Pag97]R. Paget, I. D. Longstaff and B. Lovell, “Texture Classification Using Nonparametric Markov Random Fields,” Proc. Of 13th Int’l Conf. On Digital Signal Processing, vol. 1, pp. 67-70, 1997.

    QR CODE