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Relevant bibliographies by topics / Traffic flow Image processing

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Academic literature on the topic 'Traffic flow Image processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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Journal articles on the topic "Traffic flow Image processing"

1

Kudo, Yasuo. "Traffic flow measurement system using image processing." Systems and Computers in Japan 17, no. 1 (1986): 62–72. http://dx.doi.org/10.1002/scj.4690170108.

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FUJITOMI, Go, Kentaro OHKUBO, and Katsuhiro YAMAMOTO. "Measurement of Urban Traffic Flow Using Image Processing." Journal of the Visualization Society of Japan 20, no. 1Supplement (2000): 197–200. http://dx.doi.org/10.3154/jvs.20.1supplement_197.

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Farooq, M. U., A. Ahmed, S. M. Khan, and M. B. Nawaz. "Estimation of Traffic Occupancy using Image Segmentation." Engineering, Technology & Applied Science Research 11, no. 4 (2021): 7291–95. http://dx.doi.org/10.48084/etasr.4218.

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Increased traffic flow results in high road occupancy. Traffic road occupancy is often used as a parameter for the prediction of traffic conditions by traffic engineers. Although traffic monitoring systems are based on a large number of technologies, challenges are still present. Most of the methods work efficiently for free-flow traffic but not in heavy congestion. Image processing techniques are more effective than other methods, as they are based on loop sensors and detectors to monitor road traffic. A huge number of image frames are processed in image processing hence there is a need for a

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Atkočiūnas, E., R. Blake, A. Juozapavičius, and M. Kazimianec. "Image Processing in Road Traffic Analysis." Nonlinear Analysis: Modelling and Control 10, no. 4 (2005): 315–32. http://dx.doi.org/10.15388/na.2005.10.4.15112.

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The article presents an application of computer vision methods to traffic flow monitoring and road traffic analysis. The application is utilizing image-processing and pattern recognition methods designed and modified to the needs and constrains of road traffic analysis. These methods combined together gives functional capabilities of the system to monitor the road, to initiate automated vehicle tracking, to measure the speed, and to recognize number plates of a car. Software developed was applied in and approved with video monitoring system, based on standard CCTV cameras connected to wide are

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Et. al., Lakshmanan M,. "Traffic Light Controller using Image Processing." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (2021): 405–11. http://dx.doi.org/10.17762/turcomat.v12i2.824.

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Traffic congestion at junctions is a serious issue on a daily basis. The prevailing traffic light controllers are unable to manage the different traffic flows. Most of the current systems operate on a timing mechanism that changes the signal after a particular interval of time. This may cause frustration and result in motorist's time waste. Traffic congestion is a major problem in the currently existing systems. Delays, safety, parking, and environmental problems are the main issues of current traffic systems that emit smoke and contribute to increasing Global Warming. Sensor-based systems red

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Hоуеr, R., and M. Fellendorf. "Parametrization of Microscopic Traffic Flow Models Through Image Processing." IFAC Proceedings Volumes 30, no. 8 (1997): 889–94. http://dx.doi.org/10.1016/s1474-6670(17)43934-6.

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Iwata, Takeo. "Image Techniques for Safe and Comfortable Automobile Driving. Image Processing Technologies for Traffic Control System. Traffic Flow Measurment Utilizing Image Processing." Journal of the Institute of Image Information and Television Engineers 51, no. 6 (1997): 766–68. http://dx.doi.org/10.3169/itej.51.766.

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Taniguchi, Hiroyasu, Takahiro Nakamura, Haruki Furusawa, and Shinji Ozawa. "A Traffic Flow Surveillance Method using Spatio-Temporal Image Processing." IEEJ Transactions on Industry Applications 122, no. 5 (2002): 531–40. http://dx.doi.org/10.1541/ieejias.122.531.

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Soto, Alvaro, and Aldo Cipriano. "Image Processing Applied to Real Time Measurement of Traffic Flow." IFAC Proceedings Volumes 28, no. 19 (1995): 43–48. http://dx.doi.org/10.1016/s1474-6670(17)45056-7.

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Gong, Suning, Rakesh Kumar, and D. Kumutha. "Design of Lighting Intelligent Control System Based on OpenCV Image Processing Technology." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 29, Supp01 (2021): 119–39. http://dx.doi.org/10.1142/s0218488521400079.

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The high growth of vehicular travel in urban areas, in particular, requires a traffic control system that optimizes traffic flow efficiency. Traffic congestion can also occur by large de-lays in Red Light etc. The delay in lighting is difficult to code and does not rely on real traffic density. It follows that traffic controls are simulated and configured to better meet this rising demand. So, in order to avoid the traffic control problem, the Adaptive Intelligent Traffic Light control system (AITLCS) has been proposed based on OpenCV and Image processing technique. The system proposed is desi

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Dissertations / Theses on the topic "Traffic flow Image processing"

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Pierce, Ryan. "Incident modeling with the use of video reidentification /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p1422955.

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Hoummady, Bouchaïb. "Système d'analyse de mouvement dans les images routières : samir." Saint-Etienne, 1988. http://www.theses.fr/1988STET4002.

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Après une présentation de l'intérêt et des enjeux d'un capteur d'images de trafic routier, une bibliographie des principales recherches d'extraction de paramètres de trafic par analyse d'image et une mise au point sur les principales techniques de segmentation de l'image, l'auteur présente le nouveau système d'extraction, d'analyse et de quantification automatique du mouvement dans les images de trafic routier : SAMIR

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Thomson, Malcolm S. "Real-time image processing for traffic analysis." Thesis, Edinburgh Napier University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.260986.

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Dickinson, Keith William. "Traffic data capture and analysis using video image processing." Thesis, University of Sheffield, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.306374.

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Zhang, Xiaowei. "Pedestrian flow measurement using image processing techniques." Thesis, Northumbria University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367418.

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Ikram, Waseem. "Traffic studies using imaging techniques." Thesis, University of Manchester, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.253750.

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Atiquzzaman, M. "Algorithms and architectures for automatic traffic analysis." Thesis, University of Manchester, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.378141.

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So, Wai-ki, and 蘇慧琪. "Shadow identification in traffic video sequences." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B32045967.

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Wiegand, Frank. "VLSI parallel processing in flow image based measurement." Thesis, University of Leeds, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.252932.

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Lorio, Berino. "Towards a non-intrusive traffic surveillance system using digital image processing." Thesis, Stellenbosch : Stellenbosch University, 2001. http://hdl.handle.net/10019.1/52589.

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Thesis (MScEng)--Stellenbosch University, 2001.<br>ENGLISH ABSTRACT: With the increased focus on the use of innovative and state-of-the-art technology in Intelligent Transport Systems (ITS), the need for more accurate and more detailed road traffic flow data has become apparent. Data obtained from vehicle detector loops, which merely act as vehicle presence sensors, is neither reliable nor accurate enough anymore. This type of sensor poses the problem that it has to be inserted into the road surface; temporarily obstructing traffic flows, and has to be replaced after pavement reconstruct

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Books on the topic "Traffic flow Image processing"

1

Dailey, Daniel J. Video image processing to create a speed sensor. Washington State Dept. of Transportation, 2000.

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Nihan, N. L. Improved error detection using prediction techniques and video imaging. Transportation Northwest, Dept. of Civil Engineering, University of Washington, 1995.

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Nihan, N. L. Video image processing for freeway monitoring and control: Evaluation of the Mobilizer. Washington State Dept. of Transportation, 1995.

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Dailey, Daniel J. TrafficTV, phase 2. Washington State Dept. of Transportation, 2006.

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Computer image processing in traffic engineering. Research Studies Press, 1991.

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Nieuwstadt, F. T. M. Flow Visualization and Image Analysis. Springer Netherlands, 1993.

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Keinert, Joachim. Design of Image Processing Embedded Systems Using Multidimensional Data Flow. Springer Science+Business Media LLC, 2011.

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Keinert, Joachim, and Jürgen Teich. Design of Image Processing Embedded Systems Using Multidimensional Data Flow. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-7182-1.

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Cunagin, Wiley D. Passer IV quick response procedures. Texas Transportation Institute, Texas A&M University, 1985.

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1951-, Bonsall P. W., and Young W. 1949-, eds. Understanding traffic systems: Data, analysis, and presentation. Ashgate, 2000.

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Book chapters on the topic "Traffic flow Image processing"

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Molnár, P., and T. R. Collins. "Traffic Data Collection Using Image Processing Technology." In Traffic and Granular Flow ’99. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-59751-0_35.

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Suzuno, Kohta, Akiyasu Tomoeda, Mayuko Iwamoto, and Daishin Ueyama. "Dynamic Structure in Pedestrian Evacuation: Image Processing Approach." In Traffic and Granular Flow '13. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10629-8_23.

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Lee, Tae-Seung, Eung-Min Lee, Hyeong-Taek Park, et al. "Implementation of Traffic Flow Measuring Algorithm Using Real-Time Dynamic Image Processing." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36592-3_8.

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Blosseville, Jean-Marc. "Image Processing for Traffic Management." In Advanced Video-Based Surveillance Systems. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5085-3_7.

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Kovalevsky, Vladimir. "Recognition of Bicycles in Traffic." In Modern Algorithms for Image Processing. Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-4237-7_13.

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Ballerini, Roberto, Luigi Cinque, Luca Lombardi, and Roberto Marmo. "Rectangular Traffic Sign Recognition." In Image Analysis and Processing – ICIAP 2005. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11553595_135.

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Marti, Fausto, and Maurizio Naldi. "Simulation of aircraft images for Airport Surface Traffic Control." In Image Analysis and Processing. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60298-4_333.

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Gła̧bowski, Mariusz, Sławomir Hanczewski, Maciej Stasiak, Michał Weissenberg, Piotr Zwierzykowski, and Vito Bai. "Traffic Modeling for Industrial Internet of Things (IIoT) Networks." In Image Processing and Communications. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31254-1_31.

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Pathan, Saira Saleem, and Klaus Richter. "Pedestrian Behavior Analysis in Crowds Using Image-Based Methods." In Traffic and Granular Flow '13. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10629-8_22.

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Hanczewski, Sławomir, Maciej Stasiak, and Joanna Weissenberg. "Model of a Multiservice Server with Stream and Elastic Traffic." In Image Processing and Communications. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31254-1_34.

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Conference papers on the topic "Traffic flow Image processing"

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Hashimoto, Toshiaki, and Shunji Murai. "Traffic flow measurement by video image processing." In Close-Range Photogrammetry Meets Machine Vision. SPIE, 1990. http://dx.doi.org/10.1117/12.2294346.

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Takatoo, Masao, Tadaaki Kitamura, Yoshiyuki Okuyama, et al. "Traffic Flow Measuring System Using Image Processing." In 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, edited by Michael J. W. Chen. SPIE, 1990. http://dx.doi.org/10.1117/12.969946.

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Lee, Joonsoo, and Alan C. Bovik. "Estimation and analysis of urban traffic flow." In 2009 16th IEEE International Conference on Image Processing ICIP 2009. IEEE, 2009. http://dx.doi.org/10.1109/icip.2009.5413520.

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Toropov, Evgeny, Liangyan Gui, Shanghang Zhang, Satwik Kottur, and Jose M. F. Moura. "Traffic flow from a low frame rate city camera." In 2015 IEEE International Conference on Image Processing (ICIP). IEEE, 2015. http://dx.doi.org/10.1109/icip.2015.7351516.

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Yawen, Yan, Chen Guojun, Yang Xiaoguang, and Wu Zhizhou. "Traffic Time-Intervals Split Based on the Traffic Flow Variation of Days of Week." In 2010 International Conference on Optoelectronics and Image Processing (ICOIP). IEEE, 2010. http://dx.doi.org/10.1109/icoip.2010.115.

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Yu, Dan, Zhixiang Hou, Huihua Yuan, and Xiaomei Yin. "Research on Chaos Characters of Velocity in Traffic Flow." In 2010 International Conference on Optoelectronics and Image Processing (ICOIP). IEEE, 2010. http://dx.doi.org/10.1109/icoip.2010.337.

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Toyama, M., T. Horiuchi, and Y. Shiina. "Development of a portable traffic flow measurement system using image processing." In Vehicle Navigation and Information Systems Conference, 1996. IEEE, 1996. http://dx.doi.org/10.1109/vnis.1996.1623734.

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Song, Jun Fang, A. Ning Bai, and Ru Xue. "A reliable counting vehicles method in traffic flow monitoring." In 2011 4th International Congress on Image and Signal Processing (CISP). IEEE, 2011. http://dx.doi.org/10.1109/cisp.2011.6099921.

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Fang, Yu, Jizhen Niu, and Fan Wang. "Application of Multi-scale Wavelet Kernel in Traffic Flow Forecasting." In 2010 International Conference on Optoelectronics and Image Processing (ICOIP). IEEE, 2010. http://dx.doi.org/10.1109/icoip.2010.197.

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Chai, Xiaoqi, Douglas Qian, Qinle Ba, Angran Li, Yongjie Jessica Zhang, and Ge Yang. "Image-based measurement of cargo traffic flow in complex neurite networks." In 2017 IEEE International Conference on Image Processing (ICIP). IEEE, 2017. http://dx.doi.org/10.1109/icip.2017.8296891.

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Reports on the topic "Traffic flow Image processing"

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Hanson, Ronald K. Advanced Flow Visualization and Image Processing Instrumentation. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada224574.

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Miles, Richard B. Development of Pulse-Burst Laser Source and Digital Image Processing for Measurements of High-Speed, Time-Evolving Flow. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada381328.

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Miles, Richard B. AASERT: Development of Pulse-Burst Laser Source and Digital Image Processing for Measurements of High-Speed, Time-Evolving Flow. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada383154.

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