An Obstacle Detection Scheme for Vehicles in an Intelligent Transportation System

An Obstacle Detection Scheme for Vehicles in an Intelligent Transportation System

Автор: Vidhi R. Shah, Sejal V. Maru, Rutvij H. Jhaveri

Журнал: International Journal of Computer Network and Information Security(IJCNIS) @ijcnis

Статья в выпуске: 10 vol.8, 2016 года.

Бесплатный доступ

Road obstacles cause serious accidents that have a severe impact on driver safety, traffic flow efficiency and damage of the vehicle. Detecting obstacles are important to prevent or to reduce such kind of the accidents and fatalities. However, it is difficult and becomes tricky because of some problems like presence of shadow, environmental changes or a sudden action of any moving things (e.g., car overtaking, animal coming) and many more. Thereby, this paper aims to design an obstacle detection technique based on (i) moving cameras and (ii) moving objects. These methods are applied to obstacle detection phase, in order to identify the different obstacles (e.g., potholes, animals, stop sign, obstacles, bumps, road cracks) by considering road dimensions. A new technique is introduced for detecting obstacles from moving camera and moving objects which overcomes several limitations over stationary cameras and moving/stationary objects. Further, paper reviews recent research trends to detect obstacles for moving cameras and moving objects with discussion of key points and limitations of each approach. Finally, the results show that the proposed method is more robust and reliable than the previous approaches based on the stationary cameras.

Еще

Image Processing, Obstacle Detection, Intelligent Transportation System, Safety, VANET (Vehicular Ad-hoc Network)

Короткий адрес: https://sciup.org/15011591

IDR: 15011591

Список литературы An Obstacle Detection Scheme for Vehicles in an Intelligent Transportation System

  • Zhihu Wang; Kai Liao; JiulongXiong; Qi Zhang, "Moving Object Detection Based on Temporal Information," Signal Processing Letters, EEE, vol.21, no.11, pp.1403,1407, Nov. 2014.
  • Bhaskar, P.K.; Suet-Peng Yong, "Image processing based vehicle detection and tracking method," Computer and Information Sciences(ICCOINS), 2014 International Conference on , vol., no., pp.1,5, 3-5June 2014.
  • Dong, Xia, Kedian Wang, and GuohuaJia. "Moving object and shadow detection based on RGB color space and edge ratio." In Image andSignal Processing, 2009.CISP'09.2nd International Congress on, pp. 1- 5.IEEE, 2009.
  • Gang, Liu, NingShangkun, You Yugan, Wen Guanglei, and ZhengSiguo. "An improved moving objects detection algorithm." In WaveletAnalysis and Pattern Recognition (ICWAPR), 2013 International Conference on, pp. 96-102. IEEE, 2013.
  • Hassannejad, Hamid, Paolo Medici, Elena Cardarelli, and PietroCerri. "Detection of moving objects in roundabouts based on a monocularsystem." Expert Systems with Applications 42, no. 9 (2015): 4167-4176.
  • Choi, JinMin, Hyung Jin Chang, Yung Jun Yoo, and Jin Young Choi. "Robust moving object detection against fast illumination change."Computer Vision and Image Understanding 116, no. 2 (2012): 179-193.
  • Patel, Chirag, Atul Patel, and Dipti Shah. "A Novel Approach for Detecting Number Plate Based on Overlapping Window and RegionClustering for Indian Conditions." (2015).
  • Olaverri-Monreal, Cristina, Pedro Gomes, Ricardo Fernandes, Fausto Vieira, and Michel Ferreira. "The See-Through System: A VANETenabled assistant for overtaking maneuvers." In Intelligent VehiclesSymposium (IV), 2010 IEEE, pp. 123-128.IEEE, 2010.
  • Zhang, Huijuan, and Hanmei Zhang. "A moving target detectionalgorithm based on dynamic scenes." In Computer Science & Education(ICCSE), 2013 8th International Conference on, pp. 995-998. IEEE,2013.
  • Xiang, Jinhai, Heng Fan, Honghong Liao, Jun Xu, Weiping Sun, andShengsheng Yu. "Moving Object Detection and Shadow Removingunder Changing Illumination Condition."Mathematical Problems inEngineering 2014 (2014).
  • Kanungo, Anurag, Ashok Sharma, and ChetanSingla. "Smart trafficlights switching and traffic density calculation using video processing."In Engineering and Computational Sciences (RAECS), 2014 RecentAdvances in, pp. 1-6. IEEE, 2014.
  • Gomes, Pedro, Cristina Olaverri-Monreal, and Michel Ferreira. "Makingvehicles transparent through V2V video streaming."IntelligentTransportation Systems, IEEE Transactions on 13, no. 2 (2012): 930-938.
  • Toth, Stefan, Jan Janech, and Emil r k. uery Based ImageProcessing in the VANET." In Computational Intelligence, Communication Systems and Networks (CICSyN), 2013 FifthInternational Conference on, pp. 256-260. IEEE, 2013.
  • Badura, Stefan, and Anton Lieskovsky. "Intelligent traffic system:Cooperation of MANET and image processing." In IntegratedIntelligent Computing (ICIIC), 2010 First International Conference on, pp. 119-123. IEEE, 2010.
  • Hao, JiuYue, Chao Li, Zuwhan Kim, and Zhang Xiong. "Spatiotemporaltraffic scene modeling for object motion detection."IntelligentTransportation Systems, IEEE Transactions on 14, no. 1 (2013): 295-302.
  • A. P. Shukla and Mona Saini, "Moving Object Tracking of VehicleDetection" International Journal of Signal Processing, Image Processingand Pattern Recognition Vol.8, No.3 , 2015.
  • Shahare, Dipali, and RanjanaShende. "Moving Object Detection withFixed Camera and Moving Camera for Automated VideoAnalysis." International Journal of Computer Applications Technologyand Research 3, no. 5 (2014): 277-283.
  • Labayrade, Raphael, Didier Aubert, and Jean-Philippe Tarel. "Real time obstacle detection in stereovision on non flat road geometry through" vdisparity" representation."In Intelligent Vehicle Symposium, 2002. IEEE, vol. 2, pp. 646-651. IEEE, 2002.
  • Byun, Jaemin, Ki-in Na, Beom-suSeo, and MyungchanRoh. "Drivable Road Detection with 3D Point Clouds Based on the MRF for Intelligent Vehicle." InField and Service Robotics, pp. 49-60. Springer International publishing, 2015.
  • Kaur, Amandeep, and Tanupreet Singh. "A Comparative Analysis of Lane Detection Techniques."International Journal of ComputerApplications 112, no. 3 (2015).
  • Bello-Salau, H., A. M. Aibinu, E. N. Onwuka, J. J. Dukiya, and A. J. Onumanyi. "Image processing techniques for automated road defectdetection: A survey." In Electronics, Computer and Computation (ICECCO), 2014 11th International Conference on, pp. 1-4.IEEE, 2014.
  • Ding, Feng, Yibing Zhao, Lie Guo, Mingheng Zhang, and LinhuiLi."Obstacle Detection in Hybrid Cross-Country Environment Based onMarkov Random Field for Unmanned Ground Vehicle." Discrete Dynamics in Nature and Society2015 (2015).
  • Aly, Mohamed. "Real time detection of lane markers in urban streets." In Intelligent Vehicles Symposium, 2008 IEEE, pp. 7-12. IEEE, 2008.
  • Boroujeni, NasimSepehri, S. Ali Etemad, and Anthony Whitehead. "Fast obstacle detection using targeted optical flow." In Image Processing (ICIP), 2012 19th IEEE International Conference on, pp. 65-68. IEEE, 2012.
  • MATLAB and Statistics Toolbox Release 2012b, TheMathWorks, I nc., Natick, Massachusetts, United States.
  • Viola–Jones object detection framework. (2016, February 26). In Wikipedia, The Free Encyclopedia. Retrieved 12:40, March 25, 2016, from https://en.wikipedia.org/w/index.php?title=Viola%E2%80%93Jones_object_detection_framework&oldid=707070330
  • P. Viola and M. Jones, "Rapid object detection using a boosted cascade of simple features," Computer Vision and Pattern Recognition, 2001.CVPR 2001.Proceedings of the 2001 IEEE Computer Society Conference on, 2001, pp. I-511-I-518 vol.1. doi: 10.1109/CVPR.2001.990517.
Еще
Статья научная
QR-код для установки приложения SciUp Наведите камеру и скачайте бесплатное приложение SciUp