Computer Vision Based Pothole Detection and Notification

  • Abstract
  • Keywords
  • References
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  • Abstract

    Potholes on the road cause accidents and lead to traffic congestion. If left unresolved, the damage worsens and time taken to fix it also increases. We aim to develop an automated pothole detection and alert system which can detect potholes and also its location. In this paper, we propose a prototype for a computer vision based pothole detection system. Blob detection is used where the potholes are    assumed to be a blob. The potholes are determined by the algorithm that is embedded in the Pi, which captures live images using the Pi camera. The OpenCV library is utilized for accomplishing the detection.


  • Keywords

    Blob detection; Computer vision; GPS; Pi camera; Potholes; Raspberry Pi

  • References

      [1] Nienaber S, Booysen M and Kroon R, “Detecting Potholes Using Simple Image Processing Techniques And Real-World Footage”, Proceedings of the 34th Southern African Transport Conference (SATC 2015), Pretoria (South Africa), July 9th, 2015, pp. 153-164.

      [2] CSIR, 2010, “Potholes: Technical guide to their causes, identification and repair”.

      [3] S. Pawade, B. P. Fuladi, L. A. Hundikar, “FPGA Based Intelligent Potholes Detection”, International Journal of Innovative Research in Computer and Communication Engineering, Vol. 3, No. 3, 2015, pp.2285–2290.

      [4] G. D. De Silva, R. S. Parera, N. M. Laxman, K.M., “Automated Pothole Detection System”, Proceedings of the International Conference on Advances in ICT for Emerging Regions (ICTer), IEEE Sri Lanka Section C Chapter (Sri Lanka), 11–15 December, 2013.

      [5] Mednis, G. Strazdins, R. Zviedris, G, “Real Time Pothole Detection Using Android Smartphones With Accelerometers”, Proceedings of the International Conference on Distributed Computing in Sensor Systems and Workshops (DCOSS), IEEE (Spain), 27–29 June, 2011, pp. 1–6.

      [6] Z. Zhang, X. Ai, C. K. Chan, N. Dahnoun, “An Efficient Algorithm for Pothole Detection Using Stereo Vision”, Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE (Italy), 4-9 May, 2014, pp. 564–568.




Article ID: 22684
DOI: 10.14419/ijet.v7i3.24.22684

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