IDEAS home Printed from https://ideas.repec.org/a/alk/jcsts0/v2y2020i1id68.html

Automated Traffic Detection System Based on Image Processing

Author

Listed:
  • Fahad Faisal

    (Department of Computer Science and Engineering, Daffodil international University, Dhaka 1207, Bangladesh)

  • Sumon Kumar Das

    (Department of Computer Science and Engineering, Daffodil international University, Dhaka 1207, Bangladesh)

  • Abdul Hasib Siddique

    (Department of Electrical and Electronic Engineering, University of Science and Technology Chittagong, Chattogram 4202, Bangladesh)

  • Mehedi Hasan

    (Department of Electrical and Electronic Engineering, University of Science and Technology Chittagong, Chattogram 4202, Bangladesh)

  • Samia Sabrin

    (Department of Electrical and Electronic Engineering, Chittagong University of Engineering and Technology, Chattogram 4349, Bangladesh)

  • Chowdhury Akram Hossain

    (Department of Electrical and Electronic Engineering, American International University-Bangladesh, Dhaka 1212, Bangladesh)

  • Zhou Tong

    (College of Engineering, IT and Environment, Charles Darwin University, NT 0810, Australia)

Abstract

This paper proposes a low-cost automated traffic detection system based on image processing. Dhaka is one of the crowded cities in the world with highly challenging traffic system. There is substantial lack of awareness among the drivers of transport system. As a result, citizens do not follow the rules and regulation while driving in Dhaka city. The tendency of violating the traffic regulation is noticeable throughout the country. As a result, the whole traffic system collapses very often and sometimes it ends-up with severe accidents. In recent days, the government has taken different initiatives including enlargement of pedestrian walkways, building new flyovers and foot-over bridges, expansion of existing roads. But, violation still the outcome of all these initiatives could not improve the situation significantly. The proposed system will automatically detect the traffic through live streaming video so that the detected images can be used to detect traffic violation. Later on, the law enforcement agency will be able to take necessary legal steps based on the stored information on the database.

Suggested Citation

  • Fahad Faisal & Sumon Kumar Das & Abdul Hasib Siddique & Mehedi Hasan & Samia Sabrin & Chowdhury Akram Hossain & Zhou Tong, 2020. "Automated Traffic Detection System Based on Image Processing," Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 2(1), pages 18-25, June.
    • Handle: RePEc:alk:jcsts0:v:2:y:2020:i:1:id:68
    as

    Download full text from publisher

    File URL: https://al-kindipublisher.com/index.php/jcsts/article/view/68
    File Function: Abstract page
    Download Restriction: no
    File URL: https://al-kindipublisher.com/index.php/jcsts/article/download/68/71
    File Function: Full text
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:alk:jcsts0:v:2:y:2020:i:1:id:68. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Al-Kindi Center for Research and Development (email available below). General contact details of provider: https://al-kindipublisher.com/index.php/jcsts .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.