IDEAS home Printed from https://ideas.repec.org/a/abq/ijist1/v3y2022i5p166-176.html
   My bibliography  Save this article

Automatic Vehicle Number Plate Recognition Approach Using Color Detection Technique

Author

Listed:
  • Muhammad Ayaz

    (Department of Computer Science University of Science and Technology Bannu, Pakistan)

  • Dr. Said Khalid Shah

    (Department of Computer Science University of Science and Technology Bannu, Pakistan)

  • Dr. Muhammad Javed

    (Department of Computer Science University of Science and Technology Bannu, Pakistan)

  • Muhammad Assam

    (College of Computer Science and Technology Hangzhou 310027, China.)

  • Wasiat Khan

    (Department of Software Engineering, University of Science and Technology, Bannu, KP Pakistan)

  • Fahad Najeeb

    (Department of Computer Science University of Science and Technology Bannu, Pakistan)

Abstract

An Automatic Vehicle Number Plate Recognition System (AVNPR) is a key research area in image processing. Various techniques are developed and tested by researchers to improve the detection and recognition rate of AVNPR system but faced problems due to issues such as variation in format, lighting conditions, scales, and colors of number plates in different countries or states or even provinces of a country. Douglas Peucker Algorithm for shape approximation has been used in this research to detect the rectangular contours and the most prominent rectangular contour is extracted as a number plate (NP) and the connected component analysis is used to segment the characters followed by optical character recognition (OCR) to recognize the number plate characters. A custom dataset of 210 vehicle images with different colors at various distances and lighting conditions was used for the proposed method captured on my smart phone Galaxy J7 Model SM-j700F at roads and parking. The dataset contains various types of vehicles (i.e. Trucks, motorcars, mini-buses, tractors, pick-ups etc). The proposed method shows an average result of 95.5%. The novelty used in this method is that it works for different colors simultaneously because in Pakistan, several colors are used for vehicle NPs.

Suggested Citation

  • Muhammad Ayaz & Dr. Said Khalid Shah & Dr. Muhammad Javed & Muhammad Assam & Wasiat Khan & Fahad Najeeb, 2022. "Automatic Vehicle Number Plate Recognition Approach Using Color Detection Technique," International Journal of Innovations in Science & Technology, 50sea, vol. 3(5), pages 166-176, January.
    • Handle: RePEc:abq:ijist1:v:3:y:2022:i:5:p:166-176
    DOI: https://doi.org/10.33411/IJIST/2021030513
    as

    Download full text from publisher

    File URL: https://journal.50sea.com/index.php/IJIST/article/view/111/582
    Download Restriction: no
    File URL: https://journal.50sea.com/index.php/IJIST/article/view/111
    Download Restriction: no
    File URL: https://libkey.io/https://doi.org/10.33411/IJIST/2021030513?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    Number plate recognition; color detection; contours; HSV color format; Douglas Peucker Algorithm; optical character recognition (OCR);
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:abq:ijist1:v:3:y:2022:i:5:p:166-176. 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: Hafiz Haroon Ahmad, Iqra Nazeer (email available below). General contact details of provider: .

    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.