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Reseach Article

An Automatic Number Plate Recognition System using OpenCV and Tesseract OCR Engine

by Andrew S. Agbemenu, Jepthah Yankey, Ernest O. Addo
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 43
Year of Publication: 2018
Authors: Andrew S. Agbemenu, Jepthah Yankey, Ernest O. Addo
10.5120/ijca2018917150

Andrew S. Agbemenu, Jepthah Yankey, Ernest O. Addo . An Automatic Number Plate Recognition System using OpenCV and Tesseract OCR Engine. International Journal of Computer Applications. 180, 43 ( May 2018), 1-5. DOI=10.5120/ijca2018917150

@article{ 10.5120/ijca2018917150,
author = { Andrew S. Agbemenu, Jepthah Yankey, Ernest O. Addo },
title = { An Automatic Number Plate Recognition System using OpenCV and Tesseract OCR Engine },
journal = { International Journal of Computer Applications },
issue_date = { May 2018 },
volume = { 180 },
number = { 43 },
month = { May },
year = { 2018 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number43/29416-2018917150/ },
doi = { 10.5120/ijca2018917150 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:03:27.379861+05:30
%A Andrew S. Agbemenu
%A Jepthah Yankey
%A Ernest O. Addo
%T An Automatic Number Plate Recognition System using OpenCV and Tesseract OCR Engine
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 43
%P 1-5
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Automatic Number Plate Recognition (ANPR) is a fairly well explored problem with many successful solutions. However, these solutions are typically tuned towards a particular environment due to the variations in the features of number plates across the world. Algorithms written for number plate recognition are based on these features and so a universal solution would be difficult to realize as the image analysis techniques that are used to build these algorithms cannot themselves boast hundred percent accuracy. The focus of this paper is a proposed algorithm that is optimized to work with Ghanaian vehicle number plates. The algorithm, written in C++ with the OpenCV library, uses edge detection and Feature Detection techniques combined with mathematical morphology for locating the plate. The Tesseract OCR engine was then used to identify the detected characters on the plate.

References
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Index Terms

Computer Science
Information Sciences

Keywords

OpenCV edge detection template matching morphology Tesseract OCR engine