Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Dec 5:33:106554.
doi: 10.1016/j.dib.2020.106554. eCollection 2020 Dec.

Artificial Mercosur license plates dataset

Affiliations

Artificial Mercosur license plates dataset

Gilles Velleneuve Trindade Silvano et al. Data Brief. .

Abstract

Mercosur (a.k.a. Mercosul) is a trade bloc comprising five South American countries. In 2018, a unified Mercosur license plate model was rolled out. Access to large volumes of ground truth Mercosur license plates with sufficient presentation variety is a significant challenge for training supervised models for license plate detection (LPD) in automatic license plate recognition (ALPR) systems. To address this problem, a Mercosur license plate generator was developed to generate artificial license plate images meeting the new standard with sufficient variety for ALPR training purposes. This includes images with variation due to occlusions and environmental conditions. An embedded system was developed for detecting legacy license plates in images of real scenarios and overwriting these with artificially generated Mercosur license plates. This data set comprises 3,829 images of vehicles with synthetic license plates that meet the new Mercosur standard in real scenarios, and equivalent number of text files containing label information for the images, all organized in a CSV file with compiled image file paths and associated labels.

Keywords: Automated license plate recognition license; Deep Learning; License plates images; Mercosur license plates; Number Plate Detection; Plate detection; Smart Cities; Synthetic Data.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that have, or could be perceived to have, influenced the work reported in this article.

Figures

Fig 1
Fig. 1
Overview of the proposed methodology.
Fig 2
Fig. 2
Types of artificial shading.
Fig 3
Fig. 3
Scenario with inclined license plate.

References

    1. Ribeiro V., Greati V., Bezerra A., Silvano G., Silva I., Endo P.T., Lynn T. 2019 IX Brazilian Symposium On Computing Systems Engineering (SBESC) IEEE; 2019. Brazilian mercosur license plate detection: a deep learning approach relying on synthetic imagery; pp. 1–8.
    1. J. Redmon, A. Farhadi, Yolov3: an incremental improvement, arXiv preprint arXiv:1804.02767.
    1. G. Bradski, The OpenCV library, Dr. Dobb's J Software Tools.
    1. OpenCV, Opencv modules, available online: https://docs.opencv.org/4.1.0/ (accessed on 30 June 2019) (Apr 2019).
    1. J. Redmon, Darknet: open source neural networks in C, Available online: http://pjreddie.com/darknet/ (accessed on 30 June 2019) (2013–2016).

LinkOut - more resources