Recognition of Hybrid Graphic-Text License Plates

John Anthony C. Jose; Allysa Kate M. Brillantes; Elmer P. Dadios; Edwin Sybingco; Laurence A. Gan Lim; Alexis M. Fillone; Robert Kerwin C. Billones

doi:10.20965/jaciii.2021.p0416

Regular Papers

Recognition of Hybrid Graphic-Text License Plates

John Anthony C. Jose, Allysa Kate M. Brillantes, Elmer P. Dadios, Edwin Sybingco, Laurence A. Gan Lim, Alexis M. Fillone, Robert Kerwin C. Billones

Author information

Keywords: license plate detection, license plate recognition, multiple object tracking, ReID network

JOURNAL OPEN ACCESS

2021 Volume 25 Issue 4 Pages 416-422

DOI https://doi.org/10.20965/jaciii.2021.p0416

Details

Abstract

Most automatic license-plate recognition (ALPR) systems use still images and ignore the temporal information in videos. Videos provide rich temporal and motion information that should be considered during training and testing. This study focuses on creating an ALPR system that uses videos. The proposed system is comprised of detection, tracking, and recognition modules. The system achieved accuracies of 81.473% and 84.237% for license-plate detection and classification, respectively.

Corresponding author

Correction information

Funder information

1.Fund name: Philippine Council for Industry, Energy, and Emerging Technology Research and Development

2.Fund name: De La Salle University

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