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Tay Eng Liang
Intel Microelectronics (M) Sdn. Bhd
Electrical & Electronics Engineering

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Malaysian car plate localization using region-based convolutional neural network Tay Eng Liang; Usman Ullah Sheikh; Mohd Norzali Haji Mohd
Bulletin of Electrical Engineering and Informatics Vol 9, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (439.703 KB) | DOI: 10.11591/eei.v9i1.1862

Abstract

Automatic car plate localization and recognition system is a system that identifies the car plate location and recognizes the characters on the car plate input images. Within the automated system, the car plate localization stage is the first stage and is the most crucial stage as the success rate of the whole system depends heavily on it. In this paper, a Malaysian car plate localization system using Region-based Convolutional Neural Network (R-CNN) is proposed. Using transfer learning on the AlexNet CNN, the localization was greatly improved achieving best precision and recall rate of 95.19% and 97.84% respectively. Besides, the proposed R-CNN was able to localize car plates in complex scenarios such as under occlusion.
Co-Authors Mohd Norzali Haji Mohd Usman Ullah Sheikh