Implementation of Licensed Plate Detection and Noise Removal in Image Processing

Yiquan Gao

cs.CVMar 1, 2026

Implementation of Licensed Plate Detection and Noise Removal in Image Processing

Authors: Yiquan Gao

Organizations: BSc (Hons) in Intelligent Systems, Asia Pacific University, Malaysia

Abstract

Car license plate recognition system is an image processing technology used to identify vehicles by capturing their Car License Plates. The car license plate recognition technology is also known as automatic number-plate recognition, automatic vehicle identification, car license plate recognition or optical character recognition for cars. In Malaysia, as the number of vehicle is increasing rapidly nowadays, a pretty great number of vehicle on the road has brought about the considerable demands of car license plate recognition system. Car license plate recognition system can be implemented in electronic parking payment system, highway toll-fee system, traffic surveillance system and as police enforcement tools. Additionally, car license plate recognition system technology also has potential to be combined with various techniques in other different fields like biology, aerospace and so on to achieve the goal of solving some specialized problems.

Automatic License Plate Recognition

Automatic license plate recognition detects vehicle plates and reads their characters from images or video for traffic and access-control systems.

See all 21 papers

An Embedded Real-Time License Plate Recognition System for Complex Traffic Scenes
Jun 26, 2026Anuki Pasqual, Dulan Lokugeegana, Manimohan Thiriloganathan +3Quantization Automatic License Plate Recognition
The authors are with the Dept. of Electronic and Telecommunication Engineering, University of Moratuwa, Sri Lanka
Character Recognition of Nepali Number Plate
Jun 27, 2026Satyasa Khadka, Sandhya Baral, Sudip Tiwari +1Automatic License Plate Recognition Optical Character Recognition
Pulchowk Campus, Institute of Engineering, Lalitpur, Nepal1
A Robust Deep Learning Framework for Bangla License Plate Recognition Using YOLO and Vision-Language OCR
Mar 10, 2026Nayeb Hasin, Md. Arafath Rahman Nishat, Mainul Islam +2Automatic License Plate Recognition Object Detection
Department of Electrical and Electronic Engineering, Islamic University of Technology, Gazipur, Bangladesh · Department of Mechanical Engineering, Bangladesh University Of Engineering And Technology, Dhaka, Bangladesh

Jun 26, 2026J/K move · Enter open · S save

An Embedded Real-Time License Plate Recognition System for Complex Traffic Scenes

Anuki Pasqual, Dulan Lokugeegana, Manimohan Thiriloganathan, Nuthya Rathnayake+2

The authors are with the Dept. of Electronic and Telecommunication Engineering, University of Moratuwa, Sri Lanka

Quantization Automatic License Plate Recognition

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Vehicle license plate recognition is an integral component of intelligent transportation systems. In this work, we present an embedded real-time license plate recognition system customized for developing countries. We address the challenge of handling complex, unstructured traffic scenes with diverse vehicle types while implementing the system on an embedded platform for low-cost deployment. Our method consists of license plate detection on a multi-vehicle image, followed by character recognition on the detected license plates. Both steps use lightweight convolutional neural networks to balance accuracy and efficiency. We also introduce the SL-LPR dataset of Sri Lankan road images, which contains a variety of vehicle types and traffic conditions typically seen in developing countries. On this dataset, the license plate detection and character recognition models achieved 93.6% mAP and 87.88% accuracy, respectively, and were competitive against larger models on several public datasets. To achieve real-time performance in a resource-constrained embedded environment, we applied low-bitwidth quantization using the Brevitas library and implemented FPGA acceleration for the models using the FINN framework. The end-to-end system can operate at 11.5~FPS when implemented on the Xilinx Kria KV260 platform. These results demonstrate that our system is effective for real-time license plate recognition on an embedded device, even in complex traffic scenarios. The SL-LPR dataset is available for research use at: https://github.com/sl-lpr-uom/SL-LPR.git.

Abstract

Automatic License Plate Recognition

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