# Automatic Number Plate Detection and Recognition System for Small-Sized Number Plates of Category L-Vehicles for Remote Emission Sensing Applications

**Authors:** Hafiz Hashim Imtiaz, Paul Schaffer, Paul Hesse, Martin Kupper, Alexander Bergmann

PMC · DOI: 10.3390/s25113499 · Sensors (Basel, Switzerland) · 2025-05-31

## TL;DR

This paper introduces a new automatic number plate recognition system for small vehicles like mopeds to help monitor road traffic emissions.

## Contribution

A novel ANPR system specifically designed for small-sized number plates of Category L vehicles is developed and tested in real-world conditions.

## Key findings

- The L-ANPR system achieved over 90% detection accuracy for license plates of Category L vehicles.
- Character recognition accuracy for small number plates exceeded 70%.
- The system was successfully implemented in multiple European cities for remote emission sensing.

## Abstract

Road traffic emissions are still a significant contributor to air pollution, which causes adverse health effects. Remote emission sensing (RES) is a state-of-the-art technique that continuously monitors the emissions of thousands of vehicles in traffic. Automatic number plate recognition (ANPR) systems are an essential part of RES systems to identify the registered owners of high-emitting vehicles. Recognizing number plates on L-vehicles (two-wheelers) with a standard ANPR system is challenging due to differences in size and placement across various categories. No ANPR system is designed explicitly for Category L vehicles, especially mopeds. In this work, we present an automatic number plate detection and recognition system for Category L vehicles (L-ANPR) specially developed to recognize L-vehicle number plates of various sizes and colors from different categories and countries. The cost-effective and energy efficient L-ANPR system was implemented on roads during remote emission measurement campaigns in multiple European cities and tested with hundreds of vehicles. The L-ANPR system recognizes Category L vehicles by calculating the size of each passing vehicle using photoelectric sensors. It can then trigger the L-ANPR detection system, which begins detecting license plates and recognizing license plate numbers with the L-ANPR recognizing system. The L-ANPR system’s license plate detection model is trained using thousands of images of license plates from various types of Category L vehicles across different countries, and the overall detection accuracy with test images exceeded 90%. The L-ANPR system’s character recognition is designed to identify large characters on standard number plates as well as smaller characters in various colors on small, moped license plates, achieving a recognition accuracy surpassing 70%. The reasons for false recognitions are identified and the solutions are discussed in detail.

## Full-text entities

- **Genes:** METTL13 (methyltransferase 13, eEF1A N-terminus and K55) [NCBI Gene 51603] {aka 5630401D24Rik, CGI-01, DFNB26, DFNB26M, DFNM1, EEF1AKNMT}
- **Diseases:** GS (MESH:D005736), injury to (MESH:D014947)
- **Chemicals:** Pi (MESH:D010716), L-ANPR (-), L (MESH:D007930), CO2 (MESH:D002245)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

25 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12158335/full.md

## References

49 references — full list in the complete paper: https://tomesphere.com/paper/PMC12158335/full.md

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Source: https://tomesphere.com/paper/PMC12158335