Improving the License Plate Character Segmentation Using Naïve Bayesian Network

Abdenebi Rouigueb, Fethi Demim, Hadjira Belaidi, Ali Messaoui, Mohamed Benatia, Badis Djamaa

2023

Abstract

Character segmentation plays a pivotal role in automatic license plate recognition (ALPR) systems. Assuming that plate localization has been accurately performed in a preceding stage, this paper mainly introduces a character segmentation algorithm based on combining standard segmentation techniques with prior knowledge about the plate’s structure. We propose employing a set of relevant features on-demand to classify detected blocks into either character or noise and to refine the segmentation when necessary. We suggest using the na ı̈ve Bayesian network (NBN) classifier for efficient combination of selected features. Incrementally, one after one, high computational cost features are computed and involved only if the low-cost ones cannot decisively determine the class of a block. Experimental results on a sample of Algerian car license plates demonstrate the efficiency of the proposed algorithm. It is designed to be more generic and easily extendable to integrate other features into the process.

Paper Citation

in Harvard Style

Rouigueb A., Demim F., Belaidi H., Messaoui A., Benatia M. and Djamaa B. (2023). Improving the License Plate Character Segmentation Using Naïve Bayesian Network. In Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-670-5, SciTePress, pages 61-68. DOI: 10.5220/0012091500003543

in Bibtex Style

@conference{icinco23,
author={Abdenebi Rouigueb and Fethi Demim and Hadjira Belaidi and Ali Messaoui and Mohamed Benatia and Badis Djamaa},
title={Improving the License Plate Character Segmentation Using Naïve Bayesian Network},
booktitle={Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2023},
pages={61-68},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012091500003543},
isbn={978-989-758-670-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - Improving the License Plate Character Segmentation Using Naïve Bayesian Network
SN - 978-989-758-670-5
AU - Rouigueb A.
AU - Demim F.
AU - Belaidi H.
AU - Messaoui A.
AU - Benatia M.
AU - Djamaa B.
PY - 2023
SP - 61
EP - 68
DO - 10.5220/0012091500003543
PB - SciTePress