Improved Automatic License Plate Recognition in Jordan Based on Ceiling Analysis

The main challenge of automatic license plate recognition (ALPR) systems is that the overall performance is highly dependent upon the results of each component in the system’s pipeline. This paper proposes an improved ALPR system for the Jordanian license plates. Ceiling analysis is carried out to i...

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Autores principales:	Musa Al-Yaman, Haneen Alhaj Mustafa, Sara Hassanain, Alaa Abd AlRaheem, Adham Alsharkawi, Majid Al-Taee
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	character recognition character segmentation intelligent transport system license plate recognition machine learning neural networks Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/0d3e6e7bf58349e99806daf6e5ce99b6
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id	oai:doaj.org-article:0d3e6e7bf58349e99806daf6e5ce99b6
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spelling	oai:doaj.org-article:0d3e6e7bf58349e99806daf6e5ce99b62021-11-25T16:33:12ZImproved Automatic License Plate Recognition in Jordan Based on Ceiling Analysis10.3390/app1122106142076-3417https://doaj.org/article/0d3e6e7bf58349e99806daf6e5ce99b62021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10614https://doaj.org/toc/2076-3417The main challenge of automatic license plate recognition (ALPR) systems is that the overall performance is highly dependent upon the results of each component in the system’s pipeline. This paper proposes an improved ALPR system for the Jordanian license plates. Ceiling analysis is carried out to identify potential enhancements in each processing stage of a previously reported ALPR system. Based on the obtained ceiling analysis results, several enhancements are then suggested to improve the overall performance of the system under study. These improvements are (i) vertical-edge histogram analysis and size estimation of the candidate regions in the detection stage and (ii) de-rotation of the misaligned license plate images in the segmentation unit. These enhancements have resulted in significant improvements in the overall system performance despite a <1% increase in the execution time. The performance of the developed ALPR is assessed experimentally using a dataset of 500 images for parked and moving vehicles. The obtained results are found to be superior to those reported in equivalent systems, with a plate detection accuracy of 94.4%, character segmentation accuracy of 91.9%, and character recognition accuracy of 91.5%.Musa Al-YamanHaneen Alhaj MustafaSara HassanainAlaa Abd AlRaheemAdham AlsharkawiMajid Al-TaeeMDPI AGarticlecharacter recognitioncharacter segmentationintelligent transport systemlicense plate recognitionmachine learningneural networksTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10614, p 10614 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	character recognition character segmentation intelligent transport system license plate recognition machine learning neural networks Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	character recognition character segmentation intelligent transport system license plate recognition machine learning neural networks Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Musa Al-Yaman Haneen Alhaj Mustafa Sara Hassanain Alaa Abd AlRaheem Adham Alsharkawi Majid Al-Taee Improved Automatic License Plate Recognition in Jordan Based on Ceiling Analysis
description	The main challenge of automatic license plate recognition (ALPR) systems is that the overall performance is highly dependent upon the results of each component in the system’s pipeline. This paper proposes an improved ALPR system for the Jordanian license plates. Ceiling analysis is carried out to identify potential enhancements in each processing stage of a previously reported ALPR system. Based on the obtained ceiling analysis results, several enhancements are then suggested to improve the overall performance of the system under study. These improvements are (i) vertical-edge histogram analysis and size estimation of the candidate regions in the detection stage and (ii) de-rotation of the misaligned license plate images in the segmentation unit. These enhancements have resulted in significant improvements in the overall system performance despite a <1% increase in the execution time. The performance of the developed ALPR is assessed experimentally using a dataset of 500 images for parked and moving vehicles. The obtained results are found to be superior to those reported in equivalent systems, with a plate detection accuracy of 94.4%, character segmentation accuracy of 91.9%, and character recognition accuracy of 91.5%.
format	article
author	Musa Al-Yaman Haneen Alhaj Mustafa Sara Hassanain Alaa Abd AlRaheem Adham Alsharkawi Majid Al-Taee
author_facet	Musa Al-Yaman Haneen Alhaj Mustafa Sara Hassanain Alaa Abd AlRaheem Adham Alsharkawi Majid Al-Taee
author_sort	Musa Al-Yaman
title	Improved Automatic License Plate Recognition in Jordan Based on Ceiling Analysis
title_short	Improved Automatic License Plate Recognition in Jordan Based on Ceiling Analysis
title_full	Improved Automatic License Plate Recognition in Jordan Based on Ceiling Analysis
title_fullStr	Improved Automatic License Plate Recognition in Jordan Based on Ceiling Analysis
title_full_unstemmed	Improved Automatic License Plate Recognition in Jordan Based on Ceiling Analysis
title_sort	improved automatic license plate recognition in jordan based on ceiling analysis
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/0d3e6e7bf58349e99806daf6e5ce99b6
work_keys_str_mv	AT musaalyaman improvedautomaticlicenseplaterecognitioninjordanbasedonceilinganalysis AT haneenalhajmustafa improvedautomaticlicenseplaterecognitioninjordanbasedonceilinganalysis AT sarahassanain improvedautomaticlicenseplaterecognitioninjordanbasedonceilinganalysis AT alaaabdalraheem improvedautomaticlicenseplaterecognitioninjordanbasedonceilinganalysis AT adhamalsharkawi improvedautomaticlicenseplaterecognitioninjordanbasedonceilinganalysis AT majidaltaee improvedautomaticlicenseplaterecognitioninjordanbasedonceilinganalysis
_version_	1718413118848106496

Improved Automatic License Plate Recognition in Jordan Based on Ceiling Analysis

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