License plate localization based on Kapur optimal multilevel threshold

Nur Aliyatul Husna Bt Yahya, Siti Norul Huda Sheikh Abdullah, Abbas Salimi Bin Zaini, Mohd. Zamri Murah, Azizi Abdullah, Shariffpudin Basiron

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A license plate localization system is useful for many applications. Due to ambient of lighting in three distinct situation which are morning, afternoon and night causing difficulty to search optimum threshold value in each situation. This research uses global thresholding approach by using Kapur entropy multilevel threshold based on Patch-Levy Bees Algorithm (PLBA). As a result, the system properly localize and identify number plate in the image by using proposed segmentation image. From the experiment, proposed method are achieve accuracy rates to 67.68%, 90.71%, 24.34% respectively for morning, afternoon and night dataset.

Original languageEnglish
Title of host publicationProceedings of the 7th International Conference Confluence 2017 on Cloud Computing, Data Science and Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages77-81
Number of pages5
ISBN (Electronic)9781509035182
DOIs
Publication statusPublished - 7 Jun 2017
Event7th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2017 - Noida, Uttar Pradesh, India
Duration: 12 Jan 201713 Jan 2017

Other

Other7th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2017
CountryIndia
CityNoida, Uttar Pradesh
Period12/1/1713/1/17

Fingerprint

Image segmentation
Entropy
Lighting
Experiments
Localization
License
Experiment

Keywords

  • Image segmentation
  • License Plate Localization
  • Multilevel thresholding

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management

Cite this

Yahya, N. A. H. B., Sheikh Abdullah, S. N. H., Zaini, A. S. B., Murah, M. Z., Abdullah, A., & Basiron, S. (2017). License plate localization based on Kapur optimal multilevel threshold. In Proceedings of the 7th International Conference Confluence 2017 on Cloud Computing, Data Science and Engineering (pp. 77-81). [7943127] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CONFLUENCE.2017.7943127

License plate localization based on Kapur optimal multilevel threshold. / Yahya, Nur Aliyatul Husna Bt; Sheikh Abdullah, Siti Norul Huda; Zaini, Abbas Salimi Bin; Murah, Mohd. Zamri; Abdullah, Azizi; Basiron, Shariffpudin.

Proceedings of the 7th International Conference Confluence 2017 on Cloud Computing, Data Science and Engineering. Institute of Electrical and Electronics Engineers Inc., 2017. p. 77-81 7943127.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yahya, NAHB, Sheikh Abdullah, SNH, Zaini, ASB, Murah, MZ, Abdullah, A & Basiron, S 2017, License plate localization based on Kapur optimal multilevel threshold. in Proceedings of the 7th International Conference Confluence 2017 on Cloud Computing, Data Science and Engineering., 7943127, Institute of Electrical and Electronics Engineers Inc., pp. 77-81, 7th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2017, Noida, Uttar Pradesh, India, 12/1/17. https://doi.org/10.1109/CONFLUENCE.2017.7943127
Yahya NAHB, Sheikh Abdullah SNH, Zaini ASB, Murah MZ, Abdullah A, Basiron S. License plate localization based on Kapur optimal multilevel threshold. In Proceedings of the 7th International Conference Confluence 2017 on Cloud Computing, Data Science and Engineering. Institute of Electrical and Electronics Engineers Inc. 2017. p. 77-81. 7943127 https://doi.org/10.1109/CONFLUENCE.2017.7943127
Yahya, Nur Aliyatul Husna Bt ; Sheikh Abdullah, Siti Norul Huda ; Zaini, Abbas Salimi Bin ; Murah, Mohd. Zamri ; Abdullah, Azizi ; Basiron, Shariffpudin. / License plate localization based on Kapur optimal multilevel threshold. Proceedings of the 7th International Conference Confluence 2017 on Cloud Computing, Data Science and Engineering. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 77-81
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