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Toward Robust Image Pre-processing Steps for Vehicle Plate Recognition

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Third International Conference on Image Processing and Capsule Networks (ICIPCN 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 514))

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Abstract

Generally, improving the quality of vehicle plate images has proved to be the key of obtaining a promising recognition accuracy rate. Therefore, researchers tend to revisit related works with the intention to add some new image pre-processing steps in attempting to improve their current results. In this paper, a new version of previous recognition approach is introduced where more attention to image pre-processing steps is given. Firstly, an illustration of a new skew detection and fixing technique is provided. Then, a coherent overview of the previous approach, after adding the new steps, is firmly defined using pseudocode. For evaluation, experiments conduct using standard vehicle plates datasets. Promising results is obtained.

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Author information

Authors and Affiliations

  1. IT Faculty, Computer Science Department, University of Benghazi, Benghazi, Libya

    Mohamed Alkalai

Authors
  1. Mohamed Alkalai
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Corresponding author

Correspondence to Mohamed Alkalai .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Da-Yeh University, Changhua, Taiwan

    Joy Iong-Zong Chen

  2. Departamento de Engenharia Mecânica, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal

    João Manuel R. S. Tavares

  3. Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA

    Fuqian Shi

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Alkalai, M. (2022). Toward Robust Image Pre-processing Steps for Vehicle Plate Recognition. In: Chen, J.IZ., Tavares, J.M.R.S., Shi, F. (eds) Third International Conference on Image Processing and Capsule Networks. ICIPCN 2022. Lecture Notes in Networks and Systems, vol 514. Springer, Cham. https://doi.org/10.1007/978-3-031-12413-6_8

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