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Vehicle Number Plate Detection: An Edge Image Based Approach

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Progress in Advanced Computing and Intelligent Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1198))

Abstract

Transportation system (vehicle communication) plays a major role in today’s scenario. Detection of vehicle number plate exactly in blurry conditions was the most challenging issue found in the last three decades. Although many intensive studies were undertaken, none addressed this problem exhaustively. Various methods are introduced by several researchers for detecting the vehicle number from the vehicle number plate images. The purpose of this study was to investigate this current issue by implementing an edge-based approach on the basis of quantitative combination of Canny, Morphological and Sobel methods for the accurate detection of vehicle number in blurry conditions. The experimental results demonstrated that the proposed scheme outperforms its counterparts in terms of Sobel, Prewitt, Roberts, Laplacian of Gaussian (LoG), Morphological and Canny methods in all aspects with higher peak signal to noise ratio (PSNR) and signal to noise ratio (SNR) values. Hence, the proposed hybrid scheme is better and robust and results in accurate estimation of vehicle number from the blurry vehicle number plate (BVNP) images for the given datasets.

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Author information

Authors and Affiliations

  1. Utkal University, Bhubaneswar, India

    Kalyan Kumar Jena

  2. Amity School of Engineering and Technology, Amity University Noida, Noida, Uttar Pradesh, India

    Soumya Ranjan Nayak

  3. Department of Computer Science Engineering and Applications, Indira Gandhi Institute of Technology, Sarang, India

    Kalyan Kumar Jena, Sasmita Mishra & Sarojananda Mishra

  4. Department of Computer Science and Engineering, Parala Maharaja Engineering College, Berhampur, India

    Kalyan Kumar Jena

Authors
  1. Kalyan Kumar Jena
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  2. Soumya Ranjan Nayak
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  3. Sasmita Mishra
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  4. Sarojananda Mishra
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Corresponding author

Correspondence to Soumya Ranjan Nayak .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Rama Devi Women’s University, Bhubaneswar, Odisha, India

    Chhabi Rani Panigrahi

  2. Department of Computer Science, Rama Devi Women’s University, Bhubaneswar, Odisha, India

    Bibudhendu Pati

  3. Department of Computer Science, University of California, Davis, CA, USA

    Prasant Mohapatra

  4. Cloud Computing and Distributed Systems (CLOUDS) Laboratory, School of Computing and Information Systems, University of Melbourne, Melbourne, VIC, Australia

    Rajkumar Buyya

  5. Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan

    Kuan-Ching Li

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Cite this paper

Jena, K.K., Nayak, S.R., Mishra, S., Mishra, S. (2021). Vehicle Number Plate Detection: An Edge Image Based Approach. In: Panigrahi, C.R., Pati, B., Mohapatra, P., Buyya, R., Li, KC. (eds) Progress in Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 1198. Springer, Singapore. https://doi.org/10.1007/978-981-15-6584-7_3

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  • DOI: https://doi.org/10.1007/978-981-15-6584-7_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-6583-0

  • Online ISBN: 978-981-15-6584-7

  • eBook Packages: EngineeringEngineering (R0)

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