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An Improved Intelligent Transportation System: An Approach for Bilingual License Plate Recognition

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Information and Communication Technology for Intelligent Systems

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 107))

Abstract

An intelligent transportation system (ITS) is the leading-edge technology that is used to control the traffic and prevent the rule violators. The ITS systems are equipped with an automatic number plate recognition (ANPR) techniques which recognize the license plate of the vehicles. This paper proposes an approach for Hindi license plate recognition and extends the ability of ITS systems. In the proposed approach, connected component labeling is used for character segmentation and histograms of oriented gradient (HOG) features are used to classify the Hindi characters. We propose an integrated classification model for character classification. To classify the alphabets and numerals, a ANN model is designed and trained for datasets. The approach segments the characters with 100% accuracy, and average accuracy of the classification model is 96.7%.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Banasthali University, Banasthali, Jaipur, India

    Nikita Singh

  2. Department of Computer Science and Engineering, Government Engineering College Bikaner, Bikaner, India

    Tarun Kumar

Authors
  1. Nikita Singh
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  2. Tarun Kumar
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Corresponding author

Correspondence to Nikita Singh .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, India

    Suresh Chandra Satapathy

  2. Sabar Institute of Technology, Gujarat Technological University, Ahmedabad, Gujarat, India

    Amit Joshi

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Singh, N., Kumar, T. (2019). An Improved Intelligent Transportation System: An Approach for Bilingual License Plate Recognition. In: Satapathy, S., Joshi, A. (eds) Information and Communication Technology for Intelligent Systems . Smart Innovation, Systems and Technologies, vol 107. Springer, Singapore. https://doi.org/10.1007/978-981-13-1747-7_4

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