research-article

Thermal-image processing and statistical analysis for vehicle category in nighttime traffic

Authors:

Apiwat Sangnoree,

Kosin ChamnongthaiAuthors Info & Claims

Journal of Visual Communication and Image Representation, Volume 48, Issue C

Pages 88 - 109

https://doi.org/10.1016/j.jvcir.2017.06.006

Published: 01 October 2017 Publication History

Abstract

The automatic tollgate at highway entrance and exit needs to categorize vehicle in order to collect highway passing fee especially at night time. This paper proposes a method of vehicle categorization in nighttime traffic using thermal-image processing and statistical analysis. To recognize the vehicular types, statistical relation between thermal features of engine heat, windscreen and others are utilized in this method. Firstly, appropriate threshold values for classifying the thermal features are automatically determined, entire area of the thermal image is then divided into blocks, and thermal features classified in all blocks by the threshold values are finally integrated for vehicle type categorization. To evaluate the performance of proposed method, experiments with 2937 samples of cars, vans and trucks are categorized, and the results approximately reveal 95.51% accuracy.

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Cited By

Gu ZLei YChan SCao DZhang K(2022)Traffic Incident Detection System Based on Video AnalysisProceedings of the 2022 5th International Conference on Computational Intelligence and Intelligent Systems10.1145/3581792.3581795(15-20)Online publication date: 4-Nov-2022
https://dl.acm.org/doi/10.1145/3581792.3581795
Lin WDeng ZLi XWang KYang YJin B(2017)RETRACTED ARTICLE: Discrete Noetherian ring variational pattern feature sets for space-air-ground network protocol monitoringCluster Computing10.1007/s10586-017-1440-022:Suppl 4(7805-7814)Online publication date: 8-Dec-2017
https://dl.acm.org/doi/10.1007/s10586-017-1440-0

Index Terms

Thermal-image processing and statistical analysis for vehicle category in nighttime traffic
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
      2. Computer vision tasks
        Scene understanding
  2. Machine learning

Index terms have been assigned to the content through auto-classification.

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cover image Journal of Visual Communication and Image Representation

Journal of Visual Communication and Image Representation Volume 48, Issue C

October 2017

482 pages

ISSN:1047-3203

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Copyright © Elsevier Inc.

Publisher

Academic Press, Inc.

United States

Publication History

Published: 01 October 2017

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Cited By

Gu ZLei YChan SCao DZhang K(2022)Traffic Incident Detection System Based on Video AnalysisProceedings of the 2022 5th International Conference on Computational Intelligence and Intelligent Systems10.1145/3581792.3581795(15-20)Online publication date: 4-Nov-2022
https://dl.acm.org/doi/10.1145/3581792.3581795
Lin WDeng ZLi XWang KYang YJin B(2017)RETRACTED ARTICLE: Discrete Noetherian ring variational pattern feature sets for space-air-ground network protocol monitoringCluster Computing10.1007/s10586-017-1440-022:Suppl 4(7805-7814)Online publication date: 8-Dec-2017
https://dl.acm.org/doi/10.1007/s10586-017-1440-0

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