Thermal-image processing and statistical analysis for vehicle category in nighttime traffic
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Author list: Sangnoree A., Chamnongthai K.
Publisher: Elsevier
Publication year: 2017
Journal: Journal of Visual Communication and Image Representation (1047-3203)
Volume number: 48
Start page: 88
End page: 109
Number of pages: 22
ISSN: 1047-3203
eISSN: 1095-9076
Languages: English-Great Britain (EN-GB)
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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. ฉ 2017 Elsevier Inc.
Keywords
ITS, Nighttime traffic, Thermal imaging, Traffic monitoring, Vehicle category
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