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Determination of Congestion Levels Using Texture Analysis of Road Traffic Images

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Contemporary Challenges of Transport Systems and Traffic Engineering

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 2))

Abstract

The paper discusses the application of texture analysis of road traffic images for determination of congestion levels. The capability of mapping congestion is investigated using such texture features as: energy, entropy, contrast, homogeneity, dissimilarity, correlation, captured by co-occurrence matrices. No single feature distinctly represents congestion. An optimal combination of features is chosen for classification of congestion levels. Three levels of congestion are correctly differentiated using the proposed texture model of road traffic images. The model is validated using images registered by UAV (Unmanned Aerial Vehicle) flying over a traffic junction.

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Author information

Authors and Affiliations

  1. Faculty of Transport, Silesian University of Technology, Katowice, Poland

    Teresa Pamuła

Authors
  1. Teresa Pamuła
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Correspondence to Teresa Pamuła .

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Editors and Affiliations

  1. Faculty of Transport, Silesian University of Technology Faculty of Transport, Katowice, Poland

    Elżbieta Macioszek

  2. Faculty of Transport, Silesian University of Technology Faculty of Transport, Katowice, Poland

    Grzegorz Sierpiński

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Pamuła, T. (2017). Determination of Congestion Levels Using Texture Analysis of Road Traffic Images. In: Macioszek, E., Sierpiński, G. (eds) Contemporary Challenges of Transport Systems and Traffic Engineering . Lecture Notes in Networks and Systems, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-43985-3_5

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  • DOI: https://doi.org/10.1007/978-3-319-43985-3_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43984-6

  • Online ISBN: 978-3-319-43985-3

  • eBook Packages: EngineeringEngineering (R0)

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