View Invariant Motorcycle Detection for Helmet Wear Analysis in Intelligent Traffic Surveillance

  • M. AshviniEmail author
  • G. Revathi
  • B. Yogameena
  • S. Saravanaperumaal
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 460)


An important issue for intelligent traffic surveillance is automatic vehicle classification in traffic scene videos, which has great prospective for all kinds of security applications. Due to the number of vehicles in operation surpassed, occurrence of accidents is increasing. Hence, the vehicle classification is an important building block of surveillance systems that significantly impacts reliability of its applications. It helps in classifying the motorcycles that uses public transportation. This has been identified as an important task to conduct surveys on estimation of people wearing helmets, accident with and without helmet and vehicle tracking. The inability of police power in many countries to enforce helmet laws results in reduced usage of motorcycle helmets which becomes the reason for head injuries in case of accidents. This paper comes up with a system with view invariant using Histogram of Oriented Gradients which automatically detects motorcycle riders and determines whether they are wearing helmets or not.


Background subtraction Histogram of Oriented Gradients (HOG) Center-Symmetric Local Binary Pattern (CS-LBP) K-Nearest Neighbor (KNN) 


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Copyright information

© Springer Science+Business Media Singapore 2017

Authors and Affiliations

  • M. Ashvini
    • 1
    Email author
  • G. Revathi
    • 1
  • B. Yogameena
    • 1
  • S. Saravanaperumaal
    • 2
  1. 1.Department of ECEThiagarajar College of EngineeringMaduraiIndia
  2. 2.Department of MechanicalThiagarajar College of EngineeringMaduraiIndia

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