Content-Based Motorcycle Counting for Traffic Management by Image Recognition

  • Tzung-Pei HongEmail author
  • Yu-Chiao Yang
  • Ja-Hwung Su
  • Chun-Hao Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11432)


Over the past few decades, advanced technologies have increased the number of vehicles, including cars and motorcycles. Because of the large increase of vehicles, the traffic flow becomes more complex and the traffic accidents increase as rapidly. To decrease the number of traffic accidents, a number of studies has been made for how to manage the traffic flow. Especially for motorcycles, in this paper, we propose a method that counts the motorcycles by Convolutional Neural Network (CNN). To reveal the effectiveness of the proposed method, a set of experiments were conducted and the experimental results show the proposed method can bring out a good performance that provides a good support for traffic management systems.


Motorcycle counting Deep learning Convolutional Neural Network Traffic management Video surveillance 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Tzung-Pei Hong
    • 1
    • 2
    Email author
  • Yu-Chiao Yang
    • 1
  • Ja-Hwung Su
    • 3
  • Chun-Hao Chen
    • 4
  1. 1.Department of Computer Science and Information EngineeringNational University of KaohsiungKaohsiungTaiwan
  2. 2.Department of Computer Science and EngineeringNational Sun Yat-sen UniversityKaohsiungTaiwan
  3. 3.Department of Information ManagementCheng Shiu UniversityKaohsiungTaiwan
  4. 4.Department of Computer Science and Information EngineeringTamkang UniversityTaipeiTaiwan

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