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The New Detection Algorithm for an Obstacle’s Information in Low Speed Vehicles

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Computer Vision Systems (ICVS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10528))

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Abstract

MOD (Moving Object Detection) development methods were used motion region detection methods in image, but it is necessary to detect the position and the size of obstacles in a warning area for collision avoidance in a low speed vehicle. Therefore, this paper proposed the new obstacle detection algorithm. First, the proposed algorithm detects the motion region using MHI (Motion History Image) algorithm, which is based on motion information between image frames. After the algorithm is processed by a high-speed and real-time image processing of a moving obstacle, a warning logic system receives the information of the position and the size of the obstacle nearest to a car. Finally, it determines warning signal send to the control part or not. The proposed algorithm recognizes both fixed and moving obstacles such as cars and buildings using 4 - channel AVM camera images and has a fast calculation speed. After we simulated with the image DBs and the simulation tool, we have 80.07% with the average detection rate.

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Acknowledgement

This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No. R7117-16-0164, Development of wide area driving environment awareness and cooperative driving technology which are based on V2X wireless communication).

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Authors and Affiliations

  1. Smart Car Research Center, Chungbuk National University, B324 Yangcheong 4-gil, Ochang-eup, Cheongwon-gu, Cheongju, Chungbuk, 28116, South Korea

    Sinjae Lee & Seok-Cheol Kee

Authors
  1. Sinjae Lee
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  2. Seok-Cheol Kee
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Corresponding author

Correspondence to Seok-Cheol Kee .

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Editors and Affiliations

  1. Hong Kong University of Science and Technology, Hong Kong, China

    Ming Liu

  2. Harbin Institute of Technology, Shenzhen, China

    Haoyao Chen

  3. Technische Universtiät Wien, Vienna, Austria

    Markus Vincze

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Lee, S., Kee, SC. (2017). The New Detection Algorithm for an Obstacle’s Information in Low Speed Vehicles. In: Liu, M., Chen, H., Vincze, M. (eds) Computer Vision Systems. ICVS 2017. Lecture Notes in Computer Science(), vol 10528. Springer, Cham. https://doi.org/10.1007/978-3-319-68345-4_38

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  • DOI: https://doi.org/10.1007/978-3-319-68345-4_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68344-7

  • Online ISBN: 978-3-319-68345-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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