Real-time Road Obstacle Detection Using Association and Symmetry Recognition

Authors

  • Khalid Zebbara Laboratory Computer Systems and Vision, Department of Computer Science, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
  • Abdenbi Mazoul Laboratory Computer Systems and Vision, Department of Computer Science, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
  • Mohamed EL Ansari Laboratory Computer Systems and Vision, Department of Computer Science, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco

Keywords:

Obstacle detection, Vehicle detection, intelligent vehicle, edges detection, Association.

Abstract

This paper presents a fast road obstacle detection system based on association and symmetry. This approach consists to exploit the edges extracted from consecutive images acquired by a stereo sensor embedded in a moving vehicle. The algorithm contains three main components: edges detection, association detection and symmetry calculation. The edges detection is achieved by using the canny operator and point corner to extract all possible edges of different objects at the image. The association technique is used to exploit relationship between the edges of two consecutives images by combining it with the moment operator. The symmetry is used as road obstacle validation; the road obstacles like vehicle and pedestrian have a vertical symmetry. The proposed approach has been tested on different images. The provided results demonstrate the effectiveness of the proposed method.

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Published

2018-12-22

How to Cite

Zebbara, K., Mazoul, A., & EL Ansari, M. (2018). Real-time Road Obstacle Detection Using Association and Symmetry Recognition. American Scientific Research Journal for Engineering, Technology, and Sciences, 50(1), 204–213. Retrieved from https://www.asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/4606

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