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Motion detection and velocity estimation using cellular automata

Conference Paper


Abstract


  • An architecture of a real-time motion detection and velocity estimation system which can easily be implemented into a VLSI chip is presented. The system consists of the following components: image acquisition, edge extraction, velocity estimation, control, and I/O. Among the five parts of the system, the edge extraction and the velocity estimation units are the most important stages. A one-dimensional cellular automata network which emulates a parallel-iterative algorithm called edge relaxation, is employed to detect and track edges, and remove noise from the input binary image. A region-based velocity estimation is carried out by a digital circuit consisting of few counters and registers, a divider and an adder. The architecture can be extended to perform real-time motion estimation for two-dimensional gray-level images.

Publication Date


  • 1994

Citation


  • Kouzani, A. Z., Bouzerdoum, A., & Liebelt, M. (1994). Motion detection and velocity estimation using cellular automata. In Australian and New Zealand Conference on Intelligent Information Systems - Proceedings (pp. 327-331).

Scopus Eid


  • 2-s2.0-0028746363

Web Of Science Accession Number


Start Page


  • 327

End Page


  • 331

Abstract


  • An architecture of a real-time motion detection and velocity estimation system which can easily be implemented into a VLSI chip is presented. The system consists of the following components: image acquisition, edge extraction, velocity estimation, control, and I/O. Among the five parts of the system, the edge extraction and the velocity estimation units are the most important stages. A one-dimensional cellular automata network which emulates a parallel-iterative algorithm called edge relaxation, is employed to detect and track edges, and remove noise from the input binary image. A region-based velocity estimation is carried out by a digital circuit consisting of few counters and registers, a divider and an adder. The architecture can be extended to perform real-time motion estimation for two-dimensional gray-level images.

Publication Date


  • 1994

Citation


  • Kouzani, A. Z., Bouzerdoum, A., & Liebelt, M. (1994). Motion detection and velocity estimation using cellular automata. In Australian and New Zealand Conference on Intelligent Information Systems - Proceedings (pp. 327-331).

Scopus Eid


  • 2-s2.0-0028746363

Web Of Science Accession Number


Start Page


  • 327

End Page


  • 331