Parallel Extraction Architecture for Information of Numerous Particles in Real-Time Image Measurement

Yoshihiro Watanabe; Takashi Komuro; Shingo Kagami; Masatoshi Ishikawa

doi:10.20965/jrm.2005.p0420

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JRM Vol.17 No.4 pp. 420-427

doi: 10.20965/jrm.2005.p0420

(2005)

Paper:

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Parallel Extraction Architecture for Information of Numerous Particles in Real-Time Image Measurement

Yoshihiro Watanabe, Takashi Komuro, Shingo Kagami,
and Masatoshi Ishikawa

Department of Information Physics and Computing, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Received:

December 16, 2004

Accepted:

March 22, 2005

Published:

August 20, 2005

Keywords:

image measurement, moment extraction, particle information, real-time image processing

Abstract

In this paper, we propose a new architecture that can extract information of numerous particles in an image at high-speed. Particle information means various characteristics obtained from image moments. The proposed architecture simultaneously extracts moments of multiple particles in parallel. This parallel extraction enables a significant reduction in the amount of calculation required. In addition, asynchronous operation allows fast processing. We believe that this architecture can obtain more information in real-time even at high frame rates than conventional processing, providing advantages in a wide range of applications, mainly for image measurement. This paper details our proposed architecture and reviews some results of its implementation in FPGA.

Cite this article as:

Y. Watanabe, T. Komuro, S. Kagami, and M. Ishikawa, “Parallel Extraction Architecture for Information of Numerous Particles in Real-Time Image Measurement,” J. Robot. Mechatron., Vol.17 No.4, pp. 420-427, 2005.

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References

[1] http://www.micron.com/products/imaging/
[2] http://www.dalsa.com/
[3] http://www.fillfactory.com/
[4] M. Raffel, C. E. Willert, and J. Kompenhans, “Particle Image Velocimetry: A Practical Guide (Experimental Fluid Mechanics),” Springer Verlag, 1998.
[5] M. K. Hu, “Visual Pattern Recognition by Moment Invariants,” IRA Transactions on Information Theory, Vol.IT-8, pp. 179-187, 1962.
[6] I. Ishii, T. Komuro, and M. Ishikawa, “Method of Moment Calculation for a Digital Vision Chip System,” Proceedings of IEEE International Workshop on Computer Architecture for Machine Perception, pp. 41-48, 2000.
[7] T. Komuro, S. Kagami, and M. Ishikawa, “A New Architecture of Programmable Digital Vision Chip,” Proceedings of 2002 Symposium on VLSI Circuits, pp. 266-269, 2002.
[8] Y. Imai, A. Namiki, K. Hashimoto, and M. Ishikawa, “Dynamic Active Catching Using a High-speed Multifingered Hand and a High-speed Vision System,” Proceedings of 2004 IEEE International Conference on Robotics and Automation, pp. 1849-1854, 2004.
[9] T. Senoo, A. Namiki, and M. Ishikawa, “High-Speed Batting Using a Multi-Jointed Manipulator,” Proceedings of 2004 IEEE International Conference on Robotics and Automation, pp. 1191-1196, 2004.
[10] H. Oku, I. Ishii, and M. Ishikawa, “Tracking a Protozoon Using High-Speed Visual Feedback,” Proceedings of 1st Annual International IEEE-EMBS Special Topic Conference on Microtechnologies in Medicine & Biology, pp. 156-159, 2000.
[11] N. Ogawa, H. Oku, K. Hashimoto, and M. Ishikawa, “Motile Cell Galvanotaxis Control using High-Speed Tracking System,” Proceedings of 2004 IEEE International Conference on Robotics and Automation, pp. 1646-1651, 2004.
[12] S. Kleinfelder, S. Lim, X. Liu, and A. E. Gamal, “A 10000 Frames/s CMOS Digital Pixel Sensor,” IEEE Journal of Solid-State Circuits, Vol.36, No.12, pp. 2049-2058, 2001.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] http://www.micron.com/products/imaging/

[2] [2] http://www.dalsa.com/

[3] [3] http://www.fillfactory.com/

[4] [4] M. Raffel, C. E. Willert, and J. Kompenhans, “Particle Image Velocimetry: A Practical Guide (Experimental Fluid Mechanics),” Springer Verlag, 1998.

[5] [5] M. K. Hu, “Visual Pattern Recognition by Moment Invariants,” IRA Transactions on Information Theory, Vol.IT-8, pp. 179-187, 1962.

[6] [6] I. Ishii, T. Komuro, and M. Ishikawa, “Method of Moment Calculation for a Digital Vision Chip System,” Proceedings of IEEE International Workshop on Computer Architecture for Machine Perception, pp. 41-48, 2000.

[7] [7] T. Komuro, S. Kagami, and M. Ishikawa, “A New Architecture of Programmable Digital Vision Chip,” Proceedings of 2002 Symposium on VLSI Circuits, pp. 266-269, 2002.

[8] [8] Y. Imai, A. Namiki, K. Hashimoto, and M. Ishikawa, “Dynamic Active Catching Using a High-speed Multifingered Hand and a High-speed Vision System,” Proceedings of 2004 IEEE International Conference on Robotics and Automation, pp. 1849-1854, 2004.

[9] [9] T. Senoo, A. Namiki, and M. Ishikawa, “High-Speed Batting Using a Multi-Jointed Manipulator,” Proceedings of 2004 IEEE International Conference on Robotics and Automation, pp. 1191-1196, 2004.

[10] [10] H. Oku, I. Ishii, and M. Ishikawa, “Tracking a Protozoon Using High-Speed Visual Feedback,” Proceedings of 1st Annual International IEEE-EMBS Special Topic Conference on Microtechnologies in Medicine & Biology, pp. 156-159, 2000.

[11] [11] N. Ogawa, H. Oku, K. Hashimoto, and M. Ishikawa, “Motile Cell Galvanotaxis Control using High-Speed Tracking System,” Proceedings of 2004 IEEE International Conference on Robotics and Automation, pp. 1646-1651, 2004.

[12] [12] S. Kleinfelder, S. Lim, X. Liu, and A. E. Gamal, “A 10000 Frames/s CMOS Digital Pixel Sensor,” IEEE Journal of Solid-State Circuits, Vol.36, No.12, pp. 2049-2058, 2001.

Parallel Extraction Architecture for Information of Numerous Particles in Real-Time Image Measurement

Yoshihiro Watanabe, Takashi Komuro, Shingo Kagami, and Masatoshi Ishikawa

Yoshihiro Watanabe, Takashi Komuro, Shingo Kagami,
and Masatoshi Ishikawa