![](bg8.png)
the CCG sequence. No correction is applied, but the
end result of determining the correct positioning is
still achieved. Hence the current approach is quite
robust, and it is not likely that much improvement
would be obtained by adding Reed-Solomon error
correction.
In the future, if colour correction is desired, then
word sequencing could be exploited further as a
means to go back and correct the recognition of each
individual colour square so that it is in complete
agreement with the determined word sequence. This
would enable, for example, improvement in image
brightness and colour rendering.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge the financial
support of the Engineering Research Center for
Reconfigurable Manufacturing Systems (NSF Grant
EEC-9529125) at the University of Michigan and
the valuable input from the center’s industrial
sponsors. Special thanks to Nelson Woo, Brent Carr,
Kyung Han, David Wintermute, and Steve Erskine
for their aid in system construction and software
programming.
The authors thank Jean-Yves Bouguet for
publishing the Camera Calibration Toolbox for
Matlab on the Internet.
REFERENCES
Wilburn, B., Smulski, M., Lee, H.H., Horowitz, M., 2002,.
The Light Field Video Camera. Proc. of Media
Processors 2002, SPIE Electronic Imaging.
Wilburn, B., Joshi, N., Vaish, V., Levoy, M., Horowitz,
M., 2004. High-Speed Videography Using a Dense
Camera Array. Proceedings of the 2004 IEEE
Computer Society Conference on CVPR 2004, Vol. 2,
pp. 294 – 301.
Vaish, V., Wilburn, B., Joshi, N., Levoy, M., 2004. Using
Plane + Parallax for Calibrating Dense Camera
Arrays. Proceedings of the 2004 IEEE Computer
Society Conference on CVPR 2004, vol. 1, pp. 2 – 9.
Yang, J.C., Everett, M., Buehler, C., McMillan, L., 2002.
A Real-Time Distributed Light Field Camera,
Thirteenth Eurographics Workshop on Rendering.
Zhang, C., Chen, T., 2004. A Self-Reconfigurable Camera
Array, Eurographics Symposium on Rendering.
Naemura T., Tago J., Harashima H., 2002. Real-Time
Video-Based Modeling and Rendering of 3D Scenes.
IEEE Computer Graphics and Applications, Vol. 22 ,
Issue 2, pp. 66 – 73.
Koren, Y., Ulsoy, A.G., 2002, Vision, Principles and
Impact of Reconfigurable Manufacturing Systems,
Powertrain International pp.14-21.
Bouguet, J.Y., Camera Calibration Toolbox for Matlab,
http://www.vision.caltech.edu/bouguetj/calib_doc/
Tsai, R.Y., 1987. A versatile camera calibration technique
for high accuracy 3d machine vision metrology using
off-the-shelf tv cameras and lenses. IEEE Journal of
Robotics and Automation, Vol. RA-3, No. 4, pp. 323-
344.
Heikkilä, J., Silvén, O., 1997. A Four-step Camera
Calibration Procedure with Implicit Image Correction.
Proceedings of the 1997 IEEE Computer Society
Conference on CVPR'97, San Juan, Puerto Rico, pp.
1106-1112.
Brown M., Lowe D.G., 2003. Recognizing Panoramas.
Ninth IEEE International Conference on Computer
Vision (ICCV 2003), Nice, France.
Shum H.-Y., Szeliski R., 1998. Construction and
refinement of panoramic mosaics with global and local
alignment. Sixth International Conference on
Computer Vision (ICCV'98), pages 953-958, Bombay.
Abramovich G., Barhak J., Spicer P., 2005. Camera
Arrays for Machine Vision Inspection. The 2005 CIRP
3rd International Conference on Reconfigurable
Manufacturing, May 10-12, Ann Arbor, Michigan.
Anderson I., 1974. A First Course in Combinatorial
Mathematics, Oxford University Press, pp. 92-96.
Corney D., Clustering with Matlab,
http://www.cs.ucl.ac.uk/staff/d.corney/ClusteringMatl
ab.html
Communications Toolbox, Creating and Decoding Reed-
Solomon Codes., www.mathworks.com
VISAPP 2006 - IMAGE FORMATION AND PROCESSING
138