Abstract
Automatic computer analysis of images for recognition, inspection, and verification has advanced to the stage where it is feasible for many industrial applications. Industry has a need for productivity enhancements and there is a growing acceptance of other forms of computer controlled automation (such as the industrial robot). The state-of-the-art in image processing techniques, the reduced cost and size and higher reliability of image sensors, and the trend toward low-priced, yet high-performance micro- and mini-processors seems to indicate that the time is “ripe” for the introduction of complex vision tasks to industry. However, the problem in implementing computer vision tasks in the past has been one of programmability, that is, the need for skilled programmers to generate the analysis program for each new task.
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References
W. A. Perkins, “A model-based vision system for industrial parts,” IEEE Transactions on Computers, Vol. C-27, No. 2, pp. 126–143, Feb.1978.
M. L. Baird, “Image segmentation technique for locating automotive parts on belt conveyors, in Proc. of the 5th International Joint Conference on Artificial Intelligence, pp. 694-695, Cambridge, Mass., Aug.1977.
R. C. Bolles, “Verification vision for programmable assembly,” in Proc. of the 5th International Joint Conference on Artificial Intelligence, pp. 569-575, Cambridge, Mass., Aug. 1977.
J. Bretschi, “A microprocessor controlled visual sensor for industrial robots, Industrial Robot, pp. 167-172, Dec. 1976.
G. J. Agin, “An experimental vision system for industrial application,” Proc. of the 5th Int. Symposium on Industrial Robots, Chicago, pp. 135-148, 1975. References 6 to 9 appeared in the Proc. of the 8th International Symposium on Industrial Robots, Stuttgart, May 1978.
J-D. Dessimoz, “Visual identification and location in a multi-object environment by contour tracking and curvature description,” in the 8th ISIR, pp. 764-777.
A. Niemi, “Object recognition and handling in an industrial robot system with vision, in the 8th ISIR, pp. 744-755.
J. Birk, et. al., Acquiring workpieces: three approaches using vision, in the 8th ISIR, pp. 724-733.
A. Pugh, et. al., Versatile parts feeding package incorporating sensory feedback, in the 8th ISIR, pp. 206-217.
S. W. Holland, “An approach to programmable computer vision for robotics, General Motors Research Report GMR-2519, Warren, Michigan, Aug. 1977.
I. C. Braid, Designing with Volumes, Cambridge, England: Cantab Press, 1974.
“An Introduction to PADL,” Production Automation Project Technical Memorandum 22, Univ. of Rochester, Rochester, New York, Dec.1974.
B. G. Baumgart, Geometric modelling for computer vision, Ph.D. Thesis, Stanford University, Stanford Artificial Intelligence Laboratory Memo AIM-249, Oct. 1974.
L. I. Lieberman and M. A. Wesley, “AUTOPASS: An automatic programming system for computer controlled mechanical assembly, IBM Journal of Research and Development, Vol. 21, No. 4, pp. 321–333, July 1977.
D. D. Grossman, “Procedural representation of three dimensional objects, IBM Journ. of Research and Development, Vol. 20, No. 6, pp. 582–589, Nov. 1976.
H. G. Barrow, et. al., Parametric correspondence and chamfer matching: two new techniques for image matching, in Proc. of the 5th International Joint Conference on Artificial Intelligence, pp. 659-663, Cambridge, Mass., Aug. 1977.
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© 1979 Plenum Press, New York
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Lieberman, L. (1979). Model-Driven Vision for Industrial Automation. In: Stucki, P. (eds) Advances in Digital Image Processing. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-8282-3_11
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DOI: https://doi.org/10.1007/978-1-4615-8282-3_11
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