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TECHNICAL PAPERS

A Multi-Sensor Approach for Rapid Digitization and Data Segmentation in Reverse Engineering

[+] Author and Article Information
V. H. Chan

Department of Mechanical Engineering, Ryerson Polytechnic University, 350 Victoria St., Toronto, Ontario, Canada, M5B 2K3

C. Bradley, G. W. Vickers

Department of Mechanical Engineering, University of Victoria, Victoria, BC., Canada, V8W 3P6

J. Manuf. Sci. Eng 122(4), 725-733 (Oct 01, 1999) (9 pages) doi:10.1115/1.1286125 History: Received July 01, 1997; Revised October 01, 1999
Copyright © 2000 by ASME
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References

Raab,  S., 1994, “Coordinate measurements accelerate reverse engineering,” Mach. Des., 66, No. 22, pp. 50–53.
Milroy, M., 1995, Automation of Laser-Scanner-Based Reverse Engineering, Ph.D. Dissertation, University of Victoria.
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Worth,  A. J., and Kennedy,  D. N., 1994, “Segmentation of Magnetic Resonance Brain Images Using Analogue Constraint Satisfaction Neural Networks,” Image Vis. Comput., 12, No. 6, pp. 345–354.
Rao, V. B., and Rao, H. V., 1995, Neural Networks and Fuzzy Logic, 2nd ed., MIS Press, New York.
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Figures

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Picture of laser scanner mounted on CMM
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Hardware configurations of laser scanning system
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Segmentation using a neural network. Connections between neural network layers and inter-connections between each pixel within each layer are shown.
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Iteration routine to segment CCD images
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Neuron initialization routine
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Picture of simple test object
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Stereo view of test object
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Test object top surface being segmented
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(a) Scan path of laser scanner (top surfaces). (b) Machine code for the laser scanner path.
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Picture of phone cover test object under laser scanner
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Segmentation of phone cover
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Digitized phone top cover
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Photo of L-shaped test object
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Image processing routines applied to L-shaped test object

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