Modeling errors for dimensional inspection using active vision

Robotics and Computer-Integrated Manufacturing

Volumn 15, Issue 1, 1999, Pages 23-37

  Yang, Christopher C ^a   Marefat, Michael M ^b   Ciarallo, Frank W ^b  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

^b University of Arizona   (United States)

Author keywords

3D vision; Active vision; Computer integrated inspection; Dimensional inspection; Displacement error; Error analysis; Image understanding; Quantization error; Scene analysis

Indexed keywords

APPROXIMATION THEORY; COMPUTER VISION; ERROR ANALYSIS; IMAGE ANALYSIS; IMAGE SENSORS; IMAGE UNDERSTANDING; INSPECTION; MATHEMATICAL MODELS; QUALITY ASSURANCE;

ACTIVE VISIONS; COMPUTER INTEGRATED INSPECTIONS; DISPLACEMENT ERRORS; QUANTIZATION ERRORS; SCENE ANALYSIS;

COMPUTER INTEGRATED MANUFACTURING;

EID: 0032643456     PISSN: 07365845     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0736-5845(98)00025-8     Document Type: Article

References (36)

1. Kamgar-Parsi B, Kamgar-Parsi B. Evaluation of quantization error in computer vision. IEEE Trans Pattern Anal Mach Intell 1989;11(9).
2. Blostein SD, Thomas SH. Error analysis in Stereo determination of 3-D point positions. IEEE Trans Pattern Anal Mach Intell 1987;9(6).
3. Ho C-S. Precision of digital vision systems. IEEE Trans Pattern Anal Mach Intell 1983;5(6).
4. Griffin PM, Rene Villalobos J. Process capability of automated visual inspection systems. IEEE Trans Systems Man Cybernet 1992;22(3).
5. Su S-F, Lee CSG. Manipulation and propagating of uncertainty and verification of application of actions in assembly tasks. IEEE Trans systems Man Cybernet 1992;22(6).
6. Renders J-M, Rossigno E, Becquet M, Hanus R. Kinematic calibration and geometrical parameter identification for robots. IEEE Trans Robotics Automation 1991;7(6).
7. Menq C-H, Yau H-T. Lai G-Y. Autoamted precision measurement of surface profile in CAD-directed inspection. IEEE Trans Robotics Automation 1992;8(2).
8. Chen J, Chao LM. Positioning error analysis for robot manipultors with all rotary joints. IEEE Int Conf Robotics Automat San Francisco, CA, April 1986.
9. Veitschegger WK, Wu C-h. A method for calibrating and compensating robot kinematic errors. IEEE Int Conf on Robotics and Automation, 1987.
10. Bryson S. Measurement and calibration of static distortion of position data from 3D trackers. SPIE, 1669 Sterkoscopic displays and applications III. 1992.
11. Smith RC, Chessman P. On the representation and estimation of spatial uncertainty. Int J Robotics Res 1986;5(4).
12. Huertas A, Medioni C. Detection of intensity changes with subpixel accuracy using Laplacian-Gaussain masks. IEEE Trans Pattern Anal Mach Intel 1986; 8(5).
13. Jensen K, Anastassiou D. Subpixel edge localization and the interpolation of still images. IEEE Trans Image Process 1995;4(3).
14. Kisworo M, Venkatesh S, West G. Modeling edges at subpixel accuracy using the local energy approach. IEEE Trans Pattern Anal Mach Intell 1994; 16(4).
15. Lyvers E, Mitchell OR, Akey ML, Reeves P. Subpixel measurements using a moment-based edge operator. IEEE Trans Pattern Anal Machlntell 1989; 11(2).
16. MacVicar-Whelan PJ, Bindord TO. Line finding with subpixel precision. Proc SPIE Techniques Appl Image Understanding 1981;281.
17. Ballard DH, Brown CM. Computer vision. Englewood Cliffs, NJ: Prentice-Hall, Inc, 1982.
18. Chin RT. Survey automated visual inspection: 1981 to 1987. Comput Vision Graphics Image Process 1988;41:346-81.
19. Cowan CK. Automated sensor placement for vision task-requirements. IEEE Trans Pattern Anal Mach Intell 1988;10(3).
20. Foley JD, Van Dam A. Computer graphics: principles and practices. Reading, MA: Addison-Wesley, 1990.
21. Hayclock DI. Geometric precision in noise-free digital images. IEEE Trans Pattern Anal Mach Intell 1989;11:1065-75.
22. Hutchinson SA, Cronwell RL, Kak AC. Planning sensing strategies in robot work cell with multi-sensor capabilities. IEEE Trans Robotics Automation 1989;5(6).
23. Marefat M, Kashyap RL. Image interpretation and object recognition in manufacturing. IEEE Control Systems 1991;11(5).
24. Marefat M, Kashyap RL. Feature-based computer integrated inspection. Proc 1993 ASME Int Computers in Engineering Conf. San Diego, CA, 8-12 August, 1993.
25. Menq CH, Borm J-H. Statistical measure and characterization of robot errors. Proc IEEE Int Conf on Robotics and Automation, 1988.
26. Moon CW. Error analysis for dimensional measurement using computer vision techniques. IEEE instrumentation and Measurement Technology Conf. San Diego, CA, 1988;371-6.
27. Park HD, Mitchell OR. CAD based planning and execution of inspection. Proc IEEE computer vision and Pattern Recognition Conf Ann Arbor, Michigan, 1988.
28. Paul RP. Differential relationships, robot manipulators: mathematics, programming, and control, Ch. 4. The MIT Press, Cambridge, Massachusetts and London, England, 1981.
29. Radack GM, Merat FL. The integration of inspection into the CIM environment. Proc Hawaii Int Conf on System Science, 1990;445-62.
30. Yi S, Harlick RM, Shapiro L. Automatic sensor and light soruce positioning for machine vision. Proc 10th Int Conf on Pattern Recognition. Atlantic City, NJ, 2-3 June, 1991.
31. Tsai RY. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE Trans Robotics Automation 1987;3(4).
32. Yan Z, Menq C-H. Coordinate sampling and uncertainty analysis for computer integrated manufacturing and dimension inspection. Proc 1993 NSF Design and Manufacturing Systems Conf. Charlotte, North Carolina, 6-8 January, 1993.
33. Yang CC, Marefat MM, Ciarallo FW. Active visual inspection on CAD models. IEEE International Conference on Robotics and Automation, San Diego, CA, 8-13 May, 1994.
34. Yang CC, Marefat MM, Kashyap RL. Analysis of errors in dimensional inspection based on active vision. Proc SPIE Int Symp on Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, Active Vision. Cambridge, MA, 31 October-4 November, 1994.
35. Tarabanis K, Tsai RY, Allen PK. Analytic characterization of the feature detectability constraints of resolution, focus, and field-of-view for vision sensor planning. CVGIP: Image Understanding 1994;59(3):340-58.
36. Tarabanis K, Tsai RY, Alien PK. The MVP sensor planning system for robotic vision tasks. IEEE Trans Robotics Automation 1995;11(1).