Skip to main content

2D- und 3D-Objektbeschreibung für Sichtsystehe

  • Chapter

Zusammenfassung

Die Automatisierung von Transport- und Fertigungsvorgängen wird vereinfacht und für weitere Anwendungsbereiche überhaupt erst möglich, wenn das Förder- oder Handhabungsgerät mit einem Sichtsystem gekoppelt ist. Die Aufgaben, die ein Sichtsystem innerhalb des industriellen Prozesses zu erfüllen hat, bestimmen die systeminterne Beschreibungsweise der vom visuellen Sensor erfaßten Umwelt, der zu manipulierenden Gegenstände und der Aufgabenstellung. Die zahlreichen Randbedingungen, die bei der Konzeption und Realisierung eines Sichtsystems zu beachten sind, und die Vielfalt von Lösungsansätzen zur Erzeugung von Objektbeschreibungen aus den Sensordaten, wobei die Vorzüge, Nachteile und Grenzen der Verfahren oft nur experimentell und im Nachhinein feststellbar sind, rücken eine Theorie der Sichtsysteme in weite Ferne. Zur Weiterentwicklung visuell gesteuerter Maschinen kann deshalb im Augenblick nur eine Phänomenologie der Anforderungen und Lösungsansätze beitragen.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   49.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Literaturverzeichnis

  1. E. Abele, W. Sturz: “Sensoren zur adaptiven Steuerung von Industrierobotern beim Entgraten”, in [IPA82], pp. 79-92.

    Google Scholar 

  2. U. Ahrens, W. Friedrich, S. Deliev: “Sensoreinsatz beim Be-und Entladen von Paletten mit Industrierobotern”, in [IPA82], pp. 105-116.

    Google Scholar 

  3. A.P. Ambler, H.G. Barrow, CM. Brown, R.M. Burstall, R.J. Popplestone: “A Versatile System for Computer-Controlled Assembly”, Artificial Intelligence 6 (1975) 129–156.

    Article  MATH  Google Scholar 

  4. D. Andree, A. Wernersson: “Linear Vision for Finding the Orientation of Parts: Learning Procedures”, in [RV82], pp. 147-158.

    Google Scholar 

  5. T. Asano, S. Maeda, T. Murai: “Vision System of an Automatic Inserter for Printed Circuit Board Assembly”, in [RV82], pp. 63-72.

    Google Scholar 

  6. D.H. Ballard, CM. Brown: “Computer Vision”, Prentice-Hall, Englewood Cliffs/NJ USA, 1982.

    Google Scholar 

  7. G. Bancon, B. Huber: “Depression and Dual Grippers with their Possible Applications”, in [ISIR82], pp. 321-325.

    Google Scholar 

  8. H.G. Barrow, J.M. Tenenbaum: “Recovering Intrinsic Scene Characteristics from Images”, in [Hanson&Riseman78], pp. 3-26.

    Google Scholar 

  9. B.G. Batchelor, S.M. Cotter, P.W. Heywood, D.H. Mott: “Recent Advances in Automated Visual Inspection”, in [RV82], pp. 307-326.

    Google Scholar 

  10. S. Berman, P. Parikl, C.S.G. Lee: “Computer Recognition of Overlapping Parts Using a Single Camera”, in [PRIP82], pp. 650-655.

    Google Scholar 

  11. R. Bertelsmeier, G. Hille: “Anwendungen von Bildanalysetechniken zur automatischen Sichtkontrolle von Bauteilen in Automobilen”, in [Foith79], pp. 330-340.

    Google Scholar 

  12. T.O. Binford: “Inferring Surfaces from Images”, in [Brady81], pp. 205-244.

    Google Scholar 

  13. K.H. Bitter: “Anwendung von optoelektronischen Bildsensoren”, in [IPA82], pp. 39-62.

    Google Scholar 

  14. C. Blume, R. Dillmann: “Frei programmierbare Manipulatoren”, Vogel-Verlag, Würzburg 1981.

    Google Scholar 

  15. J.C. Bocquet, S. Tichkiewitch: “An ‘Expert System’ for Reconstruction of Mechanical Object from Projections”, in [PRIP82], pp. 491-496.

    Google Scholar 

  16. J.D. Boissonnat, F. Germain: “A New Approach to the Problem of Acquiring Randomly Oriented Workpieces out of a Bin”, in [IJCAI81], pp. 796-802.

    Google Scholar 

  17. R.M. Bolle, D.B. Cooper, B. Cernuschi-Frias: “Three Dimensional Surface Shape Recognition by Approximating Image Intensity Function with Quadric Polynomials”, in [PRIP82], pp. 611-617.

    Google Scholar 

  18. R.C. Bolles: “Robust Feature Matching Through Maximal Cliques”, SPIE 182 (1980) 140-149.

    Google Scholar 

  19. R.C. Bolles, R.A. Cain: “Recognizing and Locating Partially Visible Workpieces”, in [PRIP82], pp. 498-503.

    Google Scholar 

  20. R.C. Bolles, R.A. Cain: “Recognizing and Locating Partially Visible Objects: The Local-Feature-Focus Method”, Robotics Research 13(1982) 57-82.

    Google Scholar 

  21. J.M. Brady (Hrsg.): “Computer Vision”, North-Holland, Amsterdam, 1981; siehe auch Artificial Intelligence 17, August 1981.

    Google Scholar 

  22. M. Brady, J.M. Hollerbach, T.L. Johnson, T. Lozano-Peres, M.T. Mason: “Robot Motion: Planning and Control”, MIT Press, Cambridge/MA USA, 1982.

    Google Scholar 

  23. R.A. Brooks: “Symbolic Reasoning Among 3-D Models and 2-D Images”, in [Brady81], pp. 285-348.

    Google Scholar 

  24. R.A. Brooks: “Symbolic Error Analysis and Robot Planning”, Robotics Research 14 (1982) 29-68.

    Google Scholar 

  25. R.A. Brooks: “Solving the Find-Path Problem by Representing Free Space as Generalized Cones”, A.I. Memo No. 674, MIT Cambridge/MA USA 1982.

    Google Scholar 

  26. R.A. Brooks: “Representing Possible Realities for Vision and Manipulation”, in [PRIP82], pp. 587-592.

    Google Scholar 

  27. R.A. Brooks: “Solving the Find-Path Problem by Good Representation of Free Space”, IEEE Trans. SMC-13 (1983) 190-196.

    Google Scholar 

  28. R.A. Brooks, T. Lozano-Perez: “A Subdivision Algorithm in Configuration Space for Findpath with Rotation”, A.I. Memo No. 684, MIT, Cambridge/MA USA 1982.

    Google Scholar 

  29. R.A. Brooks, T. Lozano-Perez: “A Subdivision Algorithm in Configuration Space for Findpath with Rotation”, in [IJCAI83], im Druck [Bruss&Horn83] A.R. Bruss, B.K.P. Horn: “Passive Navigation” Computer Vision, Graphics, and Image Processing 21 (1983) 3-20.

    Google Scholar 

  30. H. Bunke, G. Allermann: “Inexact Graph Matching for Structural Pattern Recognition”, Pattern Recognition Letters 1 (1983) 245-253.

    Google Scholar 

  31. C.H. Chen (Hrsg.): “Pattern Recognition and Artificial Intelligence”, Academic Press, New York 1976.

    Google Scholar 

  32. J.K. Cheng, T.S. Huang: “Recognition of Curvilinear Objects by Matching Relational Structures”, in [PRIP82], pp. 343-348.

    Google Scholar 

  33. M.J. Chen, D.L. Milgram: “A Development System for Machine Vision”, in [PRIP82], pp. 512-517.

    Google Scholar 

  34. W.F. Clocksin, J.W. Barratt, P.G. Davey, C.G. Morgan, A.R. Vidler: “Visually Guided Robot Arc-Welding of Thin Sheet Steel Pressings”, in [ISIR82], pp. 225-230.

    Google Scholar 

  35. A.J. Cronshaw: “Automatic Chocolate Decoration by Robot Vision”, in [ISIR82], pp. 249-257.

    Google Scholar 

  36. H. Decker: “Elastischer Bildvergleich am Beispiel der automatischen Prüfung von Aluminiumgußteilen”, 5. DAGM-Symposium 1983, dieser Band.

    Google Scholar 

  37. G.G. Dodd, L. Rossol (Hrsg.): “Computer Vision and Sensor-Based Robots”, Plenum Press New York London 1979, Proc. Symposium in Warren/MI USA, Sept. 1978.

    Google Scholar 

  38. M.J.B. Duff: “Special Hardware for Pattern Processing”, in [ICPR82], pp. 368-379.

    Google Scholar 

  39. E. Enderle: “Automatische Analyse von Binärbildern aufgrund relationaler Modelle”, in [Radig81], pp. 55-60.

    Google Scholar 

  40. O.D. Faugeras, F. Germain, G. Kryse, J.D. Boissonnat, M. Hebert, J. Ponce: “Toward a Flexible Vision System”, in [ISIR82], pp. 67-78.

    Google Scholar 

  41. O.D. Faugeras, J. Ponce: “Prism Trees: A Hierarchical Representation for 3-D Objects”, in [IJCAI83], im Druck.

    Google Scholar 

  42. I.D. Faux, M.J. Pratt: “Computational Geometry for Design and Manufacture”, Ellis Horwood, Chichester/England, 1979.

    Google Scholar 

  43. J.A. Feldman et al.: “The Stanford Hand-Eye Project”, [IJCAI69] pp. 521-526.

    Google Scholar 

  44. M. Ferrer, M. Briot, J.C. Talon: “Study of a Video Image Treatment System for the Mobile Robot HILARE”, in [RV81], pp. 59-71.

    Google Scholar 

  45. M.A. Fischler: “On the Representation of Natural Scenes”, in [Hanson&Riseman78], pp. 47-52.

    Google Scholar 

  46. R. Fikes, P. Hart, N. Nilsson: “Learning and Executing Generalised Robot Plans”, Artificial Intelligence 3 (1972) 251-288.

    Google Scholar 

  47. J.P. Foith (Hrsg.): “Angewandte Szenenanalyse”, 2. DAGM-Symposium, Karlsruhe 1979, Informatik Fachberichte 20, Springer-Verlag Berlin Heidelberg New York 1979.

    Google Scholar 

  48. J.P. Foith, C. Eisenbarth, E. Enderle, H. Geißelmann, H. Ringshauser, G. Zimmermann: “Optischer Sensor für Erkennung von Werkstücken auf dem laufenden Band, realisiert mit einem modularen System”, in [Steusloff80], pp. 135-155.

    Google Scholar 

  49. K.S. Fu: “Syntactic Models for Image Analysis”, in [Radig81], pp. 271-295.

    Google Scholar 

  50. K.S. Fu: “Syntactic Pattern Recognition and Applications”, Prentice Hall, Englewood Cliffs/NJ USA 1982.

    Google Scholar 

  51. H. Geißelmann: “Griff in die Kiste durch Vereinzelung und optische Erkennung”, in [Steusloff80], pp. 156-165.

    Google Scholar 

  52. L. Gibson, D. Lucas: “Spatial Data Processing Using Generalized Balanced Ternary”, in [PRIP82], pp. 566-571.

    Google Scholar 

  53. F. Glazer: “Computing Optical Flow”, in [IJCAI81], pp. 644-647.

    Google Scholar 

  54. H. Goldstein: “Classical Mechanics”, Addison-Wesley, Reading/MA USA, 1950.

    Google Scholar 

  55. D. Graham, Y.C. Choong: “Robot Vision in Automated Surface Finishing”, in [RV81], pp. 113-123.

    Google Scholar 

  56. W.E.L. Grimson: “From Images to Surfaces: A Computational Study of the Human Early Visual System”, MIT Press Cambridge/MA USA 1981.

    Google Scholar 

  57. U.L. Haass, H.-B. Kuntze, W. Schill: “Ein Überwachungssystem zur Hinderniserkennung und Kollisionsverhütung im Arbeitsraum von Industrierobotern”, in [IPA82], pp. 179-189.

    Google Scholar 

  58. W. Hättich: “Hierarchische Kombination eines strukturellen und numerischen Verfahrens zur Erkennung und Lagebestimmung überlappender Werkstücke”, in [Radig81], pp. 61-67.

    Google Scholar 

  59. A. Hanson, E. Riseman (Hrsg.): “Computer Vision Systems”, Academic Press New York 1978.

    Google Scholar 

  60. R.M. Haralick: “Scene Analysis, Arrangements, and Homomorphisms”, in [Hanson&Riseman78], pp. 199-212.

    Google Scholar 

  61. J.-P. Hermann: “Pattern Recognition in the Factory: An Example”, in [ISIR82], pp. 271-280.

    Google Scholar 

  62. P.F. Hewkin, H.-J. Fuchs: “Neue Fähigkeiten des OMS Sichtsystems”, in [IPA82], pp. 165-178.

    Google Scholar 

  63. G. Hille: “Methoden und Modelle in der Bildsegmentation: Eine Übersicht”, Bericht IfI-HH-B80/81 des Fachbereichs für Informatik der Universität Hamburg, 1981.

    Google Scholar 

  64. S.W. Holland, L. Rossol, M. R. Ward: “CONSIGHT-I: A Vision-Controlled Robot System for Transferring Parts from Belt Conveyors”, in [Dodd&Rossol79], pp. 81-97.

    Google Scholar 

  65. J.M. Hollerbach: “Dynamics”, in [Brady...82], pp. 51-71.

    Google Scholar 

  66. B.K.P. Horn: “Obtaining Shape from Shading Information”, in [Winston75], pp. 115-155.

    Google Scholar 

  67. B.K.P. Horn: “Understanding Image Intensities”, Artificial Intelligence 8 (1977) 201-231.

    Google Scholar 

  68. B.K.P. Horn, B.G. Shunck: “Determining Optical Flow” in [Brady81], pp. 185-204.

    Google Scholar 

  69. G.M. Hunter, K. Steiglitz: “Operations on Images Using Quad Trees”, IEEE Trans. PAMI-1 (1979) 145-153.

    Google Scholar 

  70. J. J. Hwang, E. L. Hall: “Matching of Featured Objects Using Relational Tables from Stereo Images”, Comp. Graphics Image Proc. 20 (1982) 22–42.

    Article  Google Scholar 

  71. 6th Intern. Conference on Pattern Recognition Oct. 1982, München IEEE Computer Society Press, Silver Spring/MD, USA 1982.

    Google Scholar 

  72. M. Idesawa: “A System to Generate a Solid Figure from Three Views”, Bulletin of the JSME 16 (1973) 216-225.

    Google Scholar 

  73. Proc. Intern. Joint Conference on Artificial Intelligence May 1969, Washington/DC USA, Univ. Microfilms Intern., Ann Arbor/MI USA [IJCAI81] Proc. 7th Intern. Joint Conference on Artificial Intelligence, August 1981, Vancouver/BC Canada, AAAI, Menlo-Park/CA USA 1981.

    Google Scholar 

  74. Proc. 8th Intern. Joint Conference on Artificial Intelligence, August 1983, Karlsruhe, im Druck [Ikeuchi&Horn81] K. Ikeuchi, B.K.P. Horn: “Numerical Shape from Shading and Occluding Boundaries”, in [Brady81], pp. 141-184.

    Google Scholar 

  75. Sensorsysteme zur Automatisierung der Produktion, 15. IPA Arbeitstagung, Nov. 1982 Stuttgart, IFS Ltd. Kempston/Bedford England, 1982.

    Google Scholar 

  76. M. Ishii, T. Nagata: “Feature Extraction of Three-Dimensional Objects and Visual Processing in a Hand-Eye System Using Laser Tracker”, Pattern Recognition 8 (1976) 229–237.

    Article  Google Scholar 

  77. 12th International Symposium on Industrial Robots; 6th International Conference on Industrial Robot Technology, Juni 1982 Paris, IFS Ltd. Kempston/Bedford England, 1982.

    Google Scholar 

  78. C.L. Jackins, S.L. Tanimoto: “Oct-trees and their Use in Representing 3-D Objects”, Comp. Graphics Image Proc. 14 91980) 249-270.

    Google Scholar 

  79. R. Jain: “Segmentation of Moving Observer Frame Sequences”, Pattern Recognition Letters 1 (1982) 115-120.

    Google Scholar 

  80. R. Jain: “Segmentation of Frame Sequence Obtained by a Moving Observer”, Bericht GMR-4247 General Motors Research Lab. Warren/MI USA 1983.

    Google Scholar 

  81. R.A. Jarvis: “A Perspective on Range Finding Techniques for Computer Vision”, IEEE Trans. PAMI-5 (1983) 122-139.

    Google Scholar 

  82. W. Jentner, E.J. Schmidberger: “Lösung von Aufgaben industrieller Qualitätsprüfung mittels Bildverarbeitungssystemen”, in [IPA82], pp. 191-202.

    Google Scholar 

  83. E. Johnston: “Spray Painting Random Shapes Using CCTV Camera Control”, in [RV81], pp. 187-192.

    Google Scholar 

  84. H. Kazmierczak (Hrsg.): “Erfassung und maschinelle Verarbeitung von Bilddaten”, Springer-Verlag, Wien New York 1980.

    Google Scholar 

  85. P. Kinnucan:“How Smart Robots becoming Smarter”, High Technology, Sept./Oct. 1981, 32-40.

    Google Scholar 

  86. P. Kinnucan: “Machines that see”, High Technology, April 1983, 30-36.

    Google Scholar 

  87. L. Kitchen: “Relaxation Applied to Matching Quantitative Relational Structures”, IEEE Trans. SMC-10 (1980) 96-101.

    Google Scholar 

  88. T. Kreis, H. Kreitlow, W. Jüptner: “Kantenfindung mit Hilfe eines kombinierten Lichtschnittverfahrens”, in [IPA82], pp. 11-20.

    Google Scholar 

  89. D.T. Lee: “The Optical Flow Field: The Foundation of Vision”, Phil. Trans. Royal Soc. London, B 290 (1980) 169–179.

    Article  Google Scholar 

  90. H.C. Lee, K.S. Fu: “A Computer Vision System for Generating Object Description”, in [PRIP82], pp. 466-472.

    Google Scholar 

  91. C.-H. Lee, A. Rosenfeld: “Albedo Estimation for Scene Segmentation”, Pattern Recognition Letters 1 (1983) 155–160.

    Article  MATH  Google Scholar 

  92. P. Levi, E. Weirich: “Lasergestützte Qualitätskontrolle mit synthetischen Bildern”, 5. DAGM-Symposium 1983, dieser Band.

    Google Scholar 

  93. P. Levi, H. Stiefvater, L. Vajta: “Integriertes Laser-Kamera System für die industrielle Bilderfassung”, 5. DAGM-Symposium 1983, dieser Band [Lozano-Perez82a] T. Lozano-Perez: “Task Planning”, in [Brady...82], pp. 473-498.

    Google Scholar 

  94. T. Lozano-Perez: “Automatic Planning of Manipulator Transfer Movements”, in [Brady...82], pp. 499-535.

    Google Scholar 

  95. J.Y.S. Luh: “An Anatomy of Industrial Robots and Their Controls”, IEEE Trans. AC-28 (1983) 133-152.

    Google Scholar 

  96. A.K. Mackworth: “Interpreting Pictures of Polyhedral Scenes”, Artificial Intelligence 4 (1973) 121–137.

    Article  Google Scholar 

  97. A.G. Makhlin: “Vision Controlled Assembly by a Multiple Manipulator Robot”, in [RV82], pp. 83-92.

    Google Scholar 

  98. D. Marr: “Representing Visual Information — a Computational Approach”, in [Hanson&Riseman78], pp. 61-80.

    Google Scholar 

  99. M.T. Mason: “Compliant Motion”, in [Brady...82], pp. 305-322.

    Google Scholar 

  100. J. McCarthy et al.: “A Computer with Hands, Eyes and Ears”, AFIPS Conf. Proc. FJCC 1968, pp. 329-338.

    Google Scholar 

  101. C.A. McPherson, J.B.K. Tio, F.A. Sadjadi, E.L. Hall: “Curved Surface Representation for Image Recognition”, in [PRIP82], pp. 363-369.

    Google Scholar 

  102. D.J. Meagher: “Efficient Synthetic Image Generation of Arbitrary 3-D Objects”, in [PRIP82], pp. 473-478.

    Google Scholar 

  103. T. Mimaroglu: “A High-Speed Two-Dimensional Hardware Convolver for Image Processing” in [PRIP82], pp. 386-389.

    Google Scholar 

  104. M.L. Minsky: “An Autonomus Manipulator System”, Project MAC Progress Report 111, MIT, Cambridge/MA, 1966.

    Google Scholar 

  105. H.P. Moravec: “Obstacle Avoidance and Navigation in the Real World by a Seeing Robot Rover”, Ph.D. Dissertation Stanford AIM-340, Stanford Univ. Sept. 1980.

    Google Scholar 

  106. H.-H. Nagel: “On Change Detection and Displacement Vector Estimation in Image Sequences”, Pattern Recognition Letters 1 (1982) 55–59

    Article  MATH  Google Scholar 

  107. H.-H. Nagel: “Displacement Vectors Derived from Second-Order Intensity Variations in Image Sequences”, Computer Vision, Graphics, and Image Processing 21 (1983) 85–117.

    Article  Google Scholar 

  108. H.-H. Nagel: “Constraints for the Estimation of Displacement Vectorfields from Image Sequences”, in [IJCAI83], im Druck [Neumann81] B. Neumann: “3D-Information aus mehrfachen Ansichten”, in [Radig81], pp. 93-111.

    Google Scholar 

  109. R. Niepold: “Ein Fernsehsensor zur Überwachung und Regelung von Schweißprozessen”, in [Steusloff80], pp. 166-183.

    Google Scholar 

  110. R. Niepold, Brünnen “Ein optisches System zur Überwachung und Regelung von Lichtbogenschweißprozessen”, in [IPA82], pp. 117-132.

    Google Scholar 

  111. T. Okada: “Development of an Optical Distance Sensor for Robots”, Robotics Research] 14 (1982) 3–14.

    Article  Google Scholar 

  112. K. Ossenberg: “Optische Sensorsysteme für industrielle Anwendungen”, in [Steusloff80], pp. 97-126.

    Google Scholar 

  113. W. Patzelt: “A Robot Position Control Algorithm for the Grip onto an Accelerated Conveyor Belt”, in [ISIR82], pp. 391-399.

    Google Scholar 

  114. T. Pavlidis: “Structural Pattern Recognition”, Springer-Verlag, Berlin Heidelberg New York, 1977.

    Google Scholar 

  115. W.A. Perkins: “A Model-Based Vision System for Industrial Parts”, IEEE Trans. C-27 M1978) 126-143.

    Google Scholar 

  116. K. Prazdny: “Egomotion and Relative Depth Map from Optical Flow”, Biological Cybernetics 36 (1980) 87–102.

    Article  MathSciNet  MATH  Google Scholar 

  117. Proc. Conference on Pattern Recognition and Image Processing, IEEE Computer Society Press, Silver Spring/MD, USA 1982.

    Google Scholar 

  118. A. Pugh: “Second Generation Robotics”, in [ISIR82], pp. 1-8.

    Google Scholar 

  119. B. Radig (Hrsg.): “Modelle und Strukturen”, 4. DAGM-Symposium, Hamburg 1981, Informatik Fachberichte 49, Springer-Verlag Berlin Heidelberg New York 1981.

    Google Scholar 

  120. B. Radig: “Symbolische Beschreibung von Bildfolgen I: Relationengebilde und Morphismen”, Bericht IfI-HH-B90/82 des Fachbereiches für Informatik der Universität Hamburg, 1982.

    Google Scholar 

  121. B. Radig: “Image Sequence Analysis Using Relational Structures”, Pattern Recognition (im Druck); Mitteilung IFI-HH-M-106 des Fachbereichs für Informatik der Universität Hamburg, 1983.

    Google Scholar 

  122. M.H. Raibert, J.E. Tanner: “A VLSI Tactile Array Sensor”, in [ISIR82], pp. 417-425.

    Google Scholar 

  123. M.H. Raibert, J.E. Tanner: “Design and Implementation of a VLSI Tactile Sensing Computer”, Robotics Research 1 3(1982) 3-18.

    Google Scholar 

  124. D.R. Reddy, R.W. Hon: “Computer Architecture for Vision”, in [Dodd&Rossol79], pp. 169-185.

    Google Scholar 

  125. A.A.G. Requicha: “Representation for Rigid Solids: Theory, Methods and Systems”, Computing Surveys 12 (1980) 437–464.

    Article  Google Scholar 

  126. Robot Vision and Sensory Controls, Proc. 1st Intern. Conference April 1981, Stratford-upon-Avon, UK, IFS Ltd. Kempston/Bedford England, 1981.

    Google Scholar 

  127. Robot Vision and Sensory Controls, Proc. 2nd International Conference Nov. 1982, Stuttgart, IFS Ltd. Kempston/Bedford England, 1982.

    Google Scholar 

  128. F. Röcker: “Zum Problem der automatischen Analyse dreidimensionaler Szenen”, Dissertation, Universität Karlsruhe, Nov. 1975.

    Google Scholar 

  129. A. Rohde: “Anwendung eines Bildanalysators in der Qualitätskontrolle”, in [IPA82], pp. 29-38.

    Google Scholar 

  130. C.A. Rosen: “Machine Vision and Robotics: Industrial Requirements”. in [Dodd&Rossol79], pp. 3-20.

    Google Scholar 

  131. A. Rosenfeld, L. S. Davis: “Image Segmentation and Image Models”, Proc. IEEE 67 (1979) 764-772.

    Google Scholar 

  132. M. Salmon, A. d’Auria: “Programmable Assembly System”, in [Dodd&Rossal79], pp. 153-163.

    Google Scholar 

  133. M. Schweizer, D. Haaf: “Taktile Sensoren und ihre Anwendung in programmierbaren Montagesystemen”, in [Steusloff80], pp. 184-199.

    Google Scholar 

  134. L. G. Shapiro, R. M. Haralick: “Structural Descriptions and Inexact Matching”, IEEE Trans. PAMI-3 (1981) 504-519.

    Google Scholar 

  135. Y. Shirai: “Three-Dimensional Computer Vision”, in [Dodd&Rossol79], pp. 187-205.

    Google Scholar 

  136. S.N. Srihari: “Representation of 3-D Digital Images”, ACM Comput. Surveys 13 (1981) 399-424.

    Google Scholar 

  137. S.N. Srihari: “Hierarchical Data Structures and Progressive Refinement of 3-D Images”, in [PRIP82], pp. 485-490.

    Google Scholar 

  138. G. Stein: “Automatische Strukturanalyse von Bildsignalen aufgrund rechnerinterner Modelle aus lokalen Formmerkmalen”, 5. DAGM-Symposium 1983, dieser Band [Steusloff80] H. Steusloff (Hrsg.): “Wege zu sehr fortgeschrittenen Handhabungsystemen”, Springer-Verlag, Berlin Heidelberg New York, 1980.

    Google Scholar 

  139. P.M. Taylor, K.K.W. Selke, G.E. Taylor: “Closed Loop Control of an Industrial Robot using Visual Feedback from a Sensor Gripper”, in [ISIR82], pp. 79-86.

    Google Scholar 

  140. J.M. Tenenbaum, H.G. Barrow, R.C. Bolles: “Prospects for Industrial Vision”, in [Dodd&Rosol79], pp. 239-256.

    Google Scholar 

  141. J.B.K. Tio, C.A. McPherson, E.L. Hall: “Curved Surface Measurement for Robot Vision”, in [PRIP82], pp. 370-378.

    Google Scholar 

  142. W.H. Tsai, K.S. Fu: “Subgraph Error-Correcting Isomorphisms for Syntactic Pattern Recognition”, IEEE Trans. SMC-13 (1983) 48-61.

    Google Scholar 

  143. K.J. Turner: “Computer Perception of Curved Objects Using a Television Camera”, Dissertation, Dept. of Machine Intelligence, University Edinburgh, 1974.

    Google Scholar 

  144. T. Uno, S. Ikeda, H. Ueda, M. Ejiri, T. Tokumaga: “An Industrial Eye that Recognizes Hole Positions in a Water Pump Testing Process”, in [Dodd&Rossol79], pp. 101-114.

    Google Scholar 

  145. P. Villers: “Present Industrial Use of Vision Sensors for Robot Guidance”, in [ISIR82], pp. 291-302.

    Google Scholar 

  146. F. Wahl, H. Giebel, L. Abele: “Texturanalyseverfahren zur Fehlermessung bei Glasbehältern”, in [Radig81], pp. 303-309.

    Google Scholar 

  147. I. Walter, H. Tropf: “Erweiterte Übergangsnetze als Modell zur 3-D Erkennung von Werkstücken in Einzelbildern”, 5. DAGM-Symposium 1983, dieser Band.

    Google Scholar 

  148. H.-J. Warnecke, K. Melchior: “Bildverarbeitung als Mittel zur Automatisierung”, in [IPA82], pp 1-10.

    Google Scholar 

  149. H.-J. Warnecke, M. Schweizer, I. Schmidt: “Computer Controlled Magazining System”, in [ISIR82], pp. 197-216.

    Google Scholar 

  150. P.H. Winston (Hrsg.): “Psychology of Computer Vision”, McGraw-Hill, New York, 1975.

    Google Scholar 

  151. A. P. Witkin: “Recovering Surface Shape and Orientation from Texture”, in [Brady81], pp. 17-45.

    Google Scholar 

  152. R. J. Woodham: “Analyzing Images of Curved Surfaces”, in [Brady81], pp. 117-140.

    Google Scholar 

  153. Y. ‘Yakomovsky, R. Cunningham: “DABI — A Data Base for Image Analysis with Nondeterministic Inference Capability”, in [Chen76], pp. 554-592.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 1983 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Raoig, B. (1983). 2D- und 3D-Objektbeschreibung für Sichtsystehe. In: Mustererkennung 1983. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-36430-7_45

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-36430-7_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-8007-1334-9

  • Online ISBN: 978-3-662-36430-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics