Skip to main content
SpringerLink
Log in

Models and Structures in Image Processing

  • Conference paper
GWAI-81

Part of the book series: Informatik-Fachberichte ((2252,volume 47))

Abstract

“AI is the ‘study of how to use knowledge to achieve intelligent action, which often implies selection from a large space of alternatives’. Vision and speech are two problems which require the application of diverse sources of knowledge, including both symbolic knowledge and knowledge of the signal space, to the interpretation of a noisy signal (image or speech waveform). AI systems which solve vision and speech problems differ from purely symbolic problem solving systems since they must explicitly deal with errors, noise, and uncertainty in the input data.” [REDDY ROSENFELD 79]

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

Access this chapter

Log in via an institution
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 54.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. M. L. Baird, M. D. Kelly: “Recognizing Objects by Rules of Inference on Sequentially Thresholded Gray-Level Pictures”, Comp. Graphics Image Proc. 3 (1974) 1–22.

    Article  Google Scholar 

  2. H. G. Barrow, A. P. Ambler, R. M. Burstall: “Some Techniques for Recognizing Structures in Pictures”, in Frontiers of Pattern Recognition, S. Watanabe (ed.), Academic Press, New York 1972.

    Google Scholar 

  3. H. G. Barrow, R. M. Burstall: “Subgraph Isomorphism, Matching Relational Structures and Maximal Cliques”, Information Proc. Letters 4 (1976) 83–84.

    Article  MATH  Google Scholar 

  4. H G. Barrow, J. M. Tenenbaum: “Recovering Intrinsic Scene Characteristics from Images”, in Computer Vision Systems, A. R. Hanson, E. M. Riseman (eds.), Academic Press, New York 1978.

    Google Scholar 

  5. R. Bertelsmeier, G. Hille: “Anwendungen von Bildanalysetechniken zur automatischen Sichtkontrolle von Bauteilen im Automobilbau”, in Angewandte Szenenanalyse, J. P. Foith (ed.), Informatik Fachberichte 20, Springer Berlin-Heidelberg-New York 1979.

    Chapter  Google Scholar 

  6. R. Bertelsmeier, B. Radig: “Kontextunterstützte Analyse von Szenen mit bewegten Objecten”, GI/NTG Fachtagung Digitale Bildverarbeitung, H.-H. Nagel (ed.), München Mar. 28–30, 1977, Informatik Fachberichte 8, 101–128, Springer Berlin-Heidelberg-New York 1977.

    Google Scholar 

  7. R. Bertelsmeier, B. Radig: “Context Guided Analysis of Scenes With Moving Objects”, Report IFI-HH-B-41/77, Fachbereich Informatik, Univ. Hamburg, Feb. 1977.

    Google Scholar 

  8. M. Böhm, U. Obermöller, K. H. Höhne: “Determination of Heart Dynamics from X-Ray and Ultrasound Image Sequences”, ICPR-80, Miami Beach, Dec. 1–4, 1980, 403–408.

    Google Scholar 

  9. M. Brady: “Artificial Intelligence Approaches to Image Understanding”, Nato Adv. Study Inst. on Pattern Recognition Theory and Applications, Oxford, March 29 — April 11, 1981.

    Google Scholar 

  10. R. Brennecke, H. J. Hahne, P. H. Heintzen: “A Multiprocessor-System for the Acquisition and Analysis of Video Image Sequences”, in Erzeugung und Analyse von Bildern und Strukturen, S. J. Pöppl, H. Platzer (eds.), Informatik Fachberichte 29, Springer Berlin-Heidelberg-New York 1980.

    Chapter  Google Scholar 

  11. R. A. Brooks, R. Greiner, T. O. Binford: “The ACRONYM Model-Based Vision System”, IJCAI-79, Tokyo, Aug. 20–23, 1979, 105–113.

    Google Scholar 

  12. J.-K. Cheng, T. S. Huang: “Algorithms for Matching Relational Structures and their Applications to Image Processing”, Report TR-EE 80–53, School of Electr. Engg., Purdue Univ., Dec. 1980.

    Google Scholar 

  13. L. S. Davis: “A Survey of Edge Detection Techniques”, Comp. Graphics Image Proc. 4 (1975) 248–270.

    Article  Google Scholar 

  14. L. Dreschler, H.-H. Nagel: “On the Frame-to-Frame Correspondence between Greyvalue Characteristics in the Images of Moving Objects”, this volume.

    Google Scholar 

  15. R. W. Ehrich, J. P. Foith: “Topology and Semantics of Intensity Arrays”, in Computer Vision Systems, A. R. Hanson, E. M. Riseman (eds.), Academic Press, New York 1978.

    Google Scholar 

  16. K. S. Fu: “Recent Advantages in Syntactic Pattern Recognition”, IJCPR-78, Kyoto, Nov. 7–10, 1978, 95–105.

    Google Scholar 

  17. K. S. Fu, J. K. Mui: “A Survey on Image Segmentation”, Pattern Recognition 13 (1981) 3–16.

    Article  MathSciNet  Google Scholar 

  18. A. R. Hanson, E. M. Riseman: “The Design of a Semantically Directed Vision Processor”, COINS Technical Report 75C-l, Univ. of Massachusets, 1975.

    Google Scholar 

  19. A. R. Hanson, E. M. Riseman: “Segmentation of Natural Scenes”, in Computer Vision Systems, A. R. Hanson, E. M. Riseman (eds.), Academic Press, New York 1978.

    Google Scholar 

  20. Y. Hara, K. Okamoto, T. Hamada, N. Akiyama: “Automatic Visual Inspection of LSI Photomasks”, ICPR-80, Miami Beach, Dec. 1–4, 1980, 273–279.

    Google Scholar 

  21. R. M. Haralick: “Scene Analysis, Arrangements, and Homomorphisms”, in Computer Vision Systems, A. R. Hanson, E. M. Riseman (eds.), Academic Press, New York 1978.

    Google Scholar 

  22. R. M. Haralick: “Edge and Region Analysis for Digital Image Data”, Comp. Graphics Image Proc. 12 (1980) 60–79.

    Article  Google Scholar 

  23. P. E. Hart, N. J. Nilsson, B. Raphael: “A Formal Basis for the Heuristic Determination of Minimum Cost Paths”, IEEE Trans. Sys. Sci. Cyber. SSC-4 (1968) 100–107, and corrections in SIGART Newsletter No. 37, Dec. 1972, 28–29; see also D. Gelperin: “On the Optimality of A*”, Artificial Intelligence 8 (1977) 69–76.

    Article  Google Scholar 

  24. P. H. Heintzen, J. H. Bürsch (eds.): “Roentgen-Video-Techniques for Dynamic Studies of Structure and Function of the Heart and Circulation”, Georg Thieme Verlag, Stuttgart 1978.

    Google Scholar 

  25. G. T. Herman: “Image Reconstruction from Projections”, Academic Press, New York 1980.

    MATH  Google Scholar 

  26. G. Heygster: “Two-Dimensional Rank Filters — Deterministic and Spectral Properties”, ICPR-80, Miami Beach, Dec. 1–4, 1980, 1165–1167.

    Google Scholar 

  27. G. Hille: “Methoden und Modelle in der Bildsegmentation — Eine Ubersicht”, Fachbereich Informatik, Univ. Hamburg, in preparation.

    Google Scholar 

  28. F. Holdermann, H. Kazmierczak: “Preprocessing of Gray Scale Pictures”, Comp. Graphics Image Proc. 1 (1972) 66–80.

    Article  Google Scholar 

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

    Article  MATH  Google Scholar 

  30. C. J. Jacobus, R. T. Chien, J. M. Selander: “Motion Detection and Analysis of Matching Graphs of Intermediate-Level Primitives”, IEEE Trans. Pattern Anal. Mach. Intell. PAMI-2 (1980) 495–510.

    Google Scholar 

  31. R. Jain, H.-H. Nagel: “On the Analysis of Accumulative Difference Pictures from Image Sequences of Real World Scenes”, IEEE Trans. Pattern Anal. Mach. Intell. PAMI-1 (1979) 206–214.

    Article  Google Scholar 

  32. T. Kanade: “Region Segmentation: Signal vs Semantics”, Comp. Graphics Image Proc. 13 (1980) 279–297.

    Article  MathSciNet  MATH  Google Scholar 

  33. L. N. Kanal: “Problem-Solving Models and Search Strategies for Pattern Recognition”, IEEE Trans. Pattern Analysis Machine Intell. PAMI-1 (1979) 193–201.

    Article  Google Scholar 

  34. M. D. Kelly: “Visual Identification of Peoples by Computer”, Memo AI-130, Comp. Sc. Dept. Stanford Univ. 1970.

    Google Scholar 

  35. R. Kraasch, W. Zach: “Dreidimensionale Beschreibung einfacher bewegter Gegenstände”, Diploma thesis, Fachbereich Informatik, Univ. Hamburg, July 1979.

    Google Scholar 

  36. M. D. Levine: “A Knowledge-Based Computer Vision System”, in Computer Vision Systems, A. R. Hanson, E. M. Riseman (eds.), Academic Press, New York 1978.

    Google Scholar 

  37. D. Marr: “Early Processing of Visual Information”, Memo AI-340, MIT Cambridge /MA, Dec. 1975, and Phil. Trans. Royal Society, Series B, 275 (1976) 483–524.

    Google Scholar 

  38. A. Martelli: “An Application of Heuristic Search Methods to Edge and Contour Detection”, C.ACM 19 (1976) 73–83.

    Article  MATH  Google Scholar 

  39. R. Mohr, J.-P. Haton: “A Parsing Algorithm for Imperfect Patterns and its Application to Speech and Image Recognition”, talk given at IJCPR-76, published as Report 76-R-018, Univ. de Nancy I, 1976.

    Google Scholar 

  40. R. Mohr, G. Masini: “Knowledge Directed Recognition: A Syntactical Approach”, ICPR-80, Miami Beach, Dec. 1–4, 1980, 337–339.

    Google Scholar 

  41. M. Nagao, T. Matsuyama: “Edge Preserving Smoothing”, Comp. Graphics Image Proc. 9 (1979) 394–407.

    Article  Google Scholar 

  42. H.-H. Nagel: “Uber die Repräsentation von Wissen zur Auswertung von Bildern”, in Angewandte Szenenanalyse, J. P. Foith (ed.), Informatik Fachberichte 20, Springer Berlin-Heidelberg-New York 1979.

    Chapter  Google Scholar 

  43. H.-H. Nagel: “Image Sequence Analysis: What Can we Learn from Applications?”, to appear in Image Sequence Analysis, T. S. Huang (ed.) Springer Berlin-Heidelberg-New York 1981; and Report IFI-HH-M-79/80, Fachbereich Informatik, Univ. Hamburg, 1980.

    Google Scholar 

  44. R. Nevatia, K. Price: “Locating Structures in Areal Images”, ICPR-80, Miami Beach, Dec. 1–4, 1980, 686–690.

    Google Scholar 

  45. A. Newell, G. Ernst: “The Search for Generality”, Proc. IFIP Congress 65, W. A. Kalenich (ed.), Spartan Books, Washington D.C., and Macmillan, London, 1965.

    Google Scholar 

  46. H. Niemann: “Hierarchical Graphs in Pattern Analysis”, ICPR-80, Miami Beach, Dec. 1–4, 1980, 213–216; see also “Zur Repräsentation von Kontrollstrukturen und Wissen in der Musteranalyse”, in Erzeugung und Analyse von Bildern und Strukturen, S. J. Pö l, H. Platzer (eds.),), Informatik Fachberichte 29, Springer Berlin-Heidelberg-New York 1980.

    Google Scholar 

  47. N. J. Nilsson: “Problem-Solving Methods in Artificial Intelligence”, McGraw Hill, New York 1971.

    Google Scholar 

  48. Y. I. Ohta, T. Kanade, T. Sakai: “Color Information for Region Segmentation”, Comp. Graphics Image Proc. 13 (1980) 222–241.

    Article  Google Scholar 

  49. M. Onoe, K. Preston, A. Rosenfeld (eds.): “Real-Time Medical Image Processing”, Plenum Press, New York 1980.

    Google Scholar 

  50. F. P. Preparata, S. R. Ray: “An Approach to Artificial Nonsymbolic Cognition”, Information Sciences 4 (1972) 65–86.

    MATH  Google Scholar 

  51. B. Radig: “Parameterized Region Extraction for the Description of Moving Objects”, Proc. AISB/GI Conf. on Artificial Intelligence, Hamburg, July 18–20, 1978.

    Google Scholar 

  52. B. Radig, H.-H. Nagel: “Evaluation of Image Sequences: A Look Beyond Applications”, Nato Adv. Study Inst. on Digital Image Proc. and Anal., Bonas, France, June 23 — July 4, 1980, published by INRIA, to be published by Reidel.

    Google Scholar 

  53. B. Radig, R. Kraasch, W. Zach: “Matching Symbolic Descriptions for 3-D Reconstruction of Simple Moving Objects”, ICPR-80, Miami Beach, Dec. 1–4, 1980, 1081–1084.

    Google Scholar 

  54. B. Radig: “Image Region Extraction of Moving Objects”, to appear in Image Sequence Analysis, T. S. Huang (ed.), Springer Berlin-Heidelberg-New York 1981.

    Google Scholar 

  55. R. Reddy, A. Rosenfeld: Final Report on Workshop on Control Structures and Knowledge Representation for Image and Speech Understanding, April 3–4, 1979, Center for Adult Education, Univ. of Maryland, College Park.

    Google Scholar 

  56. E. M. Riseman, M. A. Arbib: “Segmentation of Static Scenes”, Comp. Graphics Image Proc. 6 (1977) 221–276.

    Article  Google Scholar 

  57. A. Rosenfeld, R. A. Hummel, S. W. Zucker: “Scene Labeling by Relaxation Operation”, IEEE Trans. System, Man, Cybernetics SMC-6 (1976) 420–433

    Google Scholar 

  58. A. Rosenfeld, A. C. Kak: “Digital Picture Processing”, Academic Press, New York 1976.

    Book  Google Scholar 

  59. U. Shani: “A 3-D Model-Driven System for the Recognition of Abdominal Anatomy from CT Scans”, ICPR-80, Miami Beach, Dec. 1–4, 1980, 585–590.

    Google Scholar 

  60. L. G. Shapiro, R. M. Haralick: “Algorithms for Inexact Matching”, ICPR-80, Miami Beach, Dec. 1–4, 1980, 202–207.

    Google Scholar 

  61. M. O. Shneier: “A Compact Relational Structure Representation”, IJCAI-79, Tokyo, Aug. 20–23, 1979, 818–826.

    Google Scholar 

  62. J. M. Tenenbaum, H. G. Barrow: “IGS: A Paradigm for Integrating Image Segmentation and Interpretation”, in Pattern Recognition and Artificial Intelligence, C. H. Chen (ed.), Academic Press, New York 1976

    Google Scholar 

  63. J. M. Tenenbaum, H. G. Barrow: “Experiments in Interpretation Guided Segmentation”, Artificial Intelligence 8 (1977) 241–274.

    Article  Google Scholar 

  64. E. E. Triendl: “How to Get the Edge into the Map”, IJCPR-78, Kyoto, Nov. 7–10, 1978, 946–950.

    Google Scholar 

  65. H. Tropf: “Analysis-By-Synthesis Search for Semantic Segmentation — Applied to Workpiece Recognition”, ICPR-80, Miami Beach, Dec. 1–4, 1980, 1165–1167.

    Google Scholar 

  66. D. Waltz: “Generating Semantic Descriptions from Drawings of Scenes with Shadows”, in The Psychology of Computer Vision, P. H. Winston (ed.), McGraw Hill, New York 1975.

    Google Scholar 

  67. P. H. Winston: “Learning Structural Descriptions from Examples”, in The Psychology of Computer Vision, P. H. Winston (ed.), McGraw Hill, New York 1975.

    Google Scholar 

  68. E. H. Wood: “New Horizons for Study of the Cardiopulmonary and Circulatory Systems”, Chest 69 (1976) 394–408.

    Article  Google Scholar 

  69. K. C. You, K. S. Fu: “A Syntactic Approach to Shape Recognition Using Attributed Grammars”, IEEE Trans. System, Man, Cybernetics SMC-9 (1979) 334–344.

    Google Scholar 

  70. S. W. Zucker, A. Rosenfeld, L.-S. Davis: “General Purpose Models: Expectations About the Unexpected”, IJCAI-75, Tbilisi, Sept. 3–8, 1975, 716–721.

    Google Scholar 

  71. S. W. Zucker: “Region Growing: Childhood and Adolescence”, Comp. Graphics Image Proc. 5 (1976) 382–393.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Fachbereich Informatik, Universität Hamburg, Germany

    B. Radig

Authors
  1. B. Radig
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institut für Informatik I, Universität Karlsruhe, Postfach 6380, 7500, Karlsruhe 1, Germany

    Jörg H. Siekmann

Rights and permissions

Reprints and permissions

Copyright information

© 1981 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Radig, B. (1981). Models and Structures in Image Processing. In: Siekmann, J.H. (eds) GWAI-81. Informatik-Fachberichte, vol 47. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-02328-0_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-02328-0_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-10859-7

  • Online ISBN: 978-3-662-02328-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation