Computational Algorithms for Interactive Pattern Recognition

  • Y. T. Chien


Until recently, digital computers have been used in the design of pattern recognition systems largely for the purpose of simulating or testing computational algorithms before they are implemented in the way of hardware. The evolving use of computer graphics, however, has changed the computer’s role significantly. In the past few years, the need for man-machine interaction in data analysis and algorithm synthesis has become increasingly evident to anyone who has undertaken a serious pattern recognition problem. Like many computer-aided systems, the interactive approach allows the speed and accuracy of a computer to be combined with man’s ability and intuition at various stages of the pattern recognition process. This approach is particularly desirable whenever one is faced with a large data base of which analytic and statistical properties must be calculated dynamically and in real time. In the event of minimum prior knowledge regarding the data base, man-machine interplay via some graphical medium often becomes a necessity.


Mapping Algorithm Pattern Sample Pattern Recognition Problem Pattern Recognition System Human Observation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    H.C. ANDREWS, Introduction to Mathematical Techniques in Pattern Recognition, Wiley-Interscience, 1972.Google Scholar
  2. 2.
    G.H. BALL, “A Comparison of Some Cluster-Seeking Techniques”, RADC-TR-66–514, November, 1966.Google Scholar
  3. 3.
    G.H. BALL, et al., “Implications of Interactive Graphic Computers for Pattern Recognition Methodology”, Methodologies of Pattern Recognition (ed. S. WATARABE), Academic Press, 1969, pp. 23–31.Google Scholar
  4. 4.
    THOMAS W. CALVERT, “Nonorthogonal Projections for Feature Extraction in Pattern Recognition” IEEE Trans, on Computers, C-19, 5, May 1970, pp. 447–452.Google Scholar
  5. 5.
    THOMAS W. CALVERT, “Projections of Multidimensional Data for Use in Man-Computer Graphics”, Proc. Fall Joint Computer Conference, 1968, pp. 227–231.Google Scholar
  6. 6.
    THOMAS W. CALVERT and T.Y. YOUNG, “Randomly Generated Nonlinear Transformations for Pattern Recognition”, IEEE Trans, on Systems Science and Cybernetics, SSC-5, 4, Oct. 1969, pp. 266–273.Google Scholar
  7. 7.
    C.L. CHANG and R.C. Lee, “A Heuristic Relaxation Method for Nonlinear Mapping in Cluster Analysis”, IEEE Transactions on Systems, Man and Cybernetics, March 1973, pp. 197–200.Google Scholar
  8. 8.
    Y.T. CHIEN, “Interactive Pattern Recognition “A Review and Outlook”, Proc. 11th IEEE Symposium on Adaptive Processes, December 1972, pp. 106–110.Google Scholar
  9. 9.
    Y.T. CHIEN and K.S. FU., “Selection and Ordering of Feature Observations in a Pattern Recognition System”, Information and Control, 12, 1968, pp. 394–415.CrossRefGoogle Scholar
  10. 10.
    N.M. HERBST and P.M. WILL, “An Experimental Laboratory for Pattern Recognition and Signal Processing”, Communications of the ACM, 15, 4, April 1972, pp. 231–244.CrossRefGoogle Scholar
  11. 11.
    L.N. KANAL, “Interactive Pattern Analysis and Classification System: A Survey and Commentary”, Proc. IEEE, 60–10, October 1972, pp. 1200–1215.CrossRefGoogle Scholar
  12. 12.
    E.A. PATRICK and F.P. FISCHER, II., “Cluster Mapping with Experimental Computer Graphics”, IEEE Trans, on Computers, C-18, 11, Nov. 1969, pp. 987–991.CrossRefGoogle Scholar
  13. 13.
    E.A. PATRICK and L.Y. SHEN, “Interactive Use of Problem Knowledge for Clustering and Decision-Making”, IEEE Trans, on Computers, 20, 2, Feb. 1971, pp. 216–222.CrossRefGoogle Scholar
  14. 14.
    E.A. PATRICK, et al., “Mapping Multidimensional Space to One Dimension for Computer Output Display”, IEEE Trans. Computers, 17, Oct. 1968, pp. 949–953.CrossRefGoogle Scholar
  15. 15.
    KENDALL PRESTON, JR., and P.E. NORGREN, “Interactive Image Processor Speeds Pattern Recognition by Computer”, Electronics, Oct. 1972.Google Scholar
  16. 16.
    JOHN W. SAMMON, JR., “A Nonlinear Mapping for Data Structure Analysis”, IEEE Trans, on Computers, C-18, 5, May 1969, pp. 401–409.Google Scholar
  17. 17.
    JOHN W. SAMMON, JR., “Interactive Pattern Analysis and Classification”, IEEE Trans, on Computers, C-19, 7, July 1970, pp. 594–616.Google Scholar
  18. 18.
    JOHN W. SAMMON, JR., et al., “Programs for On-Line Pattern Analysis”, Vol. I, and II, RADC-TR-71–177, September 1971.Google Scholar
  19. 19.
    JOHN W. SAMMON, JR., A.H. PROCTOR and D.F. ROBERTS, “An interactl ve-Graphic Subsystem for Pattern Analysis”, Pattern Recognition, 3, 1971, pp. 37–52.CrossRefGoogle Scholar
  20. 20.
    G.S. SUBESTYEN, Decision-Making Processes in Pattern Recogniti on, The Macmillan Company, 1962.Google Scholar

Copyright information

© Plenum Press, New York 1974

Authors and Affiliations

  • Y. T. Chien
    • 1
  1. 1.The University of ConnecticutStorrsUSA

Personalised recommendations