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Shape Analysis Based on Boundary Curve Segmentation

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Real-Time Object Measurement and Classification

Part of the book series: NATO ASI Series ((NATO ASI F,volume 42))

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Abstract

For industrial shapes of objects to be analyzed in a factory environment, it is reasonable to assume that the silhouette boundary supplies sufficient information for the identification of the object. This boundary can be represented in a coordinate system that will make it independent of scale change, rotation and translation and then this representation can be used for comparison to the prototypes of known classes.

In this paper a method is given by which the boundary curve is partitioned into “segments” that can be represented individually by single-valued functions in a polar coordinate system.The number and “angular spans” of those segments are used as the first distinguishing criteria between the objects. If this process is not sufficient for recognition, a truncated version of the Fourier series of each segment is used for final recognition.

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References

  1. Fu, K.S., Syntactic Methods in Pattern Recognition, Academic Press, 1974.

    Google Scholar 

  2. Fu, K.S., (Editor) Syntactic Pattern Recognition, Applications, Springer-Verlag, 1977.

    Google Scholar 

  3. Pavlidis, T. Structural Pattern Recognition, Springer-Verlag, 2 nd Edition 1980.

    Google Scholar 

  4. Smith S.P. and Jain A.K., “Chord distributions for shape matching”, Computer Graphics and Image Processing, 20, pp. 259–271, 1982.

    Article  Google Scholar 

  5. Pavlidis, T., “Polygonal approximations by Newton’s Method”, IEEE Trans. Computers, Vol.C-26, pp.800–807, 1977.

    Article  Google Scholar 

  6. Freeman H., “On the encoding of arbitriary geometric configurations”, IRE Trans. Elec. Comp. EC-10, pp.260–268, 1961.

    Article  MathSciNet  Google Scholar 

  7. Freeman H., “Boundary encoding and processing”, Picture Processing, and Psychopictorics, ed. by B.S. Lipkin, A. Rosenfeld, Academic Press, New York, pp.241–266, 1970.

    Google Scholar 

  8. Lendey, R.S. “High-speed automatic analysis of biomedical pictures”, Science 146, pp.216–223, 1964.

    Article  Google Scholar 

  9. Pavlidis, T. and Ali, F., “Computer recognition of handwritten numerals by polygonal approximations”, IEEE Trans. Systems, Man & Cybernetics, Vol.SMC-5, pp.610–614, 1975.

    Article  MATH  Google Scholar 

  10. Cooper, D.B. and Yalabik, N., “On the cost approximating and recognizing a noise perturbed straight line or a quadratic curve segment in the plane”, IEEE Trans. Computers Vol.C-25, pp.1020–1032, 1976.

    Article  MathSciNet  Google Scholar 

  11. R.O. Duda, P.E. Hart, Pattern Classification and Scene Analysis Wiley, New York (1973).

    Google Scholar 

  12. C.T. Zahn and R.Z. Roskies, “Fourier Descriptors for Plane Closed Curves”, IEEE Trans. on Computers, Vol.C-21,(1972), pp.269–281.

    Article  MathSciNet  Google Scholar 

  13. E. Persoon and K.S. Fu, “Shape Discrimination Using Fourier Descriptors”, IEEE Trans. on Systems, Man and Cybernetics, Vol.SMC-7 (1977), pp.170–179

    Article  MathSciNet  Google Scholar 

  14. Strackee, J. and Nagelkerke, J.D. “On closing the Fourier descriptor presentation”, IEEE Trans. on Pattern Anal., Mach. Intell, Vol.PAM 1–5, No.6, November 1983.

    Google Scholar 

  15. Uesaka, Y., “A new Fourier descriptor applicable to open curves”, Electronics and Communications in Japan, Vol.67-A, pp.166–173, March 1984.

    MathSciNet  Google Scholar 

  16. Denizhan, Y., Istefanopulos, Y. and Panayirci, E., “Boundary curve segmentation for shape recognition”, Proc. Seventh IASTED International Symposium on Measurement and Control, pp. 41–45, July 23–25, 1985.

    Google Scholar 

  17. Dubois, S.R. and Glang, F.H. “An autoregressive model approach to two-dimensional shape classification” IEEE Trans. on Pattern Anal. Mach. Intell., Vol. PAMI-8, No. 1, pp. 55–66, January 1986.

    Article  Google Scholar 

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© 1988 Springer-Verlag Berlin Heidelberg

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Panayirci, E., Denizhan, Y. (1988). Shape Analysis Based on Boundary Curve Segmentation. In: Jain, A.K. (eds) Real-Time Object Measurement and Classification. NATO ASI Series, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83325-0_9

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  • DOI: https://doi.org/10.1007/978-3-642-83325-0_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-83327-4

  • Online ISBN: 978-3-642-83325-0

  • eBook Packages: Springer Book Archive

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