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Segmentation by Shape Discrimination Using Spatial Filtering Techniques

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Digital Image Processing

Part of the book series: NATO Advanced Study Institutes Series ((ASIC,volume 77))

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Abstract

Zadeh (4) introduced the notion of fuzzy set theory and Goetcherian (6) showed how fuzzy logic could extend a variety of binary image processes into a multi-valued (grey image) domain. This paper introduces the basics of fuzzy set theory and discusses the suitability of the physically parallel CLIP machine for implementing the multi-valued operators. A form of spatial filtering is explained and its application to shape discrimination and image segmentation is shown. Finally, an application to a real image processing problem is illustrated.

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References

  1. Unger, S. H.: A computer oriented towards spatial problems, 1958, Proc. IRE 46(10), pp. 1744–1750.

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  2. Duff, M. J. B.: CLIP 4: A large scale integrated circuit array parallel processor, 1976, Proc, 3rd IJCPR, pp. 728–733.

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  5. Nakagawa, Y., and Rosenfeld, A.: A note on the use of local min and max operations in digital picture processing, 1978, IEEE Trans. SMC-8, pp. 632–635.

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  6. Goetcherian, V.: From binary to grey tone image processing using fuzzy logic concepts, 1980, Patt. Recog. 12, pp. 7–15.

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© 1981 D. Reidel Publishing Company

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Pass, S.D. (1981). Segmentation by Shape Discrimination Using Spatial Filtering Techniques. In: Simon, J.C., Haralick, R.M. (eds) Digital Image Processing. NATO Advanced Study Institutes Series, vol 77. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-8543-8_14

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  • DOI: https://doi.org/10.1007/978-94-009-8543-8_14

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-009-8545-2

  • Online ISBN: 978-94-009-8543-8

  • eBook Packages: Springer Book Archive

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