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Signed Euclidean Distance Transform Applied to Shape Analysis

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Issues on Machine Vision

Part of the book series: International Centre for Mechanical Sciences ((CISM,volume 307))

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Abstract

The signed Euclidean distance transform is a modified version of Danielsson’s Euclidean distance transform [1]. This distance transform produces a distance map in which each pixel is a vector of two integer components. If a distance map is created inside the objects, the two integer values of a pixel in the distance map represent the displacements of the pixel from the nearest background point in x and y directions, respectively. The unique feature of this distance transform that a vector in the distance map is always pointing to the nearest background point is exploited in several applications, such as the detection of dominant points in digital curves, curve smoothing, computing Dirichlet tessellations and finding convex hulls.

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References

  1. Danielsson, P.E.: “Euclidean Distance Mapping”, Computer Graphics and Image Processing 14, 1980, pp. 227–248.

    Article  Google Scholar 

  2. Borgefors, G.: “Distance Transformations in Arbitrary Dimensions”, Computer Vision, Graphics and Image Processing 27, 1984, pp. 321–345.

    Google Scholar 

  3. Borgefors, G.: “Distance Transformations in Digital Images”, Computer Vision, Graphics and Image Processing 34, No.3, 1986, pp. 344–371.

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  4. Rosenfeld, A. and J.S. Weszka: “An Improved Method of Angle Detection on Digital Curves”, IEEE Trans. Comput., Vol. C-24, 1975, pp. 940–941.

    Article  Google Scholar 

  5. Sankar, P.V. and C.V. Sharma: “A Parallel Procedure for the Detection of Dominant Points on a Digital Curve”, Computer Graphics and Image Processing 7, 1978, pp. 403–412.

    Article  Google Scholar 

  6. Wall, K. and P.E. Danielsson: “A Fast Sequential Method for Polygonal Approximation of Digitized Curves”, Computer Graphics and Image Processing 28, 1984, pp. 220–227.

    Article  Google Scholar 

  7. Ahuja, N. and B.J. Schachter: Pattern Models, John Wiley & Sons, New York, 1983.

    Google Scholar 

  8. Borgefors, G.: “Distance Transformations in Digital Images”, FOA report, C 30401-E1, August 1985.

    Google Scholar 

  9. Rosenfeld, A. and A.C. Kak: Digital Picture Processing, Academic Press, Ice, New York, 1982.

    Google Scholar 

  10. Duda, R.O. and P.E. Hart: Pattern Classification and Scene Analysis, John Wiley, New York, 1973.

    MATH  Google Scholar 

  11. Sklansky, J.: “Measuring Concavity on a rectangular mosaic”, IEEE Trans. Computers, Vol. C-21, December 1972, pp. 1355–1364.

    Google Scholar 

  12. Ye, Q.Z.: “A Convex Hull Algorithm Using the Signed Euclidean Distance Transform”, Internal Report, LiTH-ISY-I-0919, Dept. of EE, Linöping University, April 1988.

    Google Scholar 

  13. Yamada, H.: “Complete Euclidean Distance Transformation by Parallel Operation”, Proc. of 7th Int. Conf. on Pattern Recognition, Montreal, Canada, July 1984, pp. 69–71.

    Google Scholar 

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© 1989 Springer-Verlag Wien

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Ye, QZ. (1989). Signed Euclidean Distance Transform Applied to Shape Analysis. In: Pieroni, G.G. (eds) Issues on Machine Vision. International Centre for Mechanical Sciences, vol 307. Springer, Vienna. https://doi.org/10.1007/978-3-7091-2830-5_16

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  • DOI: https://doi.org/10.1007/978-3-7091-2830-5_16

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-82148-0

  • Online ISBN: 978-3-7091-2830-5

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