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A Novel Approach for Computation of Morphological Operations Using the Number Theoretic Transform

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Discrete Geometry and Mathematical Morphology (DGMM 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13493))

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Abstract

The fundamental operations of mathematical morphology are dilation and erosion. They are often implemented using a sliding window with the purpose to compute maximum respectively minimum of pixel values within the corresponding mask.

We reformulate the problem of morphological dilation respectively erosion of an image with a non-flat filter as a convolution of their umbras. To this end, we propose to make use of the number theoretic transform to compute the convolution in this setting. In contrast to other possible schemes, this transform represents a completely discrete computational approach. It allows exact convolution of sequences made up of integers. Therefore we propose by the combination of umbra framework and number theoretic transform a well-engineered combination.

There is no restriction on size or shape of the structuring element, and also flat and non-flat filters can be realised.

The current work was supported by the European Regional Development Fund (EFRE 85037495). Furthermore, the authors acknowledge the support by BTU Graduate Research School (STIBET short-term scholarship for international PhD Students sponsored by the German Academic Exchange Service (DAAD) with funds of the German Federal Foreign Office).

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References

  1. Agarwal, R.C., Burrus, C.S.: Number theoretic transforms to implement fast digital convolution. Proc. IEEE 63(4), 550–560 (1975)

    Article  MathSciNet  Google Scholar 

  2. Harris, C.R., et al.: Array programming with NumPy. Nature 585(7825), 357–362 (2020)

    Article  Google Scholar 

  3. Tuzikov, A.V., Margolin, G.L., Grenov, A.I.: Convex set symmetry measurement via Minkowski addition. J. Math. Imaging Vis. 7(1), 53–68 (1997)

    Article  MathSciNet  Google Scholar 

  4. Kahra, M., Sridhar, V., Breuß, M.: Fast morphological dilation and erosion for grey scale images using the Fourier transform. In: Elmoataz, A., Fadili, J., Quéau, Y., Rabin, J., Simon, L. (eds.) SSVM 2021. LNCS, vol. 12679, pp. 65–77. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75549-2_6

    Chapter  MATH  Google Scholar 

  5. Sridhar, V., Breuss, M., Kahra, M.: Fast approximation of color morphology. In: Bebis, G., et al. (eds.) ISVC 2021. LNCS, vol. 13018, pp. 488–499. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-90436-4_39

    Chapter  Google Scholar 

  6. SciPy Documentation. https://docs.scipy.org/doc/scipy/ reference/generated/scipy.signal.convolve.html. Accessed 2 Feb 2021

  7. Serra, J., Soille, P. (eds.): Mathematical Morphology and its Applications to Image Processing, vol. 2. Springer, Cham (2012). https://doi.org/10.1007/978-94-011-1040-2

    Book  Google Scholar 

  8. Najman, L., Talbot, H. (eds.): Mathematical Morphology: From Theory to Applications. Wiley, Hoboken (2013)

    Google Scholar 

  9. Roerdink, J.B.T.M.: Mathematical morphology in computer graphics, scientific visualization and visual exploration. In: Soille, P., Pesaresi, M., Ouzounis, G.K. (eds.) ISMM 2011. LNCS, vol. 6671, pp. 367–380. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-21569-8_32

    Chapter  Google Scholar 

  10. Kukal, J., Majerová, D. Procházka, A.: Dilation and erosion of gray images with spherical masks. In: Proceedings of the 15th Annual Conference Technical Computing (2007)

    Google Scholar 

  11. Déforges, O., Normand, N., Babel, M.: Fast recursive grayscale morphology operators: from the algorithm to the pipeline architecture. J Real-Time Image Process. 8(2), 143–152 (2013)

    Article  Google Scholar 

  12. Moreaud, M. Itthirad, F.: Fast algorithm for dilation and erosion using arbitrary flat structuring element: improvement of Urbach and Wilkinson’s algorithm to GPU computing. In: 2014 International Conference on Multimedia Computing and Systems (ICMCS), pp. 289–294. IEEE (2014)

    Google Scholar 

  13. Lin, X. Xu, Z., A fast algorithm for erosion and dilation in mathematical morphology. In: 2009 WRI World Congress on Software Engineering, vol. 2, pp. 185–188. IEEE (2009)

    Google Scholar 

  14. Van Herk, M.: A fast algorithm for local minimum and maximum filters on rectangular and octagonal kernels. Pattern Recogn. Lett. 13(7), 517–521 (1992)

    Article  Google Scholar 

  15. Haralick, R.M., Sternberg, S.R., Zhuang, X.: Image analysis using mathematical morphology. IEEE Trans. Pattern Anal. Mach. Intell. 4, 532–550 (1987)

    Article  Google Scholar 

  16. Thurley, M.J., Danell, V.: Fast morphological image processing open-source extensions for GPU processing with CUDA. IEEE J. Sel. Top. Sig. Process. 6(7), 849–855 (2012)

    Article  Google Scholar 

  17. Van Droogenbroeck, M., Talbot, H.: Fast computation of morphological operations with arbitrary structuring elements. Pattern Recogn. Lett. 17(14), 1451–1460 (1996)

    Article  Google Scholar 

  18. Van Droogenbroeck, M., Buckley, M.J.: Morphological erosions and openings: fast algorithms based on anchors. J. Math. Imaging Vis. 22(2), 121–142 (2005)

    Article  MathSciNet  Google Scholar 

  19. Jones, R.: Connected filtering and segmentation using component trees. Comput. Vis. Image Underst. 75(3), 215–228 (1999)

    Article  Google Scholar 

  20. Agarwal, R.C., Burrus, C.: Fast convolution using Fermat number transforms with applications to digital filtering. IEEE Trans. Acoust. Speech Sig. Process. 22(2), 87–97 (1974)

    Article  MathSciNet  Google Scholar 

  21. Sridhar, V. Breuß, M.: An exact fast Fourier method for morphological dilation and erosion using the umbra technique. In: 2022 19th Conference on Robots and Vision (CRV) (2022)

    Google Scholar 

  22. Pollard, J.M.: The fast Fourier transform in a finite field. Math. Comput. 25(114), 365–374 (1971)

    Article  MathSciNet  Google Scholar 

  23. Rader, C.M., The number theoretic DFT and exact discrete convolution. In: IEEE Arden House Workshop on Digital Signal Processing. Harriman NY (1972)

    Google Scholar 

  24. Krizek, M., Luca, F., Somer, L.: 17 Lectures on Fermat Numbers: From Number Theory To Geometry. Springer, Cham (2002). https://doi.org/10.1007/978-0-387-21850-2

    Book  MATH  Google Scholar 

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Acknowledgements

The current work was supported by the European Regional Development Fund (EFRE 85037495). Furthermore, the authors acknowledge the support by BTU Graduate Research School (STIBET short-term scholarship for international PhD Students sponsored by the German Academic Exchange Service (DAAD) with funds of the German Federal Foreign Office).

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Correspondence to Vivek Sridhar .

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Sridhar, V., Breuß, M. (2022). A Novel Approach for Computation of Morphological Operations Using the Number Theoretic Transform. In: Baudrier, É., Naegel, B., Krähenbühl, A., Tajine, M. (eds) Discrete Geometry and Mathematical Morphology. DGMM 2022. Lecture Notes in Computer Science, vol 13493. Springer, Cham. https://doi.org/10.1007/978-3-031-19897-7_15

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  • DOI: https://doi.org/10.1007/978-3-031-19897-7_15

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