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An Efficient Run-Based Connected Component Labeling Algorithm for Processing Holes

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Image Analysis and Processing. ICIAP 2022 Workshops (ICIAP 2022)

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Abstract

This article introduces a new connected component labeling and analysis algorithm framework that is able to compute in one pass the foreground and the background labels as well as the adjacency tree. The computation of features (bounding boxes, first statistical moments, Euler number) is done on-the-fly. The transitive closure enables an efficient hole processing that can be filled while their features are merged with the surrounding connected component without the need to rescan the image. A comparison with State-of-the-Art shows that this new algorithm can do all these computations faster than all existing algorithms processing foreground and background connected components or holes.

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References

  1. Bailey, D., Johnston, C.: Single pass connected component analysis. In: Image and Vision New Zeland (IVNZ), pp. 282–287 (2007)

    Google Scholar 

  2. Bailey, D.G., Klaiber, M.J.: Zig-zag based single-pass connected components analysis. J. Imaging 5(45), 1–26 (2019)

    Google Scholar 

  3. Bolelli, F., Allegretti, S., Baraldi, L., Grana, C.: Spaghetti labeling: directed acyclic graphs for block-based connected components labeling. IEEE Trans. Image Process. 29, 1999–2012 (2020)

    Article  Google Scholar 

  4. Bolelli, F., Cancilla, M., Baraldi, L., Grana, C.: Toward reliable experiments on the performance of Connected Components Labeling algorithms. J. Real-Time Image Process. 17(2), 229–244 (2018). https://doi.org/10.1007/s11554-018-0756-1

    Article  Google Scholar 

  5. Cabaret, L., Lacassagne, L.: What is the world’s fastest connected component labeling algorithm? In: IEEE International Workshop on Signal Processing Systems (SiPS), pp. 97–102 (2014)

    Google Scholar 

  6. Cabaret, L., Lacassagne, L., Etiemble, D.: Parallel light speed labeling for connected component analysis on multi-core processors. J. Real-Time Image Process. (JRTIP) 15(1), 173–196 (2018)

    Article  Google Scholar 

  7. Galil, Z., Italiano, G.: Data structures and algorithms for disjoint set union problems. ACM Comput. Surv. 23(3), 319–344 (1991)

    Article  Google Scholar 

  8. Gray, S.B.: Local properties of binary images in two dimensions. Trans. Comput. 20(5), 551–561 (1971)

    Article  Google Scholar 

  9. He, L., Chao, Y.: A very fast algorithm for simultaneously performing connected-component labeling and Euler number computing. Trans. Image Process. 24(9), 2725–2735 (2017)

    MathSciNet  MATH  Google Scholar 

  10. He, L., Chao, Y., Suzuki, K.: A new algorithm for labeling connected-components and calculating the Euler number, connected-component number, and hole number. In: International Conference on Pattern Recognition (ICPR), pp. 3099–3102 (2012)

    Google Scholar 

  11. He, L., Chao, Y., Suzuki, K.: An algorithm for connected-component labeling, hole labeling and Euler number computing. J. Comput. Sci. Technol. 28(3), 468–478 (2013)

    Article  MathSciNet  Google Scholar 

  12. He, L., Ren, X., Gao, Q., Zhao, X., Yao, B., Chao, Y.: The connected-component labeling problem: a review of state-of-the-art algorithms. Pattern Recogn. 70, 25–43 (2017)

    Article  Google Scholar 

  13. He, L., Ren, X., Zhao, X., Yao, B., Kasuya, H., Chao, Y.: An efficient two-scan algorithm for computing basic shape features of objects in a binary image. J. Real-Time Image Proc. 16(4), 1277–1287 (2016)

    Article  Google Scholar 

  14. Hennequin, A., Masliah, I., Lacassagne, L.: Designing efficient SIMD algorithms for direct connected component labeling. In: ACM Workshop on Programming Models for SIMD/Vector Processing (PPoPP), pp. 1–8 (2019)

    Google Scholar 

  15. Hennequin, A., Meunier, Q.L., Lacassagne, L., Cabaret, L.: A new direct connected component labeling and analysis algorithm for GPUs. In: IEEE International Conference on Design and Architectures for Signal and Image Processing (DASIP), pp. 1–6 (2018)

    Google Scholar 

  16. Klaiber, M.J., Bailey, D.G., Simon, S.: A single-cycle parallel multi-slice connected components analysis hardware architecture. J. Real-Time Image Proc. 16(4), 1165–1175 (2019)

    Article  Google Scholar 

  17. Lacassagne, L., Zavidovique, A.B.: Light speed labeling for RISC architectures. In: IEEE International Conference on Image Analysis and Processing (ICIP) (2009)

    Google Scholar 

  18. Lacassagne, L., Zavidovique, B.: Light speed labeling: efficient connected component labeling on RISC architectures. J. Real-Time Image Process. (JRTIP) 6(2), 117–135 (2011)

    Article  Google Scholar 

  19. Lemaitre, F., Hennequin, A., Lacassagne, L.: How to speed connected component labeling up with SIMD RLE algorithms. In: ACM Workshop on Programming Models for SIMD/Vector Processing (PPoPP), pp. 1–8 (2020)

    Google Scholar 

  20. Manne, F., Patwary, M.M.A.: A scalable parallel union-find algorithm for distributed memory computers. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Wasniewski, J. (eds.) PPAM 2009. LNCS, vol. 6067, pp. 186–195. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-14390-8_20

    Chapter  Google Scholar 

  21. Patwary, M.M.A., Blair, J., Manne, F.: Experiments on union-find algorithms for the disjoint-set data structure. In: Festa, P. (ed.) SEA 2010. LNCS, vol. 6049, pp. 411–423. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-13193-6_35

    Chapter  Google Scholar 

  22. Playne, D.P., Hawick, K.: A new algorithm for parallel connected-component labelling on GPUs. IEEE Trans. Parallel Distrib. Syst. 29(6), 1217–1230 (2018)

    Article  Google Scholar 

  23. Díaz del Río, F., Molina-Abril, H., Real, P.: Computing the component-labeling and the adjacency tree of a binary digital image in near logarithmic-time. In: Marfil, R., Calderón, M., Díaz del Río, F., Real, P., Bandera, A. (eds.) CTIC 2019. LNCS, vol. 11382, pp. 82–95. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-10828-1_7

    Chapter  Google Scholar 

  24. del Rio, F.D., Sanchez-Cuevas, P., Molina-Abril, H., Real, P.: Parallel connected-component-labeling based on homotopy trees. Pattern Recogn. Lett. 131, 71–78 (2020)

    Article  Google Scholar 

  25. Rosenfeld, A.: Digital topology. Am. Math. Mon. 28(8), 621–360 (1979)

    Article  MathSciNet  Google Scholar 

  26. Rosenfeld, A., Platz, J.: Sequential operator in digital pictures processing. J. ACM 13(4), 471–494 (1966)

    Article  Google Scholar 

  27. Somasundaram, K., Kalaiselvi, T.: A method for filling holes in objects of medical images using region labeling and run length encoding schemes. In: National Conference on Image Processing (NCIMP), pp. 110–115 (2010)

    Google Scholar 

  28. Tang, J.W., Shaikh-Husin, N., Sheikh, U.U., Marsono, M.N.: A linked list run-length-based single-pass connected component analysis for real-time embedded hardware. J. Real-Time Image Proc. 15(1), 197–215 (2016)

    Article  Google Scholar 

  29. Tarjan, R.: Efficiency of good but not linear set union algorithm. J. ACM 22(2), 215–225 (1975)

    Article  MathSciNet  Google Scholar 

  30. Tarjan, R., Leeuwen, J.: Worst-case analysis of set union algorithms. J. ACM 31, 245–281 (1984)

    Article  MathSciNet  Google Scholar 

  31. Wu, K., Otoo, E., Suzuki, K.: Optimizing two-pass connected-component labeling algorithms. Pattern Anal. Appl. 12, 117–135 (2009)

    Article  MathSciNet  Google Scholar 

  32. Yao, B., He, L., Kang, S., Zhao, X., Chao, Y.: Bit-quad-based Euler number computing. IEICE Trans. Inf. Syst. E100.D(9), 2197–2204 (2017)

    Google Scholar 

  33. Zhao, H., Chen, Z.X.: A simple hole filling algorithm for binary cell images. Appl. Mech. Mater. 433–435, 1715–1719 (2013)

    Article  Google Scholar 

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Authors and Affiliations

  1. LIP6, Sorbonne University, CNRS, Paris, France

    Florian Lemaitre, Nathan Maurice & Lionel Lacassagne

Authors
  1. Florian Lemaitre
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  2. Nathan Maurice
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  3. Lionel Lacassagne
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Corresponding author

Correspondence to Florian Lemaitre .

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Editors and Affiliations

  1. National Research Council, Lecce, Italy

    Pier Luigi Mazzeo

  2. Università Politecnica delle Marche, Ancona, Italy

    Emanuele Frontoni

  3. Boston University, Boston, MA, USA

    Stan Sclaroff

  4. National Research Council, Lecce, Italy

    Cosimo Distante

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Lemaitre, F., Maurice, N., Lacassagne, L. (2022). An Efficient Run-Based Connected Component Labeling Algorithm for Processing Holes. In: Mazzeo, P.L., Frontoni, E., Sclaroff, S., Distante, C. (eds) Image Analysis and Processing. ICIAP 2022 Workshops. ICIAP 2022. Lecture Notes in Computer Science, vol 13374. Springer, Cham. https://doi.org/10.1007/978-3-031-13324-4_11

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  • DOI: https://doi.org/10.1007/978-3-031-13324-4_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13323-7

  • Online ISBN: 978-3-031-13324-4

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