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A Discrete Approach for Decomposing Noisy Digital Contours into Arcs and Segments

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Computer Vision – ACCV 2016 Workshops (ACCV 2016)

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Abstract

In the paper, we present a method for decomposing a discrete noisy curve into arcs and segments which are the frequent primitives in digital images. This method is based on two tools: dominant point detection using adaptive tangential cover and tangent space representation of the polygon issued from detected dominant points. The experiments demonstrate the robustness of the method w.r.t. noise.

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Notes

  1. 1.

    The points are said quasi collinear if they belong to a small width strip bounded by two real parallel lines.

References

  1. Nguyen, T.P., Debled-Rennesson, I.: Decomposition of a curve into arcs and line segments based on dominant point detection. In: Heyden, A., Kahl, F. (eds.) SCIA 2011. LNCS, vol. 6688, pp. 794–805. Springer, Heidelberg (2011). doi:10.1007/978-3-642-21227-7_74

    Chapter  Google Scholar 

  2. Akinlar, C., Topal, C.: EDCircles: a real-time circle detector with a false detection control. Pattern Recogn. 46, 725–740 (2013)

    Article  Google Scholar 

  3. Arkin, E.M., Chew, L.P., Huttenlocher, D.P., Kedem, K., Mitchell, J.S.B.: An efficiently computable metric for comparing polygonal shapes. In: Proceedings of the First Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 1990, pp. 129–137 (1990)

    Google Scholar 

  4. Latecki, L.J., Lakämper, R.: Shape similarity measure based on correspondence of visual parts. IEEE Trans. Pattern Anal. Mach. Intell. 22, 1185–1190 (2000)

    Article  Google Scholar 

  5. Ngo, P., Nasser, H., Debled-Rennesson, I., Kerautret, B.: Adaptive tangential cover for noisy digital contours. In: Normand, N., Guédon, J., Autrusseau, F. (eds.) DGCI 2016. LNCS, vol. 9647, pp. 439–451. Springer, Cham (2016). doi:10.1007/978-3-319-32360-2_34

    Chapter  Google Scholar 

  6. Nguyen, T.P., Debled-Rennesson, I.: Arc segmentation in linear time. In: Real, P., Diaz-Pernil, D., Molina-Abril, H., Berciano, A., Kropatsch, W. (eds.) CAIP 2011. LNCS, vol. 6854, pp. 84–92. Springer, Heidelberg (2011). doi:10.1007/978-3-642-23672-3_11

    Chapter  Google Scholar 

  7. Debled-Rennesson, I., Feschet, F., Rouyer-Degli, J.: Optimal blurred segments decomposition of noisy shapes in linear time. Comput. Graph. 30, 30–36 (2006)

    Article  MATH  Google Scholar 

  8. Reveillès, J.P.: Géométrie discrète, calculs en nombre entiersgorithmique. Thèse d’état, Université Louis Pasteur, Strasbourg (1991)

    Google Scholar 

  9. Lachaud, J.-O.: Digital shape analysis with maximal segments. In: Köthe, U., Montanvert, A., Soille, P. (eds.) WADGMM 2010. LNCS, vol. 7346, pp. 14–27. Springer, Heidelberg (2012). doi:10.1007/978-3-642-32313-3_2

    Chapter  Google Scholar 

  10. Faure, A., Buzer, L., Feschet, F.: Tangential cover for thick digital curves. Pattern Recogn. 42, 2279–2287 (2009)

    Article  MATH  Google Scholar 

  11. Kerautret, B., Lachaud, J.O.: Meaningful scales detection: an unsupervised noise detection algorithm for digital contours. Image Proc. Line 4, 98–115 (2014)

    Article  Google Scholar 

  12. Nguyen, T.P., Debled-Rennesson, I.: A discrete geometry approach for dominant point detection. Pattern Recogn. 44, 32–44 (2011)

    Article  MATH  Google Scholar 

  13. Ngo, P., Nasser, H., Debled-Rennesson, I.: Efficient dominant point detection based on discrete curve structure. In: Barneva, R.P., Bhattacharya, B.B., Brimkov, V.E. (eds.) IWCIA 2015. LNCS, vol. 9448, pp. 143–156. Springer, Cham (2015). doi:10.1007/978-3-319-26145-4_11

    Chapter  Google Scholar 

  14. Feschet, F., Tougne, L.: Optimal time computation of the tangent of a discrete curve: application to the curvature. In: Bertrand, G., Couprie, M., Perroton, L. (eds.) DGCI 1999. LNCS, vol. 1568, pp. 31–40. Springer, Heidelberg (1999). doi:10.1007/3-540-49126-0_3

    Chapter  Google Scholar 

  15. Rosin, P.L., Wesst, G.A.W.: Segmentation of edges into lines and arcs. Image Vis. Comput. 7, 109–114 (1989)

    Article  Google Scholar 

  16. Kanungo, T., Haralick, R.M., Stuezle, W., Baird, H.S., Madigan, D.: A statistical, nonparametric methodology for document degradation model validation. IEEE Trans. Pattern Anal. Mach. Intell. 22, 1209–1223 (2000)

    Article  Google Scholar 

  17. DGtal: Digital Geometry tools and algorithms library. http://libdgtal.org

  18. Imagene, generic digital image library. http://gforge.liris.cnrs.frs/projects/imagene

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Author information

Authors and Affiliations

  1. Université de Lorraine, LORIA, UMR 7503, Vandoeuvre-lès-Nancy, 54506, France

    Phuc Ngo, Hayat Nasser & Isabelle Debled-Rennesson

  2. CNRS, LORIA, UMR 7503, Vandoeuvre-lès-Nancy, 54506, France

    Phuc Ngo, Hayat Nasser & Isabelle Debled-Rennesson

Authors
  1. Phuc Ngo
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  2. Hayat Nasser
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  3. Isabelle Debled-Rennesson
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Corresponding author

Correspondence to Phuc Ngo .

Editor information

Editors and Affiliations

  1. Institute of Information Science, Academia Sinica, Taipei, Taiwan

    Chu-Song Chen

  2. Tsinghua University, Beijing, China

    Jiwen Lu

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Kai-Kuang Ma

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Ngo, P., Nasser, H., Debled-Rennesson, I. (2017). A Discrete Approach for Decomposing Noisy Digital Contours into Arcs and Segments. In: Chen, CS., Lu, J., Ma, KK. (eds) Computer Vision – ACCV 2016 Workshops. ACCV 2016. Lecture Notes in Computer Science(), vol 10117. Springer, Cham. https://doi.org/10.1007/978-3-319-54427-4_36

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  • DOI: https://doi.org/10.1007/978-3-319-54427-4_36

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-54427-4

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