Journal of Mathematical Imaging and Vision

, Volume 59, Issue 1, pp 123–135 | Cite as

Analysis of Noisy Digital Contours with Adaptive Tangential Cover

  • Phuc NgoEmail author
  • Isabelle Debled-Rennesson
  • Bertrand Kerautret
  • Hayat Nasser


The notion of tangential cover, based on maximal segments, is a well-known tool to study the geometrical characteristics of a discrete curve. However, it is not robust to noise, while extracted contours from digital images typically contain noise, and this makes the geometric analysis tasks on such contours difficult. To tackle this issue, we investigate in this paper a discrete structure, named adaptive tangential cover (ATC), which is based on the notion of tangential cover and on a local noise estimator. More specifically, the ATC is composed of maximal segments with different widths deduced from the local noise values estimated at each point of the contour. Furthermore, a parameter-free algorithm is also presented to compute ATC. This study leads to the proposal of several applications of ATC on noisy digital contours: dominant point detection, contour length estimator, tangent/normal estimator, detection of convex and concave parts. An extension of ATC to 3D curves is also proposed in this paper. The experimental results demonstrate the efficiency of this new notion.


Maximal blurred segment Noise level Geometrical parameters Dominant points Tangent Normal vectors Length contour estimator Contour concave/convexe parts 



The authors would like to thank the referees for useful comments.


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.LoriaVandoeuvre-lès-NancyFrance

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