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Optimal Blurred Segments Decomposition in Linear Time

  • Isabelle Debled-Rennesson
  • Fabien Feschet
  • Jocelyne Rouyer-Degli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3429)

Abstract

Blurred (previously named fuzzy) segments were introduced by Debled-Rennesson et al [1,2] as an extension of the arithmetical approach of Reveillès [11] on discrete lines, to take into account noise in digital images. An incremental linear-time algorithm was presented to decompose a discrete curve into blurred segments with order bounded by a parameter d. However, that algorithm fails to segment discrete curves into a minimal number of blurred segments. We show in this paper, that this characteristic is intrinsic to the whole class of blurred segments. We thus introduce a subclass of blurred segments, based on a geometric measure of thickness. We provide a new convex hull based incremental linear time algorithm for segmenting discrete curves into a minimal number of thin blurred segments.

Keywords

Convex Hull Linear Time Vertical Distance Recognition Algorithm Integer Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Isabelle Debled-Rennesson
    • 1
  • Fabien Feschet
    • 2
  • Jocelyne Rouyer-Degli
    • 1
  1. 1.LORIA NancyVandœuvre-lès-Nancy
  2. 2.LLAIC – IUT Clermont-FerrandAubièreFrance

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