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Optimal blurred segments decomposition in linear time

Abstract : Blurred (previously named fuzzy) segments were introduced by Debled-Rennesson et al as an extension of the arithmetical approach of Reveillès 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.
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Contributor : Isabelle Debled-Rennesson <>
Submitted on : Monday, June 13, 2005 - 4:09:13 PM
Last modification on : Friday, February 26, 2021 - 3:28:02 PM


  • HAL Id : inria-00000112, version 1


Isabelle Debled-Rennesson, Fabien Feschet, Jocelyne Rouyer-Degli. Optimal blurred segments decomposition in linear time. 12th International Conference on Discrete Geometry for Computer Imagery - DGCI 2005, Eric Andres, Guillaume Damiand, Pascal Lienhardt, Apr 2005, Poitiers, France, pp.371-382. ⟨inria-00000112⟩



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