Optimal blurred segments decomposition in linear time

Isabelle Debled-Rennesson; Fabien Feschet; Jocelyne Rouyer-Degli

Conference papers

Optimal blurred segments decomposition in linear time

Isabelle Debled-Rennesson ¹ Fabien Feschet ² Jocelyne Rouyer-Degli ¹

1 ADAGE - Applying discrete algorithms to genomics

INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications

2 LLAIC1 - Laboratoire de Logique, Algorithmique et Informatique

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.

keyword : segmentation blurred segment discrete line

Document type :

Conference papers

Domain :

Computer Science [cs] / Computational Geometry [cs.CG]

Complete list of metadata

https://hal.inria.fr/inria-00000112
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

Optimal blurred segments decomposition in linear time

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Optimal blurred segments decomposition in linear time

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