Optimal blurred segments decomposition in linear time
Identifieur interne : 004686 ( Hal/Checkpoint ); précédent : 004685; suivant : 004687Optimal blurred segments decomposition in linear time
Auteurs : Isabelle Debled-Rennesson [France] ; Fabien Feschet [France] ; Jocelyne Rouyer-Degli [France]Source :
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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<front><div type="abstract" xml:lang="en">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.</div>
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<hal api="V3"><titleStmt><title xml:lang="en">Optimal blurred segments decomposition in linear time</title>
<author role="aut"><persName><forename type="first">Isabelle</forename>
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<sourceDesc><biblStruct><analytic><title xml:lang="en">Optimal blurred segments decomposition in linear time</title>
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<abstract xml:lang="en">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.</abstract>
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