InforLorV4, Main, Exploration, bibRecord, 004705

Segmentation using vector-attribute filters: methodology and application to dermatological imaging

Identifieur interne : 004705 ( Main/Exploration ); précédent : 004704; suivant : 004706

Segmentation using vector-attribute filters: methodology and application to dermatological imaging

Auteurs : Benoît Naegel [France] ; Nicolas Passat [France] ; Nicolas Boch [Suisse] ; Michel Kocher [Suisse]

Source :

RBID : Hal:inria-00187232

Abstract

Attribute-based filters can be involved in analysis and processing of images by considering attributes of various kinds (quantitative, qualitative, structural). Despite their potential usefulness, they are quite infrequently considered in the development of real applications. A cause of this underuse is probably the difficulty to determine correct parameters for non-scalar attributes in a fast and efficient fashion. This paper proposes a general definition of vector-attribute filters for grey-level images and describes some solutions to perform detection tasks using vector-attributes and parameters determined from a learning set. Based on these elements, an interactive segmentation method for dermatological application has been developed.

Url:

https://hal.inria.fr/inria-00187232

Affiliations:

Links toward previous steps (curation, corpus...)

to stream Hal, to step Corpus: 004445
to stream Hal, to step Curation: 004445
to stream Hal, to step Checkpoint: 003823
to stream Main, to step Merge: 004853
to stream Main, to step Curation: 004705

Le document en format XML

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Segmentation using vector-attribute filters: methodology and application to dermatological imaging

Segmentation using vector-attribute filters: methodology and application to dermatological imaging

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