Region Growing Structuring Elements and New Operators Based on Their Shape

Abstract : This paper proposes new adaptive structuring elements in the framework of mathematical morphology. These structuring elements (SEs) have a fixed size but they adapt their shape to the image content by choosing, recursively, similar pixels in gray-scale, with regard to the seed pixel. These new SEs are called region growing structuring elements (REGSEs). Then, we introduce an original method to obtain some features by analyzing the shape of each REGSE. We get a powerful set of operators, which is able to enhance efficiently thin structures in an image. We illustrate the performance of the proposed filters with an application: the detection of cracks in the framework of non-destructive testing. We compare these methods with others, including morphological amoebas and general adaptive neighborhood structuring elements and we see that these operators, based on REGSE, yield the best detection for our application.
Type de document :
Communication dans un congrès
Signal and Image Processing (SIP 2011), Dec 2011, Dallas, United States. Acta Press, pp.Pattern recognition, track 759-018, 2011
Liste complète des métadonnées


https://hal-mines-paristech.archives-ouvertes.fr/hal-00834502
Contributeur : Doriane Ibarra <>
Soumis le : samedi 15 juin 2013 - 18:26:41
Dernière modification le : mardi 12 septembre 2017 - 11:40:53
Document(s) archivé(s) le : lundi 16 septembre 2013 - 04:04:52

Fichier

Morard-preprint_REGSE_2011.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-00834502, version 1

Collections

Citation

Vincent Morard, Etienne Decencière, Petr Dokládal. Region Growing Structuring Elements and New Operators Based on Their Shape. Signal and Image Processing (SIP 2011), Dec 2011, Dallas, United States. Acta Press, pp.Pattern recognition, track 759-018, 2011. <hal-00834502>

Partager

Métriques

Consultations de
la notice

116

Téléchargements du document

158