An Efficient Hardware Architecture without Line Memories for Morphological Image Processing

Abstract : In this paper, we present a novel hardware architecture to, achieve erosion and dilation with a large structuring element. We are, proposing a modification of HGW algorithm with a block mirroring, scheme to ease the propagation and memory access and to minimize, memory consumption. It allows to suppress the needs for backward scan-, ning and gives the possibility for hardware architecture to process very, large lines with a low latency. It compares well with the Lemonnier's, architecture in terms of ASIC gates area and shows the interest of our, solution by dividing the circuit area by an average of 10.
Type de document :
Communication dans un congrès
Jacques Blanc-Talon Salah Bourennane, Wilfried Philips, Dan Popescu, and Paul Scheunders. 10th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS 2008), Oct 2008, Juan les Pins, France. Springer, 5259, pp.147-156, 2008, Lecture Notes in Computer Science. <10.1007/978-3-540-88458-3_14>
Liste complète des métadonnées


https://hal-mines-paristech.archives-ouvertes.fr/hal-00834012
Contributeur : Doriane Ibarra <>
Soumis le : jeudi 13 juin 2013 - 18:28:23
Dernière modification le : mardi 12 septembre 2017 - 11:40:54
Document(s) archivé(s) le : samedi 14 septembre 2013 - 04:16:43

Fichier

HGWimproved.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Christophe Clienti, Michel Bilodeau, Serge Beucher. An Efficient Hardware Architecture without Line Memories for Morphological Image Processing. Jacques Blanc-Talon Salah Bourennane, Wilfried Philips, Dan Popescu, and Paul Scheunders. 10th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS 2008), Oct 2008, Juan les Pins, France. Springer, 5259, pp.147-156, 2008, Lecture Notes in Computer Science. <10.1007/978-3-540-88458-3_14>. <hal-00834012>

Partager

Métriques

Consultations de
la notice

127

Téléchargements du document

234