Object Detection With Component-Graphs in Multi-Band Images: Application to Source Detection in Astronomical Images

Autor: Thanh Xuan Nguyen, Giovanni Chierchia, Oleksandra Razim, Reynier F. Peletier, Laurent Najman, Hugues Talbot, Benjamin Perret

Publikováno v: IEEE Access, Vol 9, Pp 156482-156491 (2021)

In the context of mathematical morphology, component-graphs are complex but powerful structures for multi-band image modeling, processing, and analysis. In this work, we propose a novel multi-band object detection method relying on the component-grap

Externí odkaz: https://doaj.org/article/92455abf4393453b94404dbebcdbc78c

Fast and Effective Superpixel Segmentation Using Accurate Saliency Estimation

Autor: Felipe Belém, Isabela Borlido, Leonardo João, Benjamin Perret, Jean Cousty, Silvio J. F. Guimarães, Alexandre Falcão

Publikováno v: Lecture Notes in Computer Science ISBN: 9783031198960

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d3e8ba0567af26f37d4d5f4f50a5191e
https://doi.org/10.1007/978-3-031-19897-7_21

Robust object detection in colour images using a multivariate percentage occupancy hit-or-miss transform

Autor: Fraser Macfarlane, Paul Murray, Stephen Marshall, Benjamin Perret, Adrian Evans, Henry White

Publikováno v: Mathematical Morphology, Vol 5, Iss 1, Pp 128-152 (2021)
Macfarlane, F, Murray, P, Marshall, S, Perret, B, Evans, A & White, H 2021, ' Robust Object Detection in Colour Images Using a Multivariate Percentage Occupancy Hit-or-Miss Transform ', Mathematical Morphology-Theory and Applications, vol. 5, no. 1, pp. 128-152 . https://doi.org/10.1515/mathm-2020-0111

The extension of Mathematical Morphology to colour and multivariate images is challenging due to the need to define a total ordering in the colour space. No one general way of ordering multivariate data exists and, therefore, there is no single, defi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b28552cc0b9d01edcb13f6babe7d958f
https://strathprints.strath.ac.uk/78627/7/Macfarlane_etal_MMTA_2021_Robust_object_detection_in_colour_images.pdf

An algebraic framework for out-of-core hierarchical segmentation algorithms

Autor: Stela Carneiro, Harold Phelippeau, Lilian Buzer, Jean Cousty, Benjamin Perret, Pierre Kamlay

Publikováno v: IAPR International Conference on Discrete Geometry and Mathematical Morphology (DGMM)
IAPR International Conference on Discrete Geometry and Mathematical Morphology (DGMM), May 2021, Uppsala(virtual), Sweden
Lecture Notes in Computer Science ISBN: 9783030766566
DGMM

International audience; Binary partition hierarchies and minimum spanning trees are key structures for numerous hierarchical analysis methods, as those involved in computer vision and mathematical morphology. In this article, we consider the problem

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f1b3e53353c539c82258cf85f2f411a
https://hal.archives-ouvertes.fr/hal-03210968/document

Fuzzy-Marker-Based Segmentation Using Hierarchies

Autor: Gabriel Barbosa da Fonseca, Silvio Jamil Ferzoli Guimarães, Benjamin Perret, Romain Negrel, Jean Cousty

Publikováno v: Lecture Notes in Computer Science ISBN: 9783030766566
DGMM
International Conference on Discrete Geometry and Mathematical Morphology (DGMM)
International Conference on Discrete Geometry and Mathematical Morphology (DGMM), 2021, Uppsala, Sweden

International audience; This article extends a classical marker-based image segmentation method proposed by Salembier and Garrido in 2000. In the original approach, the segmentation relies on two sets of pixels which play the role of object and backg

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5133f62a001c11766f2649427932c43e
https://doi.org/10.1007/978-3-030-76657-3_28