@Article{braquelaire-96-1,
author = "Braquelaire, Jean Pierre and Brun, Luc",
title = "Image Segmentation with Topological Maps
and Inter-pixel Representation",
journal = "Journal of Visual Communication and
Image representation",
year = 1998,
volume = 9,
number = 1,
pages = {62-79},
url = {article:=http://www.greyc.ensicaen.fr/~luc/ARTICLES/seg_with_topo_map.ps.gz},
theme = {nonhierarchique},
abstract = "In this paper we present a data structure improving
region segmentation of 2D images. This data
structure provides an efficient access to both
geometric features such as the set of pixels of a
region and topological features like the frontier of
a region, the neighbors of a region or the set of
regions included in one region. It allows us to
combine different segmentation algorithms without
restriction. Interactive refinement or merge of
regions can also be performed efficiently."
}
@InProceedings{braquelaire-96-2,
author = "Braquelaire, Jean Pierre and Luc Brun and Anne Vialard",
title = "Inter-Pixel Euclidean Paths for Image Analysis",
volume = 1176,
pages = "193-204",
booktitle = "Lecture Notes in Computer Science",
year = 1996,
organization = "Discrete Geometry for Computer Imagery",
publisher = "Springer-Verlag",
theme = {nonhierarchique},
url = {article (.ps.gz):=http://www.greyc.ensicaen.fr/~luc/ARTICLES/dgci.ps.gz}
abstract = "Inter-pixel boundaries provide a robust and
consistent description of segmented images but have a
poor visual aspect, especially when being
enlarged. Approximation curve are sometimes used to
smooth discrete boundaries but they do not provide
error free reconstruction and may be uneasy to use in
this context. In this paper we show the advantages
of using Euclidean paths in order to smooth
inter-pixel boundaries and we demonstrate the
interest of inter-pixel Euclidean paths for the
purpose of image segmentation and analysis."
}
@InProceedings{CI-braure-2006,
author = {Braure de Calignon, M. and Luc Brun and Lachaud, Jacques Olivier},
title = {Combinatorial Pyramids and discrete geometry for energy minimizing segmentation},
booktitle = {Proc. Int. Symposium on visual Computing},
year = 2006,
number = 4292,
series = {LNCS},
address = {Lake Tahoe, Nevada},
month = {November},
publisher = {springer},
theme= {nonhierarchique},
url = {pdf:=http://www.greyc.ensicaen.fr/~luc/ARTICLES/isvc2006.pdf},
abstract = "The scale set theory allows to define a hierarchy of
segmentations according to a scale parameter. This
theory closely related to the Bayesian and the Minimum
description Length(MDL) frameworks describes the
energy of a partition as the sum of two terms : a
goodness to fit and a regularisation term. This last
term may be interpreted as the encoding cost of the
model associated to the partition. It usually includes
the total length of the partition's boundaries and is
simply computed as the number of lignels between the
regions of the partition. We propose to use a better
estimation of the total length of the boundaries by
using discrete length estimators. We state the basic
properties which must be fulfilled by these estimators
and show their influence on the partitition's energy."
}
@InProceedings{CI-Hassani-06-1,
author = {El-hassani, M. and D. Rivasseau and S. Jehan-Besson and M. Revenu and D. Tschumperl{'e} and L. Brun and M. Duranton},
title = {A time-consistent video segmentation algorithm designed for real-time implementation},
booktitle = {IEEE International Conference on Electronics, Circuits and Systems},
year = 2006,
address = {Nice France},
month = {December},
theme = {nonhierarchique}
}
@InProceedings{CI-Hassani-2006-2,
author = {El-hassani, M. and D. Rivasseau and M. Duranton and S. Jehan-Besson and D. Tschumperl{'e} and L. Brun and M. Revenu},
title = {Vectorization of a statistical segmentation},
booktitle = {International Congress of Imaging Science},
year = 2006,
address = {Rochester},
month = {May},
theme = {nonhierarchique}
}
@Article{RI-ELHASSANI-2008,
author = {Elhassani, M. and Jehan-Besson, S. and Brun, L. and Revenu, M. and Duranton, M. and Tschumperl{'e}, D. and Rivasseau, D.},
title = {A Time-Consistent Video Segmentation Algorithm designed for Real-Time Implementation},
journal ={VLSI Design},
year = {2008},
volume ={2008},
number = {Article ID 892370},
pages = {12 pages},
theme = {nonhierarchique}
}
@InProceedings{CI-NEE-2008,
author = "N{'e}e, G. and Jehan-Besson, S. and Brun, L. and Revenu, M.",
title = "Significance tests and statistical inequalities for region matching",
booktitle = "Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshops S+SSPR 2008",
year = "2008",
editor = "N. da Vitaro Lobo et al.",
volume = "5342",
series = "Lecture Notes in Computer Science",
pages = "350--360",
month = "December",
publisher = "Springer",
theme = {nonhierarchique}
}
@Article{brun-02-5,
author = {Luc Brun and Myriam Mokhtari and Domenger, Jean Philippe},
title = {Incremental modifications on segmented image defined
by discrete maps},
journal = {Journal of Visual Communication and Image Representation},
pages= {251-290},
volume= 14,
year = 2003,
url = {article:=http://www.greyc.ensicaen.fr/~luc/ARTICLES/incr_mod_disc_map.ps.gz},
abstract = "The data structure used to encode an image partition is
of critical importance for most of region-based segmentation
algorithms. Usual data structures are often convenient to extract
only few parameters from the partition while inducing complex
processing to compute others. Moreverer, the split and merge
operations allowed by such data structure are often restricted. A
new model~cite{braquelaire-96} allows segmentation algorithms to
extract a wide range of parameters from a partition. In this paper
we describe the two basic primitives used by segmentation algorithms
to modify a partition: the segment insertion and segment
suppression.",
theme = {nonhierarchique}
}
@InProceedings{brun-99-4,
author = {L. {B}run},
title = {Mod{`e}les Math{'e}matiques et Repr{'e}sentation discr{`e}tes pour la Description des Images Couleurs},
booktitle = {{'E}cole d'{'e}t{'e} - Images Couleur},
year = 1999,
address = {Site GIAT Industries, Saint Etienne},
month = {September},
theme = {nonhierarchique,couleur},
url = {slides(ppt):=http://www.greyc.ensicaen.fr/~luc/ARTICLES/presentation_ecole_ete.ppt, article(.ps.gz):=http://www.greyc.ensicaen.fr/~luc/ARTICLES/ecole_ete.ps.gz},
abstract = "Nous allons pr{'e}senter dans ce document, un
syst{`e}me permettant {`a} l'utilisateur de guider le
processus de segmentation. La prise en compte des
interventions de l'utilisateur et les modifications de
la partition en fonction de celles-ci sont
r{'e}alis{'e}es {`a} l'aide d'un mod{`e}le permettant de
coder la g{'e}om{'e}trie et la topologie d'une
partition. Ce mod{`e}le, combin{'e} {`a} plusieurs
algorithmes de segmentation ainsi qu'a diverses
fonctions d'{'e}ditions, permet {`a} l'utilisateur de
d{'e}signer interactivement les r{'e}gions qui doivent
{^e}tre d{'e}coup{'e}es ou fusionn{'e}es. Cette
interaction entre l'utilisateur et les algorithmes de
segmentation doit permettre d'obtenir de bons
r{'e}sultats sur une tr{`e}s grande vari{'e}t{'e} d'images
sans ajustement de param{`e}tres."
}
@InProceedings{brun-97,
author = "L. {B}run and Bazin, J. M.",
title = "Am{'e}lioration des performances d'un syst{`e}me de
segmentation par l'utilisation d'un syst{`e}me expert",
year = 1998,
theme = {nonhierarchique},
booktitle = "Advances in Intelligent Computing- IPMU'98",
organization = "IPMU",
url = {article:=http://www.greyc.ensicaen.fr/~luc/ARTICLES/ipmu.ps.gz},
abstract = " Nous allons pr{'e}senter un nouveau syst{`e}me de
segmentation bas{'e} sur une collaboration entre un
algorithme de segmentation existant et un syst{`e}me
expert. Le nouveau syst{`e}me se distingue de
l'algorithme de segmentation pr{'e}c{'e}dent par une
distinction claire entre les connaissances de l'expert
en Imagerie et les algorithmes utilisant ces
connaissances. Le gain en modularit{'e} obtenu permet
d'enrichir facilement la base de connaissances et de
diminuer le nombre de questions triviales pos{'e}es {`a}
l'utilisateur."
}
@InProceedings{brun-96-3,
author = "L. {B}run and Domenger, J. P.",
title = "A new split and merge algorithm with Topological maps and inter-pixel Boundaries ",
booktitle = "The fifth International Conference in Central Europe
on Computer Graphics and Visualization",
year = 1997,
month = "february",
theme = {nonhierarchique},
url= {article:=http://www.greyc.ensicaen.fr/~luc/ARTICLES/new_split_merge.ps.gz}
abstract = " Usually, the segmentation algorithms implementing
the split and merge operations are restricted to a
split stage followed by a merge stage. In this
paper, we present a new split and merge algorithm
combining alternatively split and merge operations
at each recursive step. This algorithm is based on
a data structure called {em discrete
map}~cite{braquelaire-96}. This data structure
provides an efficient framework to implement split
and merge operations."
}
@InProceedings{brun-97-2,
author = "Luc {B}run and Domenger, Jean Philipe and Braquelaire, Jean Pierre",
title = "Discrete maps : a framework for region segmentation algorithms",
booktitle = "Workshop on Graph based representations",
year = 1997,
month = "April",
theme = {nonhierarchique},
OPTorganization = "IAPR-TC15",
address = "Lyon",
url= {article (.ps.gz):=http://www.greyc.ensicaen.fr/~luc/ARTICLES/GbR97.ps.gz}
note = "published in Advances in Computing (Springer)",
abstract = "In this paper, we present different recent
segmentation works based on discrete maps. Discrete
maps provide an efficient framework for region based
segmentation methods. A discrete is a mixed model. It
combines an encoding of the discrete boundaries of
the image regions with topological graphs which
represents the topology of the image."
}
@PhdThesis{brun-96-4,
author = "L. {B}run",
title = "Segmentation d'images couleur {`a} base Topologique",
school = "Universit{'e} Bordeaux I",
year = 1996,
key = 1651,
theme = {nonhierarchique},
address = "351 cours de la Lib{'e}ration 33405 Talence",
month = "December",
url = "these:=http://www.greyc.ensicaen.fr/~luc/ARTICLES/these.ps.gz",
abstract = "La segmentation est un processus visant {`a}
extraire des objets pr{'e}sents dans une image. La
plupart des m{'e}thodes de segmentation
d{'e}velopp{'e}es jusqu'{`a} pr{'e}sent sont d{'e}volues
{`a} une classe d'images particuli{`e}re (photo
satellite, image IRM, etc.). De plus l'information
colorim{'e}trique contenue dans les images est
insuffisamment prise en compte. Le but de ce
travail est de rem{'e}dier {`a} ces deux
limitations. Nous proposons deux m{'e}thodes
permettant d'extraire des informations pertinentes
{`a} partir d'ensembles de couleurs. Nous proposons
de plus plusieurs m{'e}thodes de segmentation
bas{'e}es sur les cartes planaires et sur une
repr{'e}sentation des r{'e}gions par fronti{`e}res
inter-pixels. Ces m{'e}thodes sont tr{`e}s
g{'e}n{'e}rales et utilisent un environnement de
programmation permettant de d{'e}velopper rapidement
des logiciels de segmentation."
}
@InBook{damiand-07,
author = {Guillaume Damiand and Luc Brun},
editor = {David Coeurjolly and Annick Montanvert and Jean-Marc Chassery},
title = {G{'e}om{'e}trie discr{`e}te et images num{'e}riques},
chapter = {Cartes combinatoires pour l'analyse d'images},
publisher = {Hermes},
year = 2007,
pages = {107-124},
theme = {nonhierarchique}
}
@article{RI-BRUN-2009,
author = {Aline Deruyver and
Yann Hod{'e} and
Luc Brun},
title = {Image interpretation with a conceptual graph: Labeling over-segmented
images and detection of unexpected objects},
journal = {Artif. Intell.},
volume = {173},
number = {14},
year = {2009},
pages = {1245-1265},
ee = {http://dx.doi.org/10.1016/j.artint.2009.05.003},
bibsource = {DBLP, http://dblp.uni-trier.de},
theme="nonhierarchique",
abstract={The labeling of the regions of a segmented image according
to a semantic representation (ontology) is usually
associated with the notion of understanding. The
high combinatorial aspect of this problem can be
reduced with local checking of constraints between
the elements of the ontology. In the classical
definition of Finite Domain Constraint Satisfaction
Problem, it is assumed that the matching problem
between regions and labels is
bijective. Unfortunately, in image interpretation
the matching problem is often non-univocal. Indeed,
images are often over-segmented: one object is made
up of several regions. This non-univocal matching
between data and a conceptual graph was not possible
until a decisive step was accomplished by the
introduction of arc consistency with bilevel
constraint (FDCSPBC). However, this extension is
only adequate for a matching corresponding to
surjective functions. In medical image analysis, the
case of non-functional relations is often
encountered, for example, when an unexpected object
like a tumor appears. In this case, the data cannot
be mapped to the conceptual graph, with a classical
approach. In this paper we propose an extension of
the FDCSPBC to solve the constraint satisfaction
problem for non-functional relations.}
}
@InProceedings{CI-ELHASSANI-2006,
author = {M. Elhassani and D. Rivasseau and M. Duranton and S. Jehan-Besson and D. Tschumperle and L. Brun and M. Revenu },
title = {Vectorization of a statistical segmentation},
booktitle = {International Congress of Imaging Science},
year = 2006,
address = {Rochester, NY, USA},
month = {May},
theme= {nonhierarchique}
}
@InProceedings{CN-Hassani-2006,
author = {M. Elhassani and D. Rivasseau and S. Jehan-Besson and M. Revenu and D. Tschumperle and L. Brun and M. Duranton},
title = {Conception d'un algorithme robuste de segmentation vid{'e}o pour des applications temps r{'e}el},
booktitle = {CORESA},
year = 2006,
address = {Caen},
month = {December},
theme = {nonhierarchique}
}
