Approche fonctionnelle générique des méthodes de segmentation d'images

La segmentation d'image est une operation de traitement d'image de bas niveau qui consiste a localiser dans une image les regions (ensembles de pixels) appartenant a une meme structure (objets ou scene images). Cette operation est a la base de nombreuses applications tant en vision industrielle, qu'en imagerie medicale. De nombreuses recherches ont eu lieu dans le passe sur les methodes de segmentation. Il en resulte un tres grand nombre de methodes dont la comparaison, soit en terme de structure soit en terme de performance, est tres difficile. L'objectif de cette these est de proposer une nouvelle vision de la segmentation d'images basee sur un modele fonctionnel (MF) original. Ce modele qui decrit la segmentation en termes de fonctions, se presente sous la forme d'un operateur de segmentation (OS). L'OS est compose de cinq blocs elementaires enchaines au cours d'un processus iteratif qui correspond au processus de segmentation. Ce modele fonctionnel unifie les methodes de segmentation sous un formalisme commun et permet une meilleure comprehension de ces methodes. En effet, la decomposition avec la meme logique de techniques de segmentation (simple ou complexe) a priori totalement differentes a ete obtenue et implantee. Cela a permis de montrer la genericite du modele propose et son utilite pour la structuration, la comparaison et l'implantation logicielle des nombreuses methodes de segmentation. Ces decompositions qui ont conduit a un certain nombre de blocs fonctionnels independants, ont servi a la realisation d'un logiciel modulaire denomme GenSeg. Ce logiciel peut aider a terme a construire de nouvelles techniques de segmentation.

[1]  Kenneth Steiglitz,et al.  Operations on Images Using Quad Trees , 1979, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Flavio R. Dias Velasco,et al.  Thresholding Using the Isodata Clustering Algorithm , 1979 .

[3]  Junaed Sattar Snakes , Shapes and Gradient Vector Flow , 2022 .

[4]  Kenneth E. Barner,et al.  Tactile imaging using watershed-based image segmentation , 2000, Assets '00.

[5]  Donald Geman,et al.  Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images , 1984 .

[6]  Laurent D. Cohen,et al.  On active contour models and balloons , 1991, CVGIP Image Underst..

[7]  Edouard Duchesnay,et al.  Cooperative agents society organized as an irregular pyramid: A mammography segmentation application , 2003, Pattern Recognit. Lett..

[8]  Azriel Rosenfeld,et al.  Segmentation and Estimation of Image Region Properties through Cooperative Hierarchial Computation , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[9]  Xiaobo Li,et al.  Fast image region growing , 1995, Image Vis. Comput..

[10]  Azriel Rosenfeld,et al.  Hierarchical Image Analysis Using Irregular Tessellations , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  R. Courant,et al.  Methods of Mathematical Physics , 1962 .

[12]  Yvan G. Leclerc,et al.  Constructing simple stable descriptions for image partitioning , 1989, International Journal of Computer Vision.

[13]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[14]  P. Bolon,et al.  Analyse d'images: filtrage et segmentation , 1995 .

[15]  Laurence Germond Trois principes de coopération pour la segmentation en imagerie de résonnance magnétique cérébrale. (Three principles of cooperation for the segmentation of magnetic resonance images of the brain) , 1999 .

[16]  Thrasyvoulos N. Pappas An adaptive clustering algorithm for image segmentation , 1992, IEEE Trans. Signal Process..

[17]  Alfred Anwander Segmentation d'images couleur par un opérateur gradient vectoriel multiéchelle et contour actif : application à la quantification des phases minéralogiques du clinker de cimen , 2001 .

[18]  Jean-Pierre Gambotto,et al.  A new approach to combining region growing and edge detection , 1993, Pattern Recognit. Lett..

[19]  Jacques Ferber,et al.  Les Systèmes multi-agents: vers une intelligence collective , 1995 .

[20]  Guillermo Sapiro,et al.  Geodesic Active Contours , 1995, International Journal of Computer Vision.

[21]  Azriel Rosenfeld,et al.  A Pyramid Framework for Early Vision , 1994 .

[22]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Azriel Rosenfeld,et al.  Compact Region Extraction Using Weighted Pixel Linking in a Pyramid , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  Jayant Shah,et al.  A common framework for curve evolution, segmentation and anisotropic diffusion , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[25]  Martin D. Levine,et al.  Low Level Image Segmentation: An Expert System , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[26]  Yuan Yan Tang,et al.  Adaptive Image Segmentation With Distributed Behavior-Based Agents , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Salima Hassas,et al.  Framework for cooperative segmentation based on the multiagent paradigm , 2000, IS&T/SPIE Electronic Imaging.

[28]  Laurent Vinet,et al.  Hierarchical region based stereo matching , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[29]  Monga,et al.  1 - Segmentation d'images: vers une méthodologie , 1987 .

[30]  Valerie Ficet Cauchard Realisation d'un systeme d'aide a la conception d'applications de traitement d'images : une approche basee sur le raisonnement a partir de cas , 1999 .

[31]  Richard Lepage,et al.  Knowledge-Based Image Understanding Systems: A Survey , 1997, Comput. Vis. Image Underst..

[32]  Rolf Adams,et al.  Seeded Region Growing , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[33]  Alexandre NOUVEL,et al.  Une approche interactive de définition d ' ontologies image An Interactive Approach For Image Ontology Definition , 2001 .

[34]  Alan L. Yuille,et al.  A common framework for image segmentation , 1990, International Journal of Computer Vision.

[35]  Isabelle Bloch Information combination operators for data fusion: a comparative review with classification , 1996, IEEE Trans. Syst. Man Cybern. Part A.

[36]  Xavier Cufí,et al.  Strategies for image segmentation combining region and boundary information , 2003, Pattern Recognit. Lett..

[37]  Michael Spann,et al.  Image segmentation using a dynamic thresholding pyramid , 1989, Pattern Recognit..

[38]  King-Sun Fu,et al.  A survey on image segmentation , 1981, Pattern Recognit..

[39]  Corneliu Spinu Une approche multi-agents pour la segmentation d'images associant estimation et évaluation , 1997 .

[40]  Sabine Moisan,et al.  What can program supervision do for program reuse? , 2000, IEE Proc. Softw..

[41]  Gabor T. Herman,et al.  Low-Level Segmentation Of Multidimensional Medical Images: An Expert System , 1989, Other Conferences.

[42]  Olivier Boissier,et al.  MAVI: a multi-agent system for visual integration , 1994, Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems.

[43]  Koichiro Deguchi,et al.  An architecture of object recognition system for various images based on multi-agents , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[44]  Edward H. Adelson,et al.  The Laplacian Pyramid as a Compact Image Code , 1983, IEEE Trans. Commun..

[45]  Marinette Revenu,et al.  Une méthodologie de développement d'applications de traitement d'image , 1999 .

[46]  Konstantinos Konstantinides,et al.  The Khoros software development environment for image and signal processing , 1994, IEEE Trans. Image Process..

[47]  R. Bajcsy Active perception , 1988, Proc. IEEE.

[48]  Johan Montagnat,et al.  A review of deformable surfaces: topology, geometry and deformation , 2001, Image Vis. Comput..

[49]  Leslie J. Kitchen,et al.  Soft image segmentation by weighted linked pyramid , 2001, Pattern Recognit. Lett..

[50]  Aggelos K. Katsaggelos,et al.  Hybrid image segmentation using watersheds and fast region merging , 1998, IEEE Trans. Image Process..

[51]  Catherine Garbay,et al.  A Society of Goal-Oriented Agents for the Analysis of Living Cells , 1997, AIME.

[52]  Michel Jourlin,et al.  A new minimum variance region growing algorithm for image segmentation , 1997, Pattern Recognit. Lett..

[53]  Xavier Cufí,et al.  A Review on Image Segmentation Techniques Integrating Region and Boundary Information , 2001 .

[54]  Christopher J. Taylor,et al.  A cooperative framework for segmentation of MRI brain scans , 2000, Artif. Intell. Medicine.

[55]  Kacem Chehdi,et al.  Automatic image segmentation system through iterative edge - region co-operation , 2002, Image Vis. Comput..

[56]  Françoise Peyrin,et al.  Automated 3D region growing algorithm based on an assessment function , 2002, Pattern Recognit. Lett..

[57]  Dit-Yan Yeung,et al.  On deformable models for visual pattern recognition , 2002, Pattern Recognit..

[58]  Fabrice Bellet,et al.  Une approche incrémentale à base de processus coopératifs et adaptatifs pour la segmentation des images en niveaux de gris. (An incremental approach based on cooperative and adaptive processes for grey level image segmentation) , 1998 .

[59]  P.K Sahoo,et al.  A survey of thresholding techniques , 1988, Comput. Vis. Graph. Image Process..

[60]  Hugues Benoit-Cattin,et al.  Image segmentation functional model , 2004, Pattern Recognit..

[61]  Sankar K. Pal,et al.  A review on image segmentation techniques , 1993, Pattern Recognit..

[62]  Alan L. Yuille,et al.  Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[63]  Masafumi Hagiwara,et al.  Image Segmentation by Artificial Life Approach Using Autonomous Agents , 2000 .

[64]  Xie Yuan-dan,et al.  Survey on Image Segmentation , 2002 .

[65]  Kannan,et al.  ON IMAGE SEGMENTATION TECHNIQUES , 2022 .

[66]  Michael Spann,et al.  A quad-tree approach to image segmentation which combines statistical and spatial information , 1985, Pattern Recognit..

[67]  Takashi Matsuyama Expert systems for image processing: Knowledge-based composition of image analysis processes , 1989, Comput. Vis. Graph. Image Process..

[68]  James S. Duncan,et al.  Game-Theoretic Integration for Image Segmentation , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[69]  Philippe Bolon,et al.  A region-region and region-edge cooperative approach of image segmentation , 1994, Proceedings of 1st International Conference on Image Processing.

[70]  Pascal Bertolino,et al.  Multiresolution segmentation using the irregular pyramid , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[71]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[72]  Nuggehally Sampath Jayant,et al.  An adaptive clustering algorithm for image segmentation , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[73]  Jake K. Aggarwal,et al.  The Integration of Image Segmentation Maps using Region and Edge Information , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[74]  Jiming Liu,et al.  Reactive agents for adaptive image analysis , 1998, AGENTS '98.