A. Bibliographie, A. Cornu-ejols, M. Moulet, and R. Vincent, Dossier apprentissage Bulletin de l'AFIA Aloimonos 877 Y. Aloimonos, I. Weiss, and A. Bandyopadhyay. Active Vision, Int. J. Comput . Vision, vol.22, pp.14445-14459, 1987.

. H. Ballard, Aloimonos 944 Y. Aloimonos. What I have learned CVGIP: Image Understanding Bajcsy 888 R. Bajcsy. Active P erception Reference Frames for Animate Vision, Aloimonos 900 Y. Aloimonos. Purposive and Qualitative Active Vision IEEE Int. Conf. on Pattern Recognition Int. Joint Conf. on Artiicial Intelligence Ballard 922 D.H. Ballard and C.M. Brown. Principles of Animate Vision. CVGIP: Image Understanding, pp.3466360-74485, 1988.

J. L. Barron-944, D. J. Barron, S. S. Fleet, F. Beauchemin, J. M. Bellet et al., Performance of optical ow techniques Bellet 955 Une approche opportuniste et coop erative pour la vision de bas niveau Bellet 988 F. Bellet Une approche incr ementale, coop erative et adaptative pour la segmentation des images en niveaux de gris. T h ese de doctorat Bhanu 94bb Special Section on learning in computer vision. Une approche opportuniste et coop erative pour la vision de bas niveau Boissier 922 O. Boissier and Y. Demazeau. A Distributed Artiicial Intelligence View on General Purpose Vision Systems, Decentralized A I Boissier 933 O. Boissier. Probl eme du contr^ ole dans un syst eme int egr e de vision. T h ese de doctorat Boucher 96aa A. Boucher and C. Garbay. A Multi-Agent System to Segment Living Cells IEEE Int. Conf. on Pattern Recognition, pp.43377-4799494, 1992.

A. Boucher, C. Boucher, . Garbay, A. Boucher, X. Doisy et al., Segmentation de s equences d'images cytologiques par un syst eme multi-agents A Society of Goal-Oriented Agents for the Analysis of Living Cells, Journ ees Francophones IAD SMA, 1255135. Herm es Proc. 6th AIME, v ol. 1211 of LNAI Grenoble France. Boucher 98aa A. Boucher, A. Doisy, X. Ronot, and C. Garbay. Cell Migration Analysis After In Vitro Wounding Injury With a Multi-Agent Approach, 1996.

A. Boucher, A. Boucher, X. Doisy, C. Ronot, A. Garbay-boucher-98cc et al., Des agents sp ecialis es pour la compr ehension de s equences d'images Clermont- Ferrand France. Bouthemy 955 P. Bouthemy. I n teractions entre segmentation et mesure dans l'analyse du mouvement 2D: orientations r ecentes et perspectives Learning in distributed systems and multi-agent e n vironment Achieving Artiical Intelligence Through Building Robots Brooks 900 R.A. Brooks. Elephants Don't Play Chess, Actes 11 eme RFIA Proc. of European Workshop Session on Machine Learning, 4244439 Brown 944 C.M. Brown. Vision, Learning and Development, pp.1833199-3315, 1986.

C. Castelfranchi-900 and . Castelfranchi, Social Powe r : A P oint Missed in Multi-Agent, DAI and HCI. In Decentralized A I , v ol. 1, 33346 Charroux 966 B. Charroux. Analyse d'images : coop eration d'op erateurs de segmentation guid ee par l'interpr etation, 1990.

V. Cl-ement-93aa, G. Cl-ement, S. Giraudon, F. Houzelle, and . Sandakly, I n terpretation of remotely sensed images in a context of multi-sensor fusion using a multispecialist architecture, IEEE Trans. Geosci. and Remote Sensing, pp.314-7799791, 1993.

V. Cl-ement-93bb, M. Cl-ement, and . Thonnat, Integration of image processing procedures, ocapi: a knowledge-based approach, CVGIP: Image Understanding, vol.572, 1993.

F. Cloppet-oliva-96aa and . Cloppet-oliva, Analyse d'images de cultures cellulaires obtenues par microscope optique : application a des images de neuroblastomes de souris. T h ese de doctorat, 1996.

F. Cloppet-oliva-96bb, G. Cloppet-oliva, and . Stamon, Segmentation Coop erative R egionnContour pour une Analyse Automatique d'Images de Cellules en Culture, Proc. 10 eme RFIA, 1996.

R. Clouard, A. Elmoataz, C. Porquet, and M. Revenu, Clouard BORG: a Knowledgebased system for the automation of Image Segmentation Task Why building Knowledge-Based Image Segmentation is so diicult, IEEE Int. Conf. on Image Processing and its Applications Edinburgh UK. Clouard 95bb R. Clouard, C. Porquet, and A. Elmoatazand M. Revenu Int. Conf. on Knowledge-Based Systems for Reusing Programs Crevier 977 D. Crevier and R. Lepage. Knowledge-Based Image Understanding Systems: A Survey. Computer Vision and Image Understanding, p.1611185, 1994.

M. J. Tarr and . Black, Basic Research Series CVGIP 944 M, Vision as Process Dialogue: A Computational and Evolutionary Perspective on the Role of Representation in Vision. CVGIP: Image Understanding, p.601, 1993.

P. Dalle-988, P. Dalle, . Dejean, X. Doisy, P. T. Ronot et al., Clermont-Ferrand France Doisy 899 A Quantiication des d eformations et de la migration cellulaires: de la mitose a la cicatrisation in vitro The Schema system Drogoul 922 A. Drogoul and J. Ferber. From Tom Thumb to the Dockers : some experiments with foraging robots, Planiication en traitement d'image: Approche bas ee sur les donn ees Actes 11 eme RFIA X. Ronot and D. Scho eva ert Dynamique de la cellule vivante. Ed. INSERM Draper 966 B.A. Draper. Learning Control Strategies for Object Recognition From Animals to Animats : Second Conference on Simulation of Adaptative Behaviour, pp.3633366-2099250, 1989.

P. Dugnolle-988, C. Dugnolle, P. T. Garbay, and . Racqui, A mechanical model to simulate cell reorganisation during in-vitro wound healing, Proc European Simulation Multiconference, 3433347. SCS Europe, 1998.

E. H. Durfee-877, V. R. Durfee, D. D. Lesser, J. Corkill, R. Fan et al., Image Sequence Segmentation Based on 2D Temporal Entropic Thresholding Fenet 988 S. Fenet and S. Hassas. Une approche multi-agents de r esolution de probl emes par interaction : cas de l' equilibrage dynamique multi-crit eres Pont-a-Mousson France. Ferber 955 J. Ferber. Les syst emes multi-agents : vers une intelligence c ollective. I n ter- Editions A survey on image segmentation The Positive Role of Connict in Cooperative Multi-Agent Systems . In Decentralized A I , v ol. 1, 33346 Caracterization of cell migration using a parametric estimation of image motion, Coherent Cooperation Among Communicating Problem Solvers Galliers 900 J.R. Galliers Garbay 988 C. Garbay, F. Bellet, and A. Boucher. Des agent situ es pour l'interpr etation de sc enes Garnesson 911 P. Garnesson. MESSI : un syst eme d'analyse de sc ene, pp.127551291-110111107, 1981.

G. , L. Germond, C. Garbay, C. , and S. Solloway, C o o p eration entre processus guid es par les donn ees et processus guid es par les mod eles pour la segmentation Grenoble France. Guarda 988 A. Guarda. Apprentissage g en etique de r egles de reconnaissance visuelle : Application a l a r econnaissance d ' el ements du visage, Actes GRETSI, p.1699180, 1994.

Z. Guessoum-96aa and . Guessoum, Un environnement op erationnel de conception et de r ealisation de syst emes multi-agents. T h ese de doctorat, 1996.

Z. Guessoum-96bb, M. Guessoum, R. Dojat, and . Durand, A Real-Time Agent Model in a Asynchronous Object Environment Un syst eme multi-agents pour mod eliser l' evolution economique, Agents Breaking Away, LNAI Journ ees Francophones IAD SMA, 47757. Herm es, 1996.

S. H. Gwydir-944, H. M. Gwydir, S. M. Buettner, and . Dunn, Non-rigid motion analysis of the growth cone using continuity splines, Innov. Tech. Biol. Med, vol.153, p.3099321, 1994.

A. Hanson, E. Hanson, and . Riseman, VISIONS: A Computer System for Interpreting Scenes, 1978.

B. Hayes-roth-955, V. Hayes-roth-hennebert, P. Rebuuel, and . Bouthemy, An Architecture for Adaptive I n telligent Systems Hennebert 966 C Structuration Spatio-temporelle d'une Sc ene Textur ee, Proc. 10 eme RFIA, pp.3299365-1855203, 1980.

R. Jain-811 and . Jain, Extraction of Motion Information from Peripheral Processes, Jolion 944 J-M. Jolion. Computer Vision Methodologies. CVGIP: Image Understanding, pp.4899503-591, 1981.
DOI : 10.1109/TPAMI.1981.4767143

K. Falah, R. Kara-falah, P. Bolon, and J. P. Cocquerez, A Region-Region and Region- Edge Cooperative Approach of Image Segmentation, IEEE Int. Conf. on Image Processing, 1994.

L. Huynh, L. H. Le, and . Huynh, Apprentissage pour la param etrisation d'agents de segmentation, 1998.

F. Tecture-multi-processeurs, S. Leitner, X. Paillasson, J. Ronot, . K. Demongeot et al., Leitner 955 Dynamic functional and structural analysis of living cells : new tools for vital staining of nuclear DNA and for characterization of cell motion First Sight: A Human Body Outline Labeling System, Acta Biotheor. IEEE Trans. Patt. Anal. Mach. Int, vol.43, issue.174, p.3599377, 1994.

F. Leymarie-933, M. D. Leymarie, and . Levine, Tracking deformable objects in the plane using an active contour model, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.15, issue.6, p.6177634, 1993.
DOI : 10.1109/34.216733

C. E. Liedtke-877, T. Liedtke, F. Gahm, B. J. Kappei, B. Lockett et al., Automatic Detection of Clustered, Fluorescent- Stained Nuclei by Digital Image-Based Cytometry Maes 899 P. Maes. How to do the right thing, Aeikens. Segmentation of Microscopic Cell Scenes. Analyt. Quant. Cytol. Histol. Cytometry Connection Sci. J. Artiicial Life Journal, vol.9, issue.13, pp.1112-1113, 1987.

T. Matsuyama-900, V. Matsuyama, and . Hwang, SIGMA: a Knowledge-based A erial Image Understanding System, 1990.
DOI : 10.1007/978-1-4899-0867-4

F. Mayet-966, J. Mayet, M. Pinoli, . M. Jourlin, M. D. Nazif et al., Justiications physiques et applications du mod ele LIP pour le traitement des images obtenues en lumi ere transmise. Traitement du Signal Low level Image Segmentation: An Expert System, Pal 933 N.R. Pal and S.K. Pal. A review on image segmentation, pp.2511262-5555577, 1984.

J. M. Salotti-944, C. J. Salotti-siegert, A. Weijer, H. Nomura, and . Miike, Sandakly 955 F. Sandakly Contribution a la mise en oeuvre d'une architecture a b ase de connaissances pour l'interpr etation de sc enes 2D et 3D. T h ese de doctorat Sibarita 966 J.B. Sibarita. Formation et restauration des images en microscopie a r ayons X & application a l'observation d' echantillons biologiques. T h ese de doctorat, Universit e Joseph Fourier -Grenoble 1, France A gradient method for the quantitative analysis of cell movement and tissue ow and its application to the analysis of multicellular Dictyostelium development Spinu 977 C. Spinu. Une approche multi-agents pour la segmentation d'images associant estimation et evaluation. T h ese de doctorat, La gestion des informations dans les premi eres etapes de la vision par ordinateur Thompson 800 W.B. Thompson. Combining Motion and Contrast for Segmentation Thonnat 933 M. Thonnat, V. Cl ement, and J. Van den Elst. Supervision of perception tasks for autonomous systems : the OCAPI approach, pp.977104-5433549, 1980.

M. M. Trivedi-899, A. Trivedi, and . Rosenfeld, On making computers "see, Vercouter 988 L. Vercouter, P. Beaune, and C. Sayettat. Apprentissages dans les SMA. In Journ ees Francophones IAD SMA, 3411354. Herm es, p.133331335, 1989.

V. Martial, F. Von, and . Martial, Interactions Among Autonomous Planning Agents In Decentralized A I , v ol. 1, 1055119 Werner 900 E. Werner. Distributed Cooperation Algorithms, Decentralized A I, p.17732, 1990.

M. Wooldridge-955, N. R. Wooldridge, K. Jennings, D. Wu, M. D. Gauthier et al., Intelligent Agents: Theory and Parctice Live Cell Image Segmentation, Zhou 977 P. Zhou and D. Pycock. Robust Statistical-Models for Cell Image Interpretation . Image Vision Comput, pp.1155152-1112, 1995.
DOI : 10.1007/3-540-58855-8