S. Alkan, Internal log defect model using CT images. Phase I : Self-recognizing and visualizing log. Fourth Workshop of IUFRO Working Party S5.01-04 "Connection between Silviculture and Wood Quality through Modelling Approaches and Simulation Softwares, pp.162-166, 2002.

C. Andersson and F. Walter, Classification of compression wood using digital image analysis, Forest Products Journal, vol.45, issue.1112, pp.87-92, 1995.

J. P. Andreu and A. Rinnhofer, Modeling Knot Geometry in Norway Spruce from Industrial CT Images, Proceedings of Image Analysis, 13th Scandinavian Conference (SCIA), pp.786-791, 2003.
DOI : 10.1007/3-540-45103-X_104

J. P. Andreu and A. Rinnhofer, Modeling of Internal Defects in Logs for value Optimization based on Industrial CT Scanning, Fifth International Conference on Image Processing and Scanning of Wood, pp.23-26, 2003.

J. Andreu and A. Rinnhofer, Automatic detection of pith and annual rings on industrial computed tomography log images, pp.37-47, 2001.

J. Andreu and A. Rinnhofer, Enhancement of annual rings on industrial CT images of logs, Object recognition supported by user interaction for service robots, pp.11-15, 2002.
DOI : 10.1109/ICPR.2002.1047844

. Anon, X-Ray Log Scanner, FAIR-CT95-1188, 2000.

. Anon, Optimizing Log Breakdown By Computed Tomography Assessment of Inner Quality -Joanneum Research Institute of Digital Image Processing (Austria), 2005.

. Anon, CT generation, GE Healthcare, Bio-Sciences Europe. Medcyclopaedia.com, 2005.

J. Bauch and G. Koch, Biologische und chemische Untersuchungen über Holzverfärbungen der Rotbuche (Fagus sylvatica [L.]) und Möglichkeiten vorbeugender Maßnahmen [Biological and chemical analyses about wood discolourations of Common beech (Fagus sylvatica, Bundesforschungsanstalt für Forst-und Holzwirtschaft, p.pp, 2001.

D. M. Benson-cooper, R. L. Knowles, F. J. Thomson, and D. J. Cown, Computed tomographic scanning for the detection of defects within logs. FRI Bulletin, Forest Research Institute, p.6, 1982.

S. Bhandarkar, T. D. Faust, and M. Tang, A system for detection of internal log defects by computer analysis of axial CT images, Proceedings Third IEEE Workshop on Applications of Computer Vision. WACV'96, pp.258-263, 1996.
DOI : 10.1109/ACV.1996.572064

S. M. Bhandarkar, T. D. Faust, and M. Tang, CATALOG: a system for detection and rendering of internal log defects using computer tomography, Machine Vision and Applications, pp.171-190, 1999.
DOI : 10.1007/s001380050100

R. Birkeland and W. Han, Ultrasonic scanning for internal log defects, Proceedings of the 4th International Conference on Scanning Technology in the Wood Industry, 1991.

L. Björklund, Identifying heartwood-rich stands or stems of Pinus sylvestris by using inventory data, Silva Fennica, vol.33, issue.2, pp.119-129, 1999.
DOI : 10.14214/sf.662

L. Björklund and H. Petersson, Predicting Knot Diameter of Pinus sylvestris in Sweden, Scandinavian Journal of Forest Research, vol.14, issue.4, pp.376-384, 1999.
DOI : 10.1080/02827589950152700

J. Bresenham, Algorithm for computer control of a digital plotter, IBM Systems Journal, vol.4, issue.1, pp.25-30, 1965.
DOI : 10.1147/sj.41.0025

V. Bucur, Nondestructive Characterization and Imaging of Wood, p.3540438408, 2003.
DOI : 10.1007/978-3-662-08986-6

V. Bucur, Techniques for high resolution imaging of wood structure: a review, Measurement Science and Technology, vol.14, issue.12, pp.91-98, 2003.
DOI : 10.1088/0957-0233/14/12/R01

Y. Caraglio and D. Barthélémy, Revue critique des termes relatifs à la croissance et à la ramification des tiges des végétaux vasculaires. Modélisation et simulation de l'architecture des végétaux, 1997.

A. Chalifour, F. Nouboud, B. Deprost, and S. Okana, Automatic Detection of Tree-Rings on Wood Disc Images, 5th International Conference on Quality Control by Artificial Vision, pp.21-23, 2001.

S. J. Chang, J. R. Olson, and P. C. Wang, NMR imaging of internal features in wood, Forest Products Journal, vol.39, issue.6, pp.43-49, 1989.

S. J. Chang, Imaging hardwood logs with the NMR scanner, IAWA Bulletin, vol.11, issue.2, p.121, 1990.

S. J. Chang, External and Internal Defect Detection to Optimize Cutting of Hardwood Logs and Lumber. Transferring Technologies for Industry n°3, 1992.

S. Chiorescu and S. Grundberg, The influence of missing bark on measurements performed with a 3D log scanner, Forest Products Journal, vol.51, issue.9, pp.78-86, 2001.

J. Cocquerez and S. Philipp, Analyse d'images: filtrage et segmentation, 1995.
URL : https://hal.archives-ouvertes.fr/hal-00706168

F. Colin, Analyse et modélisation de la branchaison de l'épicéa commun en vue de prédire la qualité de la ressource. Unpublished Ph.D. dissertation, Sciences Forestières, p.pp, 1992.

W. S. Conner and R. A. Schowengerdt, Design of a computer vision based tree ring dating system, 1998 IEEE Southwest Symposium on Image Analysis and Interpretation (Cat. No.98EX165), 1998.
DOI : 10.1109/IAI.1998.666895

W. S. Conner, R. A. Schowengerdt, M. Munro, and M. K. Hughes, Engineering design of an image acquisition and analysis system for dendrochronology, Optical Engineering, vol.39, issue.2, pp.453-463, 2000.
DOI : 10.1117/1.602383

T. Constant, Characterisation of Growth Parameters in Dried Battens, Improved Spruce Timber Utilization, STUD FAIR CT 96-1915, SUBTASK B6-2, STUD.INRA.FR.B62.01 (Methods), INRA Team Partner P3, 1999.

I. Contreras, A. Guesalga, M. P. Fernandez, M. Guarini, and P. Irarrazaval, MRI fast tree log scanning with helical undersampled projection acquisitions, Magnetic Resonance Imaging, vol.20, issue.10, pp.20-781, 2002.
DOI : 10.1016/S0730-725X(02)00602-1

P. E. Cruvinel, J. M. Naime, M. Borges, A. Macedo, and A. Zhang, Detection of beetle damage in forests by X-ray CT image processing, Revista ??rvore, vol.27, issue.5, pp.747-752, 2003.
DOI : 10.1590/S0100-67622003000500017

P. Danielsson and Q. Ye, A New Procedure for Line Enhancement Applied to Fingerprints, Pattern recognition and artificial intelligence, pp.49-61, 1988.
DOI : 10.1016/B978-0-444-87137-4.50010-2

P. Danielsson and Q. Ye, Rotation-invariant operators applied to enhancement of fingerprints, [1988 Proceedings] 9th International Conference on Pattern Recognition, pp.329-333, 1988.
DOI : 10.1109/ICPR.1988.28234

R. Daquitaine, L. Saint-andre, and J. M. Leban, Improved stem taper and ring width modelling based on standard tree measurements (pages 3-23) In "Modelling stem properties distribution", Final report of Subtask A2.1. STUD research project, FAIR CT-96-1915, p.68, 1998.

J. Davis and P. Wells, Computed tomographymeasurements on wood, Industrial Metrology, vol.2, issue.3-4, pp.195-218, 1992.
DOI : 10.1016/0921-5956(92)80004-D

D. Placido, J. Gastine, F. Deleuze, and C. , Epicéa commun en France : alternatives sylvicoles pour l'essence. Fiches Informations-Forêt de l'AFOCEL, p.29, 2002.

R. O. Duda and P. E. Hart, Use of the Hough transformation to detect lines and curves in pictures, Communications of the ACM, vol.15, issue.1, pp.11-15, 1972.
DOI : 10.1145/361237.361242

C. Edelin, Aspects morphologiques de la croissance rythmique chez les arbres tropicaux Compte rendu du Séminaire du groupe d'Etude de l'Arbre: Le rythme de croissance, base de l'organisation temporelle de l'arbre, 25-26 mars, pp.13-23, 1993.

M. Ekevad, Method to compute fiber directions in wood from computed tomography images, Journal of Wood Science, vol.50, issue.1, pp.41-46, 2004.
DOI : 10.1007/s10086-003-0524-z

K. Flood, P. Danielsson, and M. M. Seger, On 3D Segmentation of Knots in 3D-volume data Acquired from X-ray Linear Cone-Beam Scanning, Fifth International Conference on Image Processing and Scanning of Wood, pp.23-26, 2003.

J. H. Fromm, I. Sautter, D. Matthies, J. Kremer, P. Schumacher et al., Xylem Water Content and Wood Density in Spruce and Oak Trees Detected by High-Resolution Computed Tomography, PLANT PHYSIOLOGY, vol.127, issue.2, pp.416-425, 2001.
DOI : 10.1104/pp.010194

B. V. Funt, A computer vision System that analyzes CT-scans of sawlogs, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp.175-177, 1985.

B. V. Funt and E. C. Bryant, Detection of internal log defects by automatic interpretation of computer tomography images, Forest Products Journal, vol.37, issue.1, pp.56-62, 1987.

L. A. Grace, Exploring the potential of using optical log scanners for predicting lumber grade, Forest Products Journal, vol.43, pp.10-45, 1993.

A. Grönlund, S. Grundberg, and U. Grönlund, The Swedish Stembank -an Unique Database for Different Silvicultural and Wood Properties. Workshop Connection between silviculture and wood quality through modelling approaches and simulation softwares, pp.13-17, 1994.

S. Grundberg and A. Grönlund, Methods for reducing data when scanning for internal log defects, Proceedings of the 4th International Conference on Scanning Technology in the Wood Industry, 1991.

S. Grundberg and A. Grönlund, Log scanning -extraction of knot geometry. The 1st International Seminar, Scanning Technology and Image Processing on Wood, 1992.

S. Grundberg, An X-ray LogScanner -A tool for control of the sawmill process, 1999.

N. K. Gupta, D. L. Schmoldt, and B. Isaacson, Tangential scanning of hardwood logs: developing an industrial computer tomography scanner, Proceedings, 11th International Symposium on Nondestructive Testing of Wood, pp.131-139, 1998.

A. Habermehl, A NEW NON-DESTRUCTIVE METHOD FOR DETERMINING INTERNAL WOOD CONDITION AND DECAY IN LIVING TREES. II: RESULTS AND FURTHER DEVELOPMENTS, Arboricultural Journal, vol.146, issue.2, pp.121-130, 1982.
DOI : 10.1007/BF01822299

A. Habermehl, A NEW NON-DESTRUCTIVE METHOD FOR DETERMINING INTERNAL WOOD CONDITION AND DECAY IN LIVING TREES. PART 1. PRINCIPLES, METHOD AND APPARATUS, Arboricultural Journal, vol.6, issue.1, pp.1-8, 1982.
DOI : 10.1080/03071375.1982.9746543

A. Habermehl and H. W. Ridder, Application of Computed-Tomography for Non-Destroying Investigations on Wood of Living Trees -Forestry Studies, Holz als Roh-und Werkstoff, pp.1-6, 1993.

A. Habermehl and H. W. Ridder, Computer-Tomographie in der Forstwirtschaft und Baumpflege (Teil 1), 1996.

A. Habermehl and H. W. Ridder, Computer-Tomographie in der Forstwirtschaft und Baumpflege, 1997.

A. Habermehl, H. W. Ridder, and P. Seidl, COMPUTERIZED TOMOGRAPHIC SYSTEMS AS TOOLS FOR DIAGNOSING URBAN TREE HEALTH, Acta Horticulturae, vol.496, issue.496, pp.261-268, 1999.
DOI : 10.17660/ActaHortic.1999.496.33

J. R. Hailey and P. I. Morris, Application of scanning and imaging techniques to assess decay and wood quality in logs and standing trees In: Application of scanning and imaging techniques to assess decay and wood quality in logs and standing trees, Alberta Forest Service (Canada-Alberta Forest Resource Development Agreement), p.48, 1987.

T. E. Harless, F. G. Wagner, P. H. Steele, F. W. Taylor, V. Yadama et al., Methodology for locating defects within hardwood logs and determining their impact on lumber-value yield, Forest Products Journal, vol.41, issue.4, pp.25-30, 1991.

Y. Hattori and Y. Kanagawa, Non-Destructive Measurement of Moisture Distribution in Wood with a Medical X-Ray CT Scanner I. Accuracy and influencing factors, Mokuzai Gakkaishi, issue.12, pp.31-974, 1985.

P. Hauffe, Weiterentwicklung der automatisierten Rundholzvermessung hinsichtlich der Erfassung und Quantifizierung äusserer und innerer Holzeigenschaften, 2001.

J. He, A Comparison of Artificial Neural Network Classifiers for Analysis of CT Images for the Inspection of Hardwood Logs, 1997.

P. Heuret, D. Barthelemy, E. Nicolini, and C. Atger, Analysis of the components of height growth and stem formation of sessile oak, Quercus petraea (Matt.) Liebl. (Fagaceae) under active silviculture, Canadian Journal of Botany, vol.78, issue.3, pp.361-373, 2000.

D. G. Hodges, W. C. Anderson, and C. W. Mcmillin, The economic potential of CT scanners for hardwood sawmills, Forest Products Journal, vol.40, issue.3, pp.65-69, 1990.

P. V. Hough, Method and means for recognizing complex patterns, U.S. Patent, vol.3, p.69654, 1962.

M. Jaeger, J. Leban, P. Borianne, S. Chemouny, and L. Saint-andré, 3D stem reconstruction from CT scan exams. From log external shape to internal structures, Workshop IUFRO, pp.5-12, 1999.

J. Johansson, O. Hagman, and B. A. Fjellner, Predicting moisture content and density distribution of Scots pine by microwave scanning of sawn timber, Journal of Wood Science, vol.49, issue.4, pp.312-316, 2003.
DOI : 10.1007/s10086-002-0493-7

B. Jourez and A. Leclercq, Modelling bark thickness in the tree in relation to silvicultural treatment. Final Report of the Task 6. EED Forest Project. Silvicultural control and non-destructive assessment of timber quality in plantation grown Spruces and Douglas fir, Contract, pp.2-0024, 1993.

A. P. Kaestner and L. B. Baath, Microwave Polarimetry Dased Wood Scanning, 12th International Symposium on Nondestructive Testing of Wood, pp.13-15, 2000.
DOI : 10.1109/jsen.2004.841343
URL : http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-716

J. T. Karsulovic, M. I. Dinator, and R. Morales, Nondestructive gamma radiation methods for detection of central rot in logs of Lenga (Nothogagus pumilio), Forest Products Journal, issue.1112, pp.52-87, 2002.

B. Larsson, B. Bengtsson, and M. Gustafsson, Nondestructive detection of decay in living trees, Tree Physiology, vol.24, issue.7, pp.853-858, 2004.
DOI : 10.1093/treephys/24.7.853

H. Lemieux, M. Samson, and A. Usenius, logs, Scandinavian Journal of Forest Research, vol.4, issue.1, pp.50-56, 1997.
DOI : 10.1080/02827588909382560

H. Lemieux, A. Usenius, and M. Samson, A method for the characterization of knots in logs, 1997.

C. Levi, J. E. Cray, E. C. Mccullough, and R. R. Hattery, The unreliability of CT numbers as absolute values, American Journal of Roentgenology, vol.139, issue.3, pp.443-447, 1982.
DOI : 10.2214/ajr.139.3.443

L. O. Lindgren, Medical CAT-scanning: X-ray absorption coefficients, CT-numbers and their relation to wood density, Wood Science and Technology, vol.25, issue.5, pp.341-349, 1991.
DOI : 10.1007/BF00226173

L. O. Lindgren, The accuracy of medical CAT-scan images for non-destructive density measurements in small volume elements within solid wood, Wood Science and Technology, vol.25, issue.6, p.25, 1991.
DOI : 10.1007/BF00225235

O. Lindgren, J. Davis, P. Wells, and P. Shadbolt, Nondestructive Wood Density Distribution Measurements Using Computed-Tomography, pp.295-299, 1992.
DOI : 10.1007/bf02615356

P. F. Lister, Applications of X-ray Computed Tomography in the Wood Products Industry. 16th WCNDT 2004 -World Conference on NDT, 2004.

J. Lohmann and G. Becker, Xylem-Conductive Area of Spruce, Karst.) of Different Age and Vitality. Holz als Roh-und Werkstoff, pp.93-100, 1993.

C. Lundgren, Predicting Log Type and Knot Size Category Using External Log Shape Data from a 3D Log Scanner, Scandinavian Journal of Forest Research, vol.15, issue.1, pp.119-126, 2000.
DOI : 10.1080/02827580050160556

A. Macedo, C. M. Vaz, J. C. Pereira, J. M. Naime, P. E. Cruvinel et al., Wood Density Determination by X- and Gamma-Ray Tomography, Holzforschung, vol.56, issue.5, pp.56-535, 2002.
DOI : 10.1515/HF.2002.082

M. Seger, M. Danielsson, and P. , Scanning of logs with linear cone-beam tomography, Computers and Electronics in Agriculture, vol.41, pp.1-3, 2003.

G. Mahler and B. Höwecke, Verkernungserscheinungen bei der Buche in Baden-Württemberg in Abhängigkeit von Alter, Standort und Durchmesser [Occurrence of heartwood of beech in Baden- Württemberg depending on age, site and diameter], Schweizerische Zeitschrift für Forstwesen, issue.5, pp.142-375, 1991.

G. Mahler and P. Hauffe, Evaluation of Internal Log Quality using X-ray and Ultrasound, Proceedings of the 12th International Symposium on Nondestructive Testing of Wood, pp.13-15, 2000.

A. Métro, Dictionnaire forestier multilingue. Terminologie forestière. Sciences forestières, technologie, pratiques et produits forestiers. (Version française). 432 pp, 1975.

S. Morales, P. Fernandez, A. Guesalaga, and P. Irarrazaval, 3D internal tree structure modeling using Magnetic Resonance Imaging (MRI): Automatic growth ring reconstruction. Fourth Workshop of IUFRO Working Party S5.01-04 "Connection between Silviculture and Wood Quality through Modelling Approaches and Simulation Softwares, pp.8-15, 2002.

S. Morales, A. Guesalaga, M. P. Fernandez, M. Guarini, and P. Irarrazaval, Computer reconstruction of pine growth rings using MRI, Magnetic Resonance Imaging, vol.22, issue.3, pp.403-412, 2004.
DOI : 10.1016/j.mri.2004.01.015

G. Nicolotti, L. V. Socco, R. Martinis, A. Godio, and L. Sambuelli, Application and comparison of three tomographic techniques for detection of decay in trees, Journal of Arboriculture, vol.29, issue.2, pp.66-78, 2003.

U. Nordmark, Knot Identification from CT Images of Young Pinus sylvestris Sawlogs Using Artificial Neural Networks, Scandinavian Journal of Forest Research, vol.51, issue.1, pp.72-78, 2002.
DOI : 10.1080/02827589908540792

U. Nordmark, Sawlogs Extracted from Computed Tomographic Images, Scandinavian Journal of Forest Research, vol.18, issue.2, pp.168-175, 2003.
DOI : 10.1080/02827580310003740

J. Nyström and D. E. Kline, Automatic classification of compression wood in green southern yellow pine, Wood and Fiber Science, vol.32, issue.3, pp.301-310, 2000.

M. Ohman and J. Nystrom, Measurement of Green Plank Shape for Prediction and Elimination of Compression Wood, Scandinavian Journal of Forest Research, vol.44, issue.4, pp.377-384, 2002.
DOI : 10.1007/BF00579521

J. Oja, Validation of Knot Models on Norway Spruce. Second IUFRO Workshop WP S 5.01-04Connection between silviculture and wood quality through modelling approaches and simulation software, 1996.

J. Oja and E. Temnerud, The appearance of resin pockets in CT-images of Norway spruce, Picea abies (L.) Karst.). Holz als Roh-und Werkstoff, pp.400-406, 1999.

J. Oja, Evaluation of knot parameters measured automatically in CT-images of Norway spruce, pp.375-379, 2000.

G. Parziale and A. Rinnhofer, Resin Pocket Enhancement through Anisotropic Diffusion, Fifth International Conference on Image Processing and Scanning of Wood, pp.161-170, 2003.

A. J. Petutschnigg, M. Flach, and H. Katz, Decay recognition for spruce in CT-images, pp.219-223, 2002.

I. Pinto, H. Pereira, and A. Usenius, Analysis of log shape and internal knots in twenty Maritime pine (Pinus pinaster Ait.) stems based on visual scanning and computer aided reconstruction, Annals of Forest Science, vol.60, issue.2, pp.137-144, 2003.
URL : https://hal.archives-ouvertes.fr/hal-00883687

I. Pinto, H. Pereira, and A. Usenius, Heartwood and sapwood development within maritime pine (Pinus pinaster Ait.) stems. Trees-Structure and Function, pp.284-294, 2004.
DOI : 10.1007/s00468-003-0305-8
URL : http://dx.doi.org/10.1007/s00468-003-0305-8

H. Polge, D??limitation de l'aubier et du bois de coeur par analyse densitom??trique de clich??s radiographiques, Annales des Sciences Foresti??res, vol.21, issue.4, pp.605-623, 1964.
DOI : 10.1051/forest/19640404

H. Polge, ??tablissement des courbes de variation de la densit?? du bois par exploration densitom??trique de radiographies d'??chantillons pr??lev??s ?? la tari??re sur des arbres vivants : applications dans les domaines Technologique et Physiologique, Thèse de Doctorat ès-Sciences Appliquées, p.pp, 1966.
DOI : 10.1051/forest/19660101

J. Radon, Über die bestimmung von funktionen durch ihre integralwerte längs gewisser mannigfaltigkeiten, Berichte Sächsische Akadamie der WissenschaftenPhys. Kl, vol.69, pp.262-277, 1917.
DOI : 10.1090/psapm/027/692055

M. R. Rauschkolb, Algorithms for automatic tree ring identification and measurement. Thesis Submitted to the Faculty Mississippi State University in Partial Fulfillment of the Requirements for the Degree of Master of science in the, p.pp, 1994.

S. Rust, Comparison of three methods for determining the conductive xylem area of Scots pine (Pinus sylvestris), Forestry, vol.72, issue.2, pp.103-108, 1999.
DOI : 10.1093/forestry/72.2.103

L. Saint-andré, Modélisation tridimensionnelle des profils de largeur de cerne dans un billon d'Epicéa commun (Picea abies Karst.) compte tenu de la mesure de son enveloppe externe et des caractéristique dendrométriques usuelles de l'arbre d'origine, 1998.

L. Saint-andré, R. Daquitaine, and J. Leban, Modelling the pith location and the ring shape in the stem using the external tree profile. Case study on Norway spruce, pp.5-12, 1999.

L. Saint-andré, J. C. Hervé, and J. M. Leban, Modelling the Number of Rings in Individual Logs of Norway Spruce, Scandinavian Journal of Forest Research, vol.15, issue.1, pp.35-143, 2000.
DOI : 10.1080/02827580050160574

L. Saint-andré and J. M. Leban, An elliptical model for tree ring shape in transverse section, Methodology and case study on Norway Spruce. Holz als Roh-und Werkstoff, pp.368-374, 2000.

L. Saint-andré and J. M. Leban, A model for the pith position and ring eccentricity in transverse sections of Norway spruce logs, Holz als Roh-und Werkstoff, pp.137-144, 2001.

E. Sarigul, A. L. Abbott, and D. L. Schmoldt, Rule-driven defect detection in CT images of hardwood logs, Computers and Electronics in Agriculture, vol.41, issue.1-3, pp.101-119, 2003.
DOI : 10.1016/S0168-1699(03)00046-2

K. C. Schad, D. L. Schmoldt, and R. J. Ross, Nondestructive Methods for Detecting Defects in Softwood Logs, 1996.

D. L. Schmoldt, J. He, and A. L. Abbott, Classifying features in CT imagery: accuracy for some single and multispecies classifiers. The 3rd International Seminar, Scanning Technology and Image Processing on Wood, pp.17-19, 1998.

D. L. Schmoldt, L. G. Occena, A. L. Abbott, and N. K. Gupta, NONDESTRUCTIVE EVALUATION OF HARDWOOD LOGS: CT SCANNING, MACHINE VISION AND DATA UTILIZATION, Nondestructive Testing and Evaluation, vol.24, issue.5, pp.279-309, 1999.
DOI : 10.1006/jvci.1994.1004

D. L. Schmoldt, J. He, and A. L. Abbott, Automated labeling of log features in CT imagery of multiple hardwood species, Wood and Fiber Science, vol.32, issue.3, pp.287-300, 2000.

D. L. Schmoldt, E. Scheinman, A. Rinnhofer, and L. G. Occena, Internal Log Scanning: Research to Reality. Twenty-eighth Annual Hardwood Symposium, pp.103-114, 2000.

V. Schwartz-spornberger, Untersuchungen an Bäumen mit Hilfe eines Computer-Tomographen. Inaugural-Dissertation zur Erlangung der Doktorwürde des Fachbereichs Biologie der Philipps, 1990.

U. Seeling, G. Becker, and C. Schwarz, Stand der Buchenrotkernforschung und zerstörungsfreie Erfassung des Rotkerns bei Buche (Fagus sylvatica L.) [State of the research on beech red heart and nondestructive detection of red heart of beech (Fagus sylvatica L, p.pp, 1999.

P. Sepulveda, J. Oja, and A. Grönlund, Predicting spiral grain by computed tomography of Norway spruce, Journal of Wood Science, vol.37, issue.1, pp.479-483, 2002.
DOI : 10.1007/BF00766643

P. Sepulveda, D. E. Kline, and J. Oja, Prediction of fiber orientation in Norway spruce logs using an X-ray log scanner: A preliminary study, Wood and Fiber Science, vol.35, issue.3, pp.421-428, 2003.

K. Shinozaki, K. Yoda, K. Hozumi, and T. Kira, A quantitative analysis of plant form -the pipe model theory, I. basic analysis, Japanese Journal of Ecology, vol.14, pp.97-105, 1964.

K. Shinozaki, K. Yoda, K. Hozumi, and T. Kira, A quantitative analysis of plant form -the pipe model theory, II. Further evidence of the theory and its application in forests ecology, Japanese Journal of Ecology, vol.14, pp.133-139, 1964.

P. Sjöberg, Image analysis of annual ring pattern for prediction of wood quality, 2001.

P. Sjöberg, P. Danielsson, and M. M. Seger, Image analysis of annual ring pattern for prediction of wood quality, Proceedings SSAB'01, Symposium on Image Analysis, pp.14-15, 2001.

T. Sliwa, P. Brunet, Y. Voisin, O. Morel, C. Stolz et al., Détection automatique des stries de croissance des arbres par transformée en ondelettes, The 16th International Conference on Vision Interface, pp.11-13, 2003.

P. Soille and L. Misson, Tree ring area measurements using morphological image analysis, Canadian Journal of Forest Research, vol.31, issue.6, pp.31-1074, 2001.
DOI : 10.1139/x01-025

S. Som, J. Davis, P. Wells, and I. Svalbe, Morphology Methods for Processing Tomographic Images of Wood, Digital Image Computing: Techniques and Applications (DICTA), pp.8-10, 1993.

S. Som, I. Svalbe, J. Davis, J. Grant, E. Gold et al., Internal Scanning of Logs for Grade Evaluation and Defect Location, Digital Image Computing: Techniques and Applications (DICTA), pp.6-8, 1995.

A. Stokes and S. Berthier, Irregular heartwood formation in Pinus pinaster Ait. is related to eccentric, radial, stem growth, Forest Ecology and Management, vol.135, issue.1-3, pp.1-3, 2000.
DOI : 10.1016/S0378-1127(00)00303-0

A. M. Taylor, B. L. Gartner, and J. J. Morrell, Heartwood Formation and Natural Durability A Review, Wood and Fiber Science, vol.34, issue.4, pp.587-611, 2002.

F. W. Taylor, F. G. Wagner, . Jr, C. W. Mcmillin, I. L. Morgan et al., Locating knots by industrial tomography -a feasibility study, Forest Products Journal, vol.34, issue.5, pp.42-46, 1984.

E. Temnerud and J. Oja, Vorl??ufige Studie zum Erfassen des wirklichen Volumens von Harztaschen mit Hilfe sterologischer Auswertung der CT-Bilder yon Fichtenrundholz, Holz als Roh-und Werkstoff, pp.193-200, 1998.
DOI : 10.1007/s001070050298

S. Thawornwong, L. G. Occena, and D. L. Schmoldt, Investigation of the Effect of Reducing Scan Resolution on Simulated Information-Augmented Sawing, Proceedings of the 4th International Conference on Image Processing and Scanning of Wood IPSW, 2000.

S. Thawornwong, L. G. Occena, and D. L. Schmoldt, Lumber value differences from reduced CT spatial resolution and simulated log sawing, Computers and Electronics in Agriculture, vol.41, issue.1-3, pp.1-3, 2003.
DOI : 10.1016/S0168-1699(03)00040-1
URL : https://naldc.nal.usda.gov/naldc/download.xhtml?id=16863&content=PDF

R. Tognetti, A. Raschi, C. Beres, A. Fenyvesi, and H. W. Ridder, Comparison of sap flow, cavitation and water status of Quercus petraea and Quercus cerris trees with special reference to computer tomography, Plant, Cell and Environment, vol.4, issue.8, pp.19-928, 1996.
DOI : 10.1146/annurev.arplant.40.1.19

C. M. Tsai and Z. H. Cho, Physics of contrast mechanism and averaging effect of linear attenuation coefficients in a computerized transverse axial tomography (CTAT) transmission scanner, Physics in Medicine and Biology, vol.21, issue.4, pp.544-559, 1976.
DOI : 10.1088/0031-9155/21/4/006

F. G. Wagner, F. W. Taylor, D. S. Ladd, C. W. Mcmillin, and F. L. Roder, Ultrafast CT scanning of an oak log for internal defects, Forest Products Journal, vol.39, pp.11-12, 1989.

M. Walter and L. J. Kucera, Vorkommen und Bedeutung verschiedener Kernformen bei der Buche (Fagus sylvatica L.) [Occurrence and importance of different heartwood types of beech (Fagus sylvatica L, Schweizerische Zeitschrift für Forstwesen, pp.142-391, 1991.

X. Wang, F. Divos, C. Pilon, B. K. Brashaw, R. J. Ross et al., Assessment of Decay in Standing Timber Using Stress Wave Timing Nondestructive Evaluation Tools, Gen, vol.12, p.pp, 2004.

. Warensjoe, . Mats, . Nylinder, and F. Walter, Modelling compression wood using data from a 3D-laser scanner. Fourth Workshop of IUFRO Working Party S5.01-04 "Connection between Silviculture and Wood Quality through Modelling Approaches and Simulation Softwares, 2002.

P. Wells, S. Som, and J. Davis, Automated Feature Extraction From Tomographic Images of Wood, Digital Image Computing: Techniques and Applications (DICTA), pp.4-6, 1991.

C. R. Wilson, Quantitative computed tomography Medical physics of CT and ultrasound-tissue imaging and characterization, 1980.

J. Wu and D. Liew, A Computer Vision Method for Detection of External Log Cracks and Pith in Log Cross-Section Images, World Automation Congress: International Symposium on Intelligent Automation and Control (ISIAC), 2000.

D. P. Zhu, R. W. Conners, and P. A. Araman, CT Image Sequence Processing for Wood Defect Recognition. The Twenty-third Southeastern Symposium on System Theory, 1991.
DOI : 10.1109/ssst.1991.138517

D. P. Zhu, R. W. Conners, F. Lamb, and P. A. Araman, A Computer Vision System for Locating and Identifying Internal Log Defects Using CT Imagery, Fourth International Conference on Scanning Technology in the Wood Industry, 1991.

D. P. Zhu, R. W. Conners, D. L. Schmoldt, and P. A. Araman, A Prototype Vision System for Analyzing CT Imagery of Hardwood Logs, IEEE Transactions on Systems, Man, and Cybernetics--Part B, 1996.

Z. Castell, W. Schrödl, S. Seifert, and T. , Volume Interpolation of CT Images from Tree Trunks, Plant Biology, vol.61, issue.6, pp.737-744, 2005.
DOI : 10.1080/02827589950152872

H. Zycha, ??ber die Kernbildung und verwandte Vorg??nge im Holz der Rotbuche, Forstwissenschaftliches Centralblatt, vol.21, issue.II, pp.80-109, 1948.
DOI : 10.1007/BF02083068

. -détection-de-la-limite-aubier, duramen dans les billons, y compris en présence des noeuds (principale source de difficulté) L'erreur sur le diamètre du duramen est de 1.8mm soit une erreur relative de 1.3%. ; -détection de la localisation des verticilles et une comparaison à une méthode optique