8.3.4 Clustering for Region Segmentation

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Eklundh, J.O., Yamamoto, H., and Rosenfeld, A.,
A Relaxation Method for Multispectral Pixel Classification,
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Earlier:
Relaxation Methods in Multispectral Pixel Classification,
UMD-TR-662, July 1978. Relaxation. Segmentation, Color. BibRef

Eklundh, J.O., Lansner, A., and Wessblad, R.,
Classification of Multispectral Images using Associative Nets,
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Eklundh, J.O.,
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Fukada, Y.,
Spatial Clustering Procedures for Region Analysis,
PR(12), No. 6, 1980, pp. 395-403.
WWW Version. BibRef 8000

Velasco, F.R.D.,
A Method for the Analysis of Gaussian-Like Clusters,
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WWW Version. BibRef 8000

Sarabi, A., and Aggarwal, J.K.,
Segmentation of Chromatic Images,
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WWW Version. BibRef 8100

Swain, P.H.[Philip H.], Vardeman, S.B.[Stephen B.], Tilton, J.C.[James C.],
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PR(13), No. 6, 1981, pp. 429-441.
WWW Version. BibRef 8100

Dondes, P.A., and Rosenfeld, A.,
Pixel Classification Based on Gray Level and Local 'Busyness',
PAMI(4), No. 1, January 1982, pp. 79-84. BibRef 8201

Dunn, S., Janos, L., Rosenfeld, A.,
Bimean Clustering,
PRL(1), 1983, pp. 169-173. BibRef 8300

Blanz, W.E., Reinhardt, E.R.,
Image Segmentation by Pixel Classification,
PR(13), No. 4, 1981, pp. 293-298.
WWW Version. BibRef 8100

Sclove, S.L.,
Application of the Conditional Population-Mixture Model to Image Segmentation,
PAMI(5), No. 4, July 1983, pp. 428-433. BibRef 8307
And: Reply to Comments: PAMI(6), No. 5, September 1984, pp. 657-658. BibRef

Titterington, D.M.,
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PAMI(6), No. 5, September 1984, pp. 656-657. BibRef 8409

Huntsberger, T.L., Jacobs, C.L., Cannon, R.L.,
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PR(18), No. 2, 1985, pp. 131-138.
WWW Version. BibRef 8500

Markham, K.C.,
Some Segmentation Processes for Application with a Spoke Filter,
PRL(5), 1987, pp. 329-335. BibRef 8700

Amadasun, M., King, R.A.,
Low-Level Segmentation of Multispectral Images via Agglomerative Clustering of Uniform Neighbourhoods,
PR(21), No. 3, 1988, pp. 261-268.
WWW Version. 0309 BibRef

Geong, D.S., and Lapsa, P.M.,
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PAMI(11), No. 4, April 1989, pp. 357-371.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 8904

Zhang, J., and Modestino, J.W.,
A Model-Fitting Approach to Cluster Validation with Application to Stochastic Model-Based Image Segmentation,
PAMI(12), No. 10, October 1990, pp. 1009-1017.
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WWW Version. BibRef 9010

Langan, D.A., Modestino, J.W., Zhang, J.,
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IP(7), No. 2, February 1998, pp. 180-195.
WWW Version. 9802 BibRef
Earlier: ICIP94(II: 197-201).
WWW Version. 9411 See also Maximum-Likelihood Parameter Estimation for Unsupervised Stochastic Model-Based Image Segmentation. BibRef

Jolion, J.M.[Jean-Michel], Meer, P.[Peter], and Bataouche, S.[Samira],
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PAMI(13), No. 8, August 1991, pp. 791-802.
IEEE Abstract. IEEE Top Reference.
WWW Version. Robust Technique. BibRef 9108

Jolion, J.M.[Jean-Michel], Meer, P.[Peter], and Rosenfeld, A.[Azriel],
Generalized Minimum Volume Ellipsoid Clustering with Applications in Computer Vision,
Robust90(339-351). BibRef 9000

Bataouche, S.[Samira], and Jolion, J.M.[Jean-Michel],
A Hierarchical and Robust Process for Information Retrieval,
IAP(510-517), 1989. BibRef 8900

Pla, F., Juste, F., Ferri, F., and Vicens, M.,
Colour Segmentation Based on a Light Reflection Model to Locate Citrus Fruits for Robotic Harvesting,
CompAgri(9), 1993, pp. 53-70. Generate classes from one image and use for the rest of sequnce. BibRef 9300

Ng, I., Kittler, J.V., Illingworth, J.,
Supervised Segmentation Using a Multiresolution Data Representation,
SP(31), 1993, pp. 133-163. BibRef 9300

Uchiyama, T., and Arbib, M.A.,
Color Image Segmentation Using Competitive Learning,
PAMI(16), No. 12, December 1994, pp. 1197-1206.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9412
Earlier:
Object Extraction System from a Color Image,
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Schroeter, P., Bigün, J.,
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PR(28), No. 5, May 1995, pp. 695-709.
WWW Version. Problems due to different size regions. BibRef 9505

Pappas, T.N., and Jayant, N.S.,
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ICCV88(310-315).
IEEE Abstract. IEEE Top Reference. BibRef 8800

Krishnapuram, R., and Freg, C.P.,
Fuzzy Algorithms to Find Linear and Planar Clusters and Their Application,
CVPR91(426-431).
IEEE Abstract. IEEE Top Reference. BibRef 9100

Panda, D.P.,
Segmentation of FLIR Images by Pixel Classification,
UMD-CS TR-508, February 1977. BibRef 7702
And: DARPA77(65-70). Segmentation as a point wise classification problem. Set of features and define decision surface; gray level and edge values together <== using a joint histogram (2-D); valleys selected manually. BibRef

Therrien, C.W.[Charles W.],
An Estimation-Theoretic Approach to Terrain Image Segmentation,
CVGIP(22), No. 3, June 1983, pp. 313-326. BibRef 8306
Earlier:
Linear Filtering Models for Texture Classification and Segmentation,
ICPR80(1132-1135). Segmentation based on texture classification (pick sample areas to get statistics) maximum likelihood is poor, maximum a posteriori estimation is better. BibRef

Therrien, C.W.,
Multi-channel Filtering Methods for Segmentation of Color Images,
CVPR85(637-639). (Naval Postgraduate School) Obvious. BibRef 8500

Zhang, M.C., Haralick, R.M., Campbell, J.B.,
Multispectral Image Context Classification Using Stochastic Relaxation,
SMC(20), 1990, pp. 128-140. BibRef 9000

Knapman, J., Dickson, W.,
Hierarchical Probabilistic Image Segmentation,
IVC(12), No. 7, September 1994, pp. 447-457.
WWW Version. BibRef 9409

Zheng, Y.J.,
Feature-Extraction and Image Segmentation Using Self-Organizing Networks,
MVA(8), No. 5, 1995, pp. 262-274.
HTML Version. BibRef 9500

Simpson, J.J., Keller, R.H.,
An Improved Fuzzy-Logic Segmentation of Sea-Ice, Clouds, and Ocean in Remotely-Sensed Arctic Imagery,
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Olariu, S., Rao, N.S.V.,
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Rao, N.S.V., Oblow, E.M., Glover, C.W.,
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PAMI(16), No. 7, July 1994, pp. 765-768.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9407
Earlier: ICPR92(II:603-606).
WWW Version. 9208 BibRef

Salzenstein, F., Pieczynski, W.,
Parameter-Estimation in Hidden Fuzzy Markov Random-Fields and Image Segmentation,
GMIP(59), No. 4, July 1997, pp. 205-220. 9709 BibRef

Salzenstein, F., Collet, C.,
Fuzzy Markov Random Fields versus Chains for Multispectral Image Segmentation,
PAMI(28), No. 11, November 2006, pp. 1753-1767.
WWW Version. 0609Comparison of fuzzy Markov chain with fuzzy random field models. BibRef

Salzenstein, F., Collet, C., Lecam, S., Hatt, M.,
Non-stationary fuzzy Markov chain,
PRL(28), No. 16, December 2007, pp. 2201-2208.
WWW Version. 0711Fuzzy Markov chain; Triplet Markov chain; Non-stationary chain; Multispectral image segmentation BibRef

Flitti, F., Collet, C.,
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WWW Version. 0803 BibRef

Pieczynski, W.[Wojciech],
Statistical Image Segmentation,
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Pieczynski, W.[Wojciech],
Hidden Evidential Markov Trees and Image Segmentation,
ICIP99(I:338-342).
IEEE Abstract. IEEE Top Reference. BibRef 9900

Salzenstein, F., Collet, C., Petremand, M.,
Champs de Markov Flous pour Imagerie Multispectrale-Fuzzy Markov Random Fields for Multispectral Images,
Traitement du Signal(21), No. 1, 2004, pp. 37-55. BibRef 0400

Derrode, S., Mercier, G., Pieczynski, W.,
Unsupervised multicomponent image segmentation combining a vectorial HMC Model and ICA,
ICIP03(II: 407-410).
IEEE Abstract. IEEE Top Reference. 0312 BibRef

Kudo, M., Yanagi, S., Shimbo, M.,
Construction of Class Regions by a Randomized Algorithm: A Randomized Subclass Method,
PR(29), No. 4, April 1996, pp. 581-588.
WWW Version. BibRef 9604

Jain, A.K.[Anil K.], and Flynn, P.J.[Patrick J.],
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AIU96(65-83). BibRef 9600

Tanaka, E.,
A Metric between Unrooted and Unordered Trees and Its Bottom-Up Computing Method,
PAMI(16), No. 12, December 1994, pp. 1233-1238.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9412

Mukherjee, D.P., Pal, P., Das, J.,
Sonar Image Segmentation by Fuzzy C-Means,
SP(54), No. 3, November 1996, pp. 295-301. 9701 BibRef

Abrantes, A.J., Marques, J.S.,
Class of Constrained Clustering Algorithms for Object Boundary Extraction,
IP(5), No. 11, November 1996, pp. 1507-1521.
WWW Version. 9611 BibRef

Priebe, C.E.[Carey E.], Marchette, D.J., Rogers, G.W.,
Segmentation of Random-Fields via Borrowed Strength Density-Estimation,
PAMI(19), No. 5, May 1997, pp. 494-499.
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WWW Version. 9705Segmentation using clustering of subregions. BibRef

Ceballos, J.C., Bottino, M.J.,
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Gupta, L., Sortrakul, T.,
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WWW Version. 9802 BibRef

Kubota, T., Huntsberger, T.,
Adaptive Pattern-Recognition System for Scene Segmentation,
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Kartikeyan, B., Sarkar, A., Majumder, K.L.,
A Segmentation Approach to Classification of Remote Sensing Imagery,
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Bianchi, N., Bottoni, P., Mussio, P., Spinu, C., Garbay, C.,
Situated Image Understanding in a Multiagent Framework,
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Bianchi, N., Bottoni, P., Spinu, C., Garbay, C., Mussio, P.,
A Dynamical Organisation for Situated Image Interpretation,
ICPR96(I: 228-232).
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Shen, X.Q., Spann, M., Nacken, P.,
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Mandal, D.P., Murthy, C.A., Pal, S.K.,
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Suri, J.S.[Jasjit S.], Haralick, R.M.[Robert M.], Sheehan, F.H.[Florence H.],
Greedy Algorithm for Error Correction in Automatically Produced Boundaries from Low Contrast Ventriculograms,
MVA(11), No. 6, 2000, pp. 39-60.
HTML Version. 0005 BibRef
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Linear vs. Quadratic Optimization Algorithms for Bias Correction of Left Ventricle Chamber Boundaries in Low Contrast Projection Ventriculograms Produced from Xray Cardiac Catheterization Procedure,
CAIP99(108-117).
WWW Version. 9909 BibRef
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Correction of Systematic Errors in Automatically Produced Boundaries from Low Contrast Ventriculograms,
ICPR96(IV: 361-365).
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Suri, J.S.[Jasjit S.], Wu, D.[Dee], Reden, L.[Laura], Gao, J.B.[Jian-Bo], Singh, S.[Sameer], Laxminarayan, S.[Swamy],
Modeling Segmentation Via Geometric Deformable Regularizers, Pde And Level Sets In Still And Motion Imagery: A Revisit,
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Rhouma, M.B.H.[Mohamed Ben Hadj], Frigui, H.[Hichem],
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Shimbo, M.[Masaru],
Fast Labelling of Natural Scenes Using Enhanced Knowledge,
PAA(4), No. 1, 2001, pp. 20-27.
HTML Version. 0105 BibRef

Fan, G.L.[Guo-Liang], Xia, X.G.[Xiang-Gen],
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IEEE Top Reference. 0201 BibRef
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IEEE Top Reference. 0203 BibRef
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Multiscale Texture Segmentation Using Hybrid Contextual Labeling Tree,
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IEEE Abstract. IEEE Top Reference. 0008 BibRef

Papin, C., Bouthemy, P., Rochard, G.,
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IEEE Top Reference. 0203 BibRef
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Detection of low clouds in METEOSAT IR night-time images based on a contextual spatio-temporal labeling approach,
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WWW Version. 9810 BibRef

Sgrenzaroli, M., Baraldi, A., Eva, H., de Grandi, G., Achard, F.,
Contextual clustering for image labeling: an application to degraded forest assessment in Landsat TM images of the Brazilian Amazon,
GeoRS(40), No. 8, August 2002, pp. 1833-1848.
IEEE Top Reference. 0210 BibRef

Colombo, S.[Sergio], Chica-Olmo, M.[Mario], Abarca, F.[Francisco], Eva, H.[Hugh],
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WWW Version. 0411 BibRef

Martínez, A.M.[Aleix M.], Mittrapiyanuruk, P.[Pradit], Kak, A.C.[Avinash C.],
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CVIU(95), No. 1, July 2004, pp. 72-85.
WWW Version. 0407Alternative implementation of the k-way Ncut approach for image segmentation. Uses the clustering algorithm of Koontz and Fukunaga ( See also Application of the Karhunen-Loeve Expansion to Feature Selection and Ordering. ) which automatically chooses the number of clusters. BibRef

Farmer, M.E., Jain, A.K.,
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WWW Version. 0512 BibRef
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WWW Version. 0409 BibRef

Lázaro, J.[Jesús], Arias, J.[Jagoba], Martín, J.L.[José L.], Zuloaga, A.[Aitzol], Cuadrado, C.[Carlos],
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PRL(27), No. 16, December 2006, pp. 1991-1997.
WWW Version. 0611Thresholding; Clustering; Self organizing map BibRef

Pavan, M.[Massimiliano], Pelillo, M.[Marcello],
Dominant Sets and Pairwise Clustering,
PAMI(29), No. 1, January 2007, pp. 167-172.
WWW Version. 0701 BibRef
Earlier:
Efficiently Segmenting Images with Dominant Sets,
ICIAR04(I: 17-24).
WWW Version. 0409 BibRef
Earlier:
Dominant sets and hierarchical clustering,
ICCV03(362-369).
WWW Version. 0311 BibRef
And:
A new graph-theoretic approach to clustering and segmentation,
CVPR03(I: 145-152).
IEEE Abstract. IEEE Top Reference. 0307 BibRef

cluster based on dominant vertices in graph representation. See also Spatio-temporal Segmentation Using Dominant Sets.

Sperotto, A.[Anna], Pelillo, M.[Marcello],
Szemerédi's Regularity Lemma and Its Applications to Pairwise Clustering and Segmentation,
EMMCVPR07(13-27).
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Zoller, T.[Thomas], Buhmann, J.M.[Joachim M.],
Robust Image Segmentation Using Resampling and Shape Constraints,
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WWW Version. 0706 BibRef
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Shape constrained image segmentation by parametric distributional clustering,
CVPR04(I: 386-393).
IEEE Abstract. IEEE Top Reference. 0408 BibRef

Hermes, L.[Lothar], Zöller, T.[Thomas], Buhmann, J.M.[Joachim M.],
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ECCV02(III: 577 ff.).
HTML Version. 0205 BibRef

Hermes, L., Buhmann, J.M.,
Contextual Classification by Entropy-Based Polygonization,
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Komodakis, N.[Nikos], Tziritas, G.[Georgios],
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WWW Version. 0707 BibRef
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A New Framework for Approximate Labeling via Graph Cuts,
ICCV05(II: 1018-1025).
WWW Version. 0510 BibRef

Chang, H.[Hong], Yeung, D.Y.[Dit-Yan],
Robust path-based spectral clustering,
PR(41), No. 1, January 2008, pp. 191-203.
WWW Version. 0710 BibRef
Robust Path-Based Spectral Clustering with Application to Image Segmentation,
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WWW Version. 0510Path-based clustering; Spectral clustering; Robust statistics; Unsupervised learning; Semi-supervised learning; Image segmentation BibRef

Kohli, P.[Pushmeet], Torr, P.H.S.[Philip H. S.],
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PAMI(29), No. 12, December 2007, pp. 2079-2088.
WWW Version. 0711 BibRef
Earlier:
Measuring Uncertainty in Graph Cut Solutions: Efficiently Computing Min-marginal Energies Using Dynamic Graph Cuts,
ECCV06(II: 30-43).
WWW Version. 0608 BibRef
Earlier:
Efficiently Solving Dynamic Markov Random Fields Using Graph Cuts,
ICCV05(II: 922-929).
WWW Version. 0510mincut/max-flow problem. Given the solution of the max-flow problem on a graph, the dynamic algorithm efficiently computes the maximum flow in a modified version of the graph. Apply to object background segmentation in video. BibRef

Zhu-Jacquot, J.[Jie],
Graph Cuts Segmentation with Geometric Shape Priors for Medical Images,
Southwest08(109-112).
WWW Version. 0803 BibRef

El-Melegy, M.[Moumen], Zanaty, E.A., Abd-Elhafiez, W.M.[Walaa M.], Farag, A.[Aly],
On Cluster Validity Indexes in Fuzzy and Hard Clustering Algorithms for Image Segmentation,
ICIP07(VI: 5-8).
WWW Version. 0709 BibRef

Zhao, Y.J.[Yan-Jun], Wang, T.[Tao], Wang, P.[Peng], Hu, W.[Wei], Du, Y.Z.[Yang-Zhou], Zhang, Y.M.[Yi-Min], Xu, G.Y.[Guang-You],
Scene Segmentation and Categorization Using NCuts,
SLAM07(1-7).
WWW Version. 0706 BibRef

Sormann, M.[Mario], Zach, C.[Christopher], Bauer, J.[Joachim], Karner, K.[Konrad], Bishof, H.[Horst],
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SCIA07(393-402).
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Sormann, M.[Mario], Zach, C.[Christopher], Karner, K.[Konrad],
Graph Cut Based Multiple View Segmentation for 3D Reconstruction,
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WWW Version. 0606 BibRef

Feng, W.[Wei], Liu, Z.Q.A.[Zhi-Qi-Ang],
Self-Validated and Spatially Coherent Clustering with Net-Structured MRF and Graph Cuts,
ICPR06(IV: 37-40).
WWW Version. 0609 BibRef

Kumar, M.P.[M. Pawan], Torr, P.H.S.[Philip H. S.], Zisserman, A.[Andrew],
Solving Markov Random Fields using Second Order Cone Programming Relaxations,
CVPR06(I: 1045-1052).
WWW Version. 0606 BibRef
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An Object Category Specific MRF for Segmentation,
CLOR06(596-616).
WWW Version. 0711 BibRef

Cleju, I.[Ioan], Fränti, P.[Pasi], Wu, X.L.[Xiao-Lin],
Clustering Based on Principal Curve,
SCIA05(872-881).
WWW Version. 0506 BibRef

Wang, L.[Lei], Ji, H.B.[Hong-Bing], Gao, X.[Xinbo],
Image Segmentation by a Robust Clustering Algorithm Using Gaussian Estimator,
ICIAR04(I: 74-81).
WWW Version. 0409 BibRef

Zabih, R.[Ramin], Kolmogorov, V.[Valdimir],
Spatially coherent clustering using graph cuts,
CVPR04(II: 437-444).
IEEE Abstract. IEEE Top Reference. 0408Segmentation by clustering. BibRef

Shental, N., Zomet, A., Hertz, T., Weiss, Y.,
Learning and Inferring Image Segmentations Using the GBP Typical Cut Algorithm,
ICCV03(1243-1250).
WWW Version. 0311Issues in clustering. BibRef

Wesolkowski, S.[Slawo], Fieguth, P.W.[Paul W.],
Hierarchical Region Mean-Based Image Segmentation,
CRV06(30-30).
WWW Version. 0607 BibRef
Earlier:
Hierarchical Regions for Image Segmentation,
ICIAR04(I: 9-16).
WWW Version. 0409 BibRef
Earlier:
A probabilistic framework for image segmentation,
ICIP03(II: 451-454).
IEEE Abstract. IEEE Top Reference. 0312 See also Highlight and Shading Invariant Color Image Segmentation Using Simulated Annealing. BibRef

Legal-Ayala, H.A., Facon, J.,
Segmentation approach by learning: different image applications,
CIAP03(600-604).
IEEE Abstract. IEEE Top Reference. 0310 BibRef

Ren, X.F.[Xiao-Feng], Malik, J.,
Learning a classification model for segmentation,
ICCV03(10-17).
WWW Version. 0311 BibRef

Singh, M.K., Ahuja, N.,
Mean-shift segmentation with wavelet-based bandwidth selection,
WACV02(43-47).
IEEE Abstract. IEEE Top Reference. 0303 BibRef

Mukherjee, D.P., Mohanta, P.P., Acton, S.T.,
Agglomerative clustering of feature data for image segmentation,
ICIP02(III: 269-272).
IEEE Abstract. IEEE Top Reference. 0210 BibRef
Earlier: A2, A1, A3:
Agglomerative clustering for image segmentation,
ICPR02(I: 664-667).
WWW Version. 0211 BibRef

Roula, M.A., Bouridane, A., Kurugollu, F., Amira, A.,
Unsupervised segmentation of multispectral images using edge progression and cost function,
ICIP02(III: 781-784).
IEEE Abstract. IEEE Top Reference. 0210 BibRef

Romano, R., Vitulano, D.,
A Variational Representation for Efficient Noisy Segmentation,
WSCG02(POS-41).
Postscript Version.
HTML Version. 0209 BibRef

Aronsson, M.[Mattias], Borgefors, G.[Gunilla],
2D Segmentation and Labelling of Clustered Ring Shaped Objects,
SCIA01(P-W4A). 0206 BibRef

Keslassy, I., Kalman, M., Wang, D., Girod, B.,
Classification of Compound Images Based on Transform Coefficient Likelihood,
ICIP01(I: 750-753).
IEEE Abstract. IEEE Top Reference. 0108 BibRef

Pham, T.,
Image Segmentation Using Probabilistic Fuzzy C-means Clustering,
ICIP01(I: 722-725).
IEEE Abstract. IEEE Top Reference. 0108 BibRef

Noordam, J.C., van den Broek, W.H.A.M., Buydens, L.M.C.,
Geometrically Guided Fuzzy C-means Clustering for Multivariate Image Segmentation,
ICPR00(Vol I: 462-465).
WWW Version.
HTML Version. 0009 BibRef

Venkatachalam, V.,
Image Classification Using Pseudo Power Signatures,
ICIP00(Vol I: 796-799).
IEEE Abstract. IEEE Top Reference. 0008 BibRef

Voles, P., Smith, A., Teal, M.,
Nautical Scene Segmentation using Variable Size Image Windows and Feature Space Reclustering,
ECCV00(II: 324-335).
WWW Version. 0003 BibRef

Schweitzer, H.[Haim],
Utilizing Scatter for Pixel Subspace Selection,
ICCV99(1111-1116).
WWW Version. Use scatter matrix for clustering and indexing. BibRef 9900

Chardin, A.[Annabelle], Perez, P.[Patrick],
Mode of Posterior Marginals with Hierarchical Models,
ICIP99(I:324-328).
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Shen, X., and Spann, M.,
Segmentation of 2D and 3D Images Through a Hierarchical Clustering Based on Region Modelling,
ICIP97(III: 50-53).
WWW Version. BibRef 9700

Weiss, Y.[Yair],
Segmentation using Eigenvectors: A Unifying View,
ICCV99(975-982).
WWW Version. BibRef 9900

Glasbey, C.A.,
Ultrasound Image Segmentation Using a Point Distribution Model in a Bayesian Framework,
BMVC96(Features, Segmentation). 9608University of Edinburgh BibRef

Cortijo, F.J., de la Blanca, N.P.[N. Perez],
Automatic Estimation of the LVQ-1 Parameters: Applications to Multispectral Image Classification,
ICPR96(IV: 346-350).
WWW Version. 9608(Univ. de Granada, E) BibRef

Olk, J., Jonker, P.,
Bucket Processing: a Paradigm for Image Processing,
ICPR96(IV: 386-390).
WWW Version. 9608(Delft Univ. of Technology, NL) BibRef

Mari, M., Dellepiane, S.G.,
A Segmentation Method Based on Fuzzy Topology and Clustering,
ICPR96(II: 565-569).
WWW Version. 9608(Univ. di Genoa, I) BibRef

Wegner, S., Harms, T., Oswald, H., Fleck, E.,
The watershed transformation on graphs for the segmentation of CT images,
ICPR96(III: 498-502).
WWW Version. 0509 BibRef
Earlier:
Medical image segmentation using the watershed transformation on graphs,
ICIP96(III: 37-40).
WWW Version. 9610Image Segmentation for a Hyperthermia Planning Environment BibRef

Wegner, S., Harms, T., Builtjes, J.H., Oswald, H., Fleck, E.,
The watershed transformation for multiresolution image segmentation,
CIAP95(31-36).
WWW Version. 9509 BibRef

Umesh Adiga, U., Chaudhuri, B.B.,
Semi-Automatic Segmentation of Tissue Cells from Confocal Microscope Images,
ICPR96(III: 494-497).
WWW Version. 9608(Indian Statistical Institute, IND) BibRef

Gong, Y., Chuan, C., Guo, X.,
An Effective Color Image Segmentation Method for Handling Images under Uneven Illumination,
ICPR96(C82.1). 9608(Nanyang Technological Univ., SGP) BibRef

Ido, S., Arai, S., Takamatsu, R., Sato, M.,
Stimulus-Driven Segmentation By Gaussian Functions,
ICPR96(II: 487-491).
WWW Version. 9608(Tokyo Inst. of Technology, J) BibRef

Dugelay, S., Augustin, J., Graffigne, C.,
Segmentation of Multibeam Acoustic Imagery in the Exploration of the Deep Sea-Bottom,
ICPR96(II: 437-446).
WWW Version. 9608(Ifremer Centre de Brest, F) BibRef

Atmaca, H.[Hamdi], Bulut, M., Demir, D.,
Histogram Based Fuzzy Kohonen Clustering Network for Image Segmentation,
ICIP96(II: 951-954).
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Ferryman, T.A., Bhanu, B.,
A Bayesian Approach for the Segmentation of SAR Images Using Dynamically Selected Neighborhoods,
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Pudil, P.[Pavel], Novovicová, J.[Jana], Ferri, F.[Francesc], Kittler, J.V.[Josef V.],
Advances in the statistical methodology for the selection of image descriptors for visual pattern representation and classification,
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Ichimura, N.,
Inexhaustive region segmentation by robust clustering,
ICIP95(III: 77-80).
WWW Version. 9510 BibRef

Zhou, J.[Jing], Fang, X.[Xiang], Ghosh, B.J.,
Image segmentation based on multiresolution filtering,
ICIP94(III: 483-487).
WWW Version. 9411 BibRef

Herlin, I.L., Nguyen, C., Graffigne, C.,
Stochastic Segmentation of Ultrasound Images,
ICPR92(I:289-292).
WWW Version. BibRef 9200

Fassnacht, C., Devijver, P.A.,
Image Segmentation With A Propagator Markov Mesh Model,
ICPR94(A:510-513).
WWW Version. BibRef 9400

Bruynooghe, M.,
A very efficient strategy for very large data sets clustering: application to image segmentation,
ICPR88(I: 623-627).
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Zucker, S.W., Leclerc, Y.G.,
Intensity Clustering by Relaxation,
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Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Unsupervised Clustering and Optimal Clusters for Segmentation .