8.3.4 Clustering for Region Segmentation

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Pla, F., Juste, F., Ferri, F., and Vicens, M.,
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Ng, I., Kittler, J.V., Illingworth, J.,
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Linear Filtering Models for Texture Classification and Segmentation,
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Salzenstein, F., Pieczynski, W.,
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Salzenstein, F., Collet, C.,
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Salzenstein, F., Collet, C., Lecam, S., Hatt, M.,
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Pieczynski, W.[Wojciech],
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Salzenstein, F., Collet, C., Petremand, M.,
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Derrode, S., Mercier, G., Pieczynski, W.,
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Kudo, M., Yanagi, S., Shimbo, M.,
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Jain, A.K.[Anil K.], and Flynn, P.J.[Patrick J.],
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Tanaka, E.,
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Mukherjee, D.P., Pal, P., Das, J.,
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Abrantes, A.J., Marques, J.S.,
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Priebe, C.E.[Carey E.], Marchette, D.J., Rogers, G.W.,
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Mandal, D.P., Murthy, C.A., Pal, S.K.,
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Sgrenzaroli, M., Baraldi, A., Eva, H., de Grandi, G., Achard, F.,
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Martínez, A.M.[Aleix M.], Mittrapiyanuruk, P.[Pradit], Kak, A.C.[Avinash C.],
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WWW Version. 0701 BibRef
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WWW Version. 0311 BibRef
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Hermes, L., Buhmann, J.M.,
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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

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Cleju, I.[Ioan], Fränti, P.[Pasi], Wu, X.L.[Xiao-Lin],
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Wang, L.[Lei], Ji, H.B.[Hong-Bing], Gao, X.[Xinbo],
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Zabih, R.[Ramin], Kolmogorov, V.[Valdimir],
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Shental, N., Zomet, A., Hertz, T., Weiss, Y.,
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Wesolkowski, S.[Slawo], Fieguth, P.W.[Paul W.],
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Hierarchical Regions for Image Segmentation,
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WWW Version. 0409 BibRef
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WWW Version. 0311 BibRef

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Mukherjee, D.P., Mohanta, P.P., Acton, S.T.,
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ICPR02(I: 664-667).
WWW Version. 0211 BibRef

Roula, M.A., Bouridane, A., Kurugollu, F., Amira, A.,
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Noordam, J.C., van den Broek, W.H.A.M., Buydens, L.M.C.,
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Venkatachalam, V.,
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Voles, P., Smith, A., Teal, M.,
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Schweitzer, H.[Haim],
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Shen, X., and Spann, M.,
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ICIP97(III: 50-53).
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Weiss, Y.[Yair],
Segmentation using Eigenvectors: A Unifying View,
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Glasbey, C.A.,
Ultrasound Image Segmentation Using a Point Distribution Model in a Bayesian Framework,
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Cortijo, F.J., de la Blanca, N.P.[N. Perez],
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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).
WWW Version. BibRef 9600

Ferryman, T.A., Bhanu, B.,
A Bayesian Approach for the Segmentation of SAR Images Using Dynamically Selected Neighborhoods,
ARPA96(891-896). BibRef 9600

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,
CAIP95(832-837).
WWW Version. 9509 BibRef

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).
WWW Version. 8811 BibRef

Zucker, S.W., Leclerc, Y.G.,
Intensity Clustering by Relaxation,
PRAI-78(192-197). BibRef 7800

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Unsupervised Clustering and Optimal Clusters for Segmentation .