8.4.2 Watershed Algorithms, Watershed Segmentation

Chapter Contents (Back)
Watershed. Segmentation, Watershed.

Beucher, S.,
Watersheds of Functions and Picture Segmentation,
ICASSP82(1928-1931). The original watershed paper. See also Segmentation Tools in Mathematical Morphology. BibRef 8200

Meyer, F., and Beucher, S.,
Morphological Segmentation,
JVCIR(1), No. 1, September 1990, pp. 21-46. Watershed technique. BibRef 9009

Meyer, F.,
Topographic Distance and Watershed Lines,
SP(38), No. 1, July 1994, pp. 113-125. BibRef 9407

Meyer, F.,
Flooding and Segmentation,
MMAISP00(189-198). BibRef 0001

Meyer, F.,
Stochastic watershed hierarchies,
ICAPR15(1-8)
IEEE DOI 1511
image segmentation BibRef

Watson, A.I.,
A New Method of Classification for Landsat Data Using the 'Watershed' Algorithm,
PRL(6), 1987, pp. 15-19. BibRef 8700

Vincent, L., and Soille, P.[Pierre],
Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations,
PAMI(13), No. 6, June 1991, pp. 583-598.
IEEE DOI Description of Watershed techniques. BibRef 9106

Najman, L., Schmitt, M.,
Geodesic Saliency of Watershed Contours and Hierarchical Segmentation,
PAMI(18), No. 12, December 1996, pp. 1163-1173.
IEEE DOI 9701
Morphology. Morphology based segmentation, find the regions based on analysis of the contours. See also Comments on Geodesic Saliency of Watershed Contours and Hierarchical Segmentation. BibRef

Najman, L., Schmitt, M.,
Watershed of a continuous function,
SP(38), No. 1, 1994, pp. 99-112. BibRef 9400

Cousty, J.[Jean], Couprie, M.[Michel], Najman, L.[Laurent], Bertrand, G.[Gilles],
Fusion Graphs: Merging Properties and Watersheds,
JMIV(30), No. 1, January 2008, pp. 87-104.
Springer DOI 0801
BibRef
Earlier: A1, A4, A2, A3:
Grayscale Watersheds on Perfect Fusion Graphs,
IWCIA06(60-73).
Springer DOI 0606
BibRef

Cousty, J.[Jean], Bertrand, G.[Gilles], Najman, L.[Laurent], Couprie, M.[Michel],
Watershed Cuts: Minimum Spanning Forests and the Drop of Water Principle,
PAMI(31), No. 8, August 2009, pp. 1362-1374.
IEEE DOI 0906
BibRef
Earlier:
On Watershed Cuts and Thinnings,
DGCI08(xx-yy).
Springer DOI 0804
Watersheds in edge-weighted graphs. See also On Topological Watersheds. BibRef

Cousty, J.[Jean], Bertrand, G.[Gilles], Najman, L.[Laurent], Couprie, M.[Michel],
Watershed Cuts: Thinnings, Shortest Path Forests, and Topological Watersheds,
PAMI(32), No. 5, May 2010, pp. 925-939.
IEEE DOI 1003
Thinning paradigm for 3 watershed cut strategies. Parallel, sequential, and link to flooding algorithms. BibRef

Cousty, J.[Jean], Bertrand, G.[Gilles], Couprie, M.[Michel], Najman, L.[Laurent],
Collapses and Watersheds in Pseudomanifolds of Arbitrary Dimension,
JMIV(50), No. 3, November 2014, pp. 261-285.
Springer DOI
WWW Link. 1410
BibRef
Earlier:
Collapses and Watersheds in Pseudomanifolds,
IWCIA09(397-410).
Springer DOI 0911
BibRef

Cousty, J.[Jean], Najman, L.[Laurent],
Morphological floodings and optimal cuts in hierarchies,
ICIP14(4462-4466)
IEEE DOI 1502
DH-HEMTs BibRef

Cousty, J.[Jean], Najman, L.[Laurent], Serra, J.[Jean],
Raising in watershed lattices,
ICIP08(2196-2199).
IEEE DOI 0810
BibRef

Cousty, J.[Jean], Bertrand, G.[Gilles],
Uniqueness of the Perfect Fusion Grid on Zd,
JMIV(34), No. 3, July 2009, pp. xx-yy.
Springer DOI 0906
BibRef

Shafarenko, L., Petrou, M., Kittler, J.V.,
Automatic Watershed Segmentation of Randomly Textured Color Images,
IP(6), No. 11, November 1997, pp. 1530-1544.
IEEE DOI 9710
Color. Texture. See also Histogram Based Segmentation in a Perceptually Uniform Color Space. BibRef

Moga, A.N.[Alina N.], Gabbouj, M.[Moncef],
Parallel Image Component Labeling with Watershed Transformation,
PAMI(19), No. 5, May 1997, pp. 441-450.
IEEE DOI 9705
Watershed. Delimit the extent of connected components locally (on each processor). Use pyramidal structure. Expand the regions out from minima until they colides with another. BibRef

Moga, A.N., Gabbouj, M.,
A Parallel Marker Based Watershed Transformation,
ICIP96(II: 137-140).
IEEE DOI BibRef 9600

Dorbin, B.P., Viero, T., Gabbouj, M.,
Fast Watershed Algorithms: Analysis and Extensions,
SPIE(2180), 1994, pp. 209-220. BibRef 9400

Moga, A.N.,
Parallel Watershed Algorithms for Image Segmentation,
Ph.D.Thesis, Tampere Univ. of Tech., Finland, February 1997. BibRef 9702

Moga, A.N., Cramariuc, B., Gabbouj, M.,
An Efficient Watershed Segmentation Algorithm Suitable for Parallel Implementation,
ICIP95(II: 101-104).
IEEE DOI 9510
BibRef

Lemarechal, C., Fjortoft, R., Marthon, P., Cubero-Castan, E.,
Comments on Geodesic Saliency of Watershed Contours and Hierarchical Segmentation,
PAMI(20), No. 7, July 1998, pp. 762-766.
IEEE DOI 9808
See also Geodesic Saliency of Watershed Contours and Hierarchical Segmentation. BibRef

Schmitt, M.,
Response to the Comment on Geodesic Saliency of Watershed Contours and Hierarchical Segmentation,
PAMI(20), No. 7, July 1998, pp. 764-766.
IEEE DOI 9808
BibRef

Wang, D.M.[De-Min],
A Multiscale Gradient Algorithm for Image Segmentation Using Watersheds,
PR(30), No. 12, December 1997, pp. 2043-2052.
WWW Link. 9805
For Video application: See also Unsupervised Video Segmentation Based on Watersheds and Temporal Tracking. BibRef

Gauch, J.M.[John M.],
Image Segmentation and Analysis via Multiscale Gradient Watershed Hierarchies,
IP(8), No. 1, January 1999, pp. 69-79.
IEEE DOI BibRef 9901

Haris, K., Efstratiadis, S.N., Maglaveras, N., Katsaggelos, A.K.,
Hybrid Image Segmentation Using Watersheds And Fast Region Merging,
IP(7), No. 12, December 1998, pp. 1684-1699.
IEEE DOI 9812
BibRef

Haris, K., Efstratiadis, S., Maglaveras, N.,
Hierarchical Image Segmentation Based on Contour Dynamics,
ICIP01(I: 54-57).
IEEE DOI 0108
BibRef

Haris, K., Efstratiadis, S.N., Maglaveras, N.,
Watershed-based image segmentation with fast region merging,
ICIP98(III: 338-342).
IEEE DOI 9810
BibRef

Pratikakis, I.E., Sahli, H., Cornelis, J.,
Low level image partitioning guided by the gradient watershed hierarchy,
SP(75), No. 2, 1 June 1999, pp. 173-195. BibRef 9906

Li, W.[Wei], Benie, G.B.[Goze B.], He, D.C.[Dong-Chen], Wang, S.R.[Sheng-Rui], Ziou, D.[Djemel], Gwyn, Q.H.J.[Q. Hugh J.],
Watershed-based hierarchical SAR image segmentation,
JRS(20), No. 17, November 1999, pp. 3377. BibRef 9911

Hansen, M.W., Higgins, W.E.,
Watershed-Based Maximum-Homogeneity Filtering,
IP(8), No. 7, July 1999, pp. 982-988.
IEEE DOI BibRef 9907
Earlier:
Image enhancement using watershed-based maximum homogeneity filtering,
ICIP95(I: 482-485).
IEEE DOI 9510
BibRef

Arcelli, C.[Carlo],
Topological changes in grey-tone digital pictures,
PR(32), No. 6, June 1999, pp. 1019-1023.
WWW Link. Reduce to a few regions. BibRef 9906

Bleau, A.[Andrè], Leon, L.J.[L. Joshua],
Watershed-Based Segmentation and Region Merging,
CVIU(77), No. 3, March 2000, pp. 317-370.
DOI Link 0004
BibRef

Bieniek, A.[Andreas], Moga, A.,
An efficient watershed algorithm based on connected components,
PR(33), No. 6, June 2000, pp. 907-916.
WWW Link. 0004
BibRef

Bieniek, A.[Andreas], Burkhardt, H.[Hans], Marschner, H.[Heiko], Noolle, M.[Michael], Schreiber, G.[Gerald],
A Parallel Watershed Algorithm,
SCIA97(xx-yy)
HTML Version. 9705
BibRef

Pitas, I., Cotsaces, C.I.,
Memory Efficient Propagation-Based Watershed and Influence Zone Algorithms for Large Images,
IP(9), No. 7, July 2000, pp. 1185-1199.
IEEE DOI 0006
BibRef

Kim, J.B.[Jong-Bae], Kim, H.J.[Hang-Joon],
Multiresolution-based watersheds for efficient image segmentation,
PRL(24), No. 1-3, January 2003, pp. 473-488.
Elsevier DOI 0211
BibRef

Kim, J.B.[Jong Bae], Kim, H.J.[Hang Joon],
A wavelet-based watershed image segmentation for VOP generation,
ICPR02(III: 505-508).
IEEE DOI 0211
BibRef

Nguyen, H.T.[Hieu Tat], Worring, M.[Marcel], van den Boomgaard, R.[Rein],
Watersnakes: Energy-Driven Watershed Segmentation,
PAMI(25), No. 3, March 2003, pp. 330-342.
IEEE DOI 0301
BibRef
And: TR12, Intelligent Sensory Information Systems Group, Univ. of Amsterdam, 2000.
PS File. Combine energy approach with watershed approach by including (as energy) distance to the watershed. Impose a priori conditions (smoothness). See also Tracking nonparameterized object contours in video. BibRef

Nguyen, H.T.[Hieu Tat], Ji, Q.A.[Qi-Ang],
Shape-Driven Three-Dimensional Watersnake Segmentation of Biological Membranes in Electron Tomography,
MedImg(27), No. 5, May 2008, pp. 616-628.
IEEE DOI 0711
BibRef
Earlier:
Improved watershed segmentation using water diffusion and local shape priors,
CVPR06(I: 985-992).
IEEE DOI 0606
BibRef

Malpica, N.[Norberto], Ortuño, J.E.[Juan E.], Santos, A.[Andrés],
A multichannel watershed-based algorithm for supervised texture segmentation,
PRL(24), No. 9-10, June 2003, pp. 1545-1554.
WWW Link. 0304
BibRef

Vanhamel, I., Pratikakis, I.E., Sahli, H.,
Multiscale gradient watersheds of color images,
IP(12), No. 6, June 2003, pp. 617-626.
IEEE DOI 0307
BibRef

Vanhamel, I., Pratikakis, I.E., Sahli, H.,
Multiscale Graph Theory Based Color Segmentation,
ICIP06(769-772).
IEEE DOI 0610
BibRef
Earlier: A1, A3, A2:
Nonlinear Multiscale Graph Theory based Segmentation of Color Images,
ICPR06(II: 407-411).
IEEE DOI 0609
BibRef
Earlier: A1, A2, A3:
Hierarchical segmentation using dynamics of multi-scale color gradient watersheds,
ScaleSpace01(xx-yy). 0106
BibRef

Pratikakis, I.E., Sahli, H., Cornelis, J.,
Hierarchical Segmentation Using Dynamics of Multiscale Gradient Watersheds,
SCIA99(Image Analysis). BibRef 9900
Earlier:
Hierarchy Determination of the Gradient Watershed Adjacent Groups,
SCIA97(xx-yy)
HTML Version. 9705
BibRef

Katartzis, A., Vanhamel, I., Sahli, H.,
A Hierarchical Markovian Model for Multiscale Region-Based Classification of Vector-Valued Images,
GeoRS(43), No. 3, March 2005, pp. 548-558.
IEEE Abstract. 0501
BibRef

Vanhamel, I., Katartzis, A., Sahli, H.,
Hierarchical segmentation via a diffusion scheme in color/texture feature space,
ICIP03(I: 969-972).
IEEE DOI 0312
BibRef

Hill, P.R., Canagarajah, C.N., Bull, D.R.,
Image segmentation using a texture gradient based watershed transform,
IP(12), No. 12, December 2003, pp. 1618-1633.
IEEE DOI 0402
BibRef

Nieniewski, M.,
Extraction of Diffuse Objects From Images by Means of Watershed and Region Merging: Example of Solar Images,
SMC-B(34), No. 1, February 2004, pp. 796-801.
IEEE Abstract. 0403
Developed for segmentation of solar images obtained from extreme-UV imaging telescope (EIT). BibRef

Grau, V., Mewes, A.U.J., Alcaniz, M., Kikinis, R., Warfield, S.K.,
Improved watershed transform for medical image segmentation using prior information,
MedImg(23), No. 4, April 2004, pp. 447-458.
IEEE Abstract. 0406
BibRef

Rambabu, C., Chakrabarti, I., Mahanta, A.,
Flooding-based watershed algorithm and its prototype hardware architecture,
VISP(151), No. 3, June 2004, pp. 224-234.
IEEE Abstract. 0409
BibRef

Tsai, Y.P.[Yu-Pao], Lai, C.C.[Chih-Chuan], Hung, Y.P.[Yi-Ping], Shih, Z.C.,
A Bayesian Approach to Video Object Segmentation via Merging 3-D Watershed Volumes,
CirSysVideo(15), No. 1, January 2005, pp. 175-180.
IEEE Abstract. 0501
BibRef
Earlier: A3, A1, A2 only: ICPR02(I: 496-499).
IEEE DOI 0211
BibRef

Makrogiannis, S., Economou, G., Fotopoulos, S., Bourbakis, N.G.,
Segmentation of Color Images Using Multiscale Clustering and Graph Theoretic Region Synthesis,
SMC-A(35), No. 2, March 2005, pp. 224-238.
IEEE Abstract. 0501
Combine region segmentation and clustering. Multi-scale clustering, then combine these regions into the final result. BibRef

Makrogiannis, S., Vanhamel, I., Sahli, H., Fotopoulos, S.,
Scale Space Segmentation of Color Images Using Watersheds and Fuzzy Region Merging,
ICIP01(I: 734-737).
IEEE DOI 0108
BibRef

Makrogiannis, S., Economou, G., Fotopoulos, S.,
Region oriented compression of color images using fuzzy inference and fast merging,
PR(35), No. 9, September 2002, pp. 1807-1820.
WWW Link. 0206
BibRef

Theoharatos, C., Pothos, V.K., Laskaris, N.A., Economou, G., Fotopoulos, S.,
Multivariate image similarity in the compressed domain using statistical graph matching,
PR(39), No. 10, October 2006, pp. 1892-1904.
WWW Link. 0606
Image similarity; Multivariate statistics; Graph matching; Minimal spanning tree (MST); Similarity measures; Discrete cosine transform (DCT); JPEG image compression; Image retrieval See also Combining self-organizing neural nets with multivariate statistics for efficient color image retrieval. See also local spectral distribution approach to face recognition, A. BibRef

Pothos, V.K.[Vasileios K.], Theoharatos, C.[Christos], Economou, G.[George], Ifantis, A.[Apostolos],
Texture retrieval based on a non-parametric measure for multivariate distributions,
CIVR07(502-509).
DOI Link 0707
BibRef

Makrogiannis, S., Schelkens, P., Fotopoulos, S., Cornelis, J.P.H.,
Region-oriented Compression of Color Images Using Fuzzy Inference and Shape Adaptive DCT,
ICIP01(III: 478-481).
IEEE DOI 0108
BibRef

Makrogiannis, S., Theoharatos, C., Economou, G., Fotopoulos, S.,
Color image segmentation using multiscale fuzzy C-means and graph theoretic merging,
ICIP03(I: 985-988).
IEEE DOI 0312
BibRef

Makrogiannis, S., Economou, G., Fotopoulos, S.,
A region dissimilarity relation that combines feature-space and spatial information for color image segmentation,
SMC-B(35), No. 1, February 2005, pp. 44-53.
IEEE Abstract. 0501
See also Combining self-organizing neural nets with multivariate statistics for efficient color image retrieval. BibRef

Patino, L.[Luis],
Fuzzy relations applied to minimize over segmentation in watershed algorithms,
PRL(26), No. 6, 1 May 2005, pp. 819-828.
WWW Link. 0501
BibRef

Jung, C.R.[Cláudio Rosito], Scharcanski, J.[Jacob],
Robust watershed segmentation using wavelets,
IVC(23), No. 7, 1 July 2005, pp. 661-669.
WWW Link. 0506
BibRef

Jung, C.R.[Cláudio Rosito],
Combining wavelets and watersheds for robust multiscale image segmentation,
IVC(25), No. 1, January 2007, pp. 24-33.
WWW Link. 0611
Segmentation; Watersheds; Wavelets; Multiresolution; Denoising; Region merging BibRef

Jung, C.R.[Cláudio Rosito],
Unsupervised multiscale segmentation of color images,
PRL(28), No. 4, 1 March 2007, pp. 523-533.
WWW Link. 0701
Watersheds; Wavelets; Multiresolution; Color images; Region merging BibRef

Zhao, C.G.[Chen Guang], Zhuang, T.G.[Tian Ge],
A hybrid boundary detection algorithm based on watershed and snake,
PRL(26), No. 9, 1 July 2005, pp. 1256-1265.
WWW Link. 0506
BibRef

Sun, H.[Han], Yang, J.Y.[Jing-Yu], Ren, M.[Mingwu],
A fast watershed algorithm based on chain code and its application in image segmentation,
PRL(26), No. 9, 1 July 2005, pp. 1266-1274.
WWW Link. 0506
BibRef

Beare, R.,
A Locally Constrained Watershed Transform,
PAMI(28), No. 7, July 2006, pp. 1063-1074.
IEEE DOI 0606
Introduce border constraints by modifying the path definition of the watershed transform. BibRef

Osma-Ruiz, V.[Víctor], Godino-Llorente, J.I.[Juan I.], Sáenz-Lechón, N.[Nicolás], Gómez-Vilda, P.[Pedro],
An improved watershed algorithm based on efficient computation of shortest paths,
PR(40), No. 3, March 2007, pp. 1078-1090.
WWW Link. 0611
Watershed; Image segmentation; Arrowing BibRef

de Carvalho, M.A.G.[Marco Antonio Garcia], de Alencar Lotufo, R.[Roberto], Couprie, M.[Michel],
Morphological segmentation of yeast by image analysis,
IVC(25), No. 1, January 2007, pp. 34-39.
WWW Link. 0611
Yeast; Watershed; Scale-space; Image analysis BibRef

Frucci, M.[Maria], Ramella, G.[Giuliana], Sanniti di Baja, G.[Gabriella],
Using resolution pyramids for watershed image segmentation,
IVC(25), No. 6, 1 June 2007, pp. 1021-1031.
WWW Link. 0704
Segmentation; Watershed transformation; Resolution pyramid See also Shape and topology preserving multi-valued image pyramids for multi-resolution skeletonization. BibRef

Frucci, M.[Maria], Perner, P.[Petra], Sanniti di Baja, G.[Gabriella],
Watershed Segmentation Via Case-Based Reasoning,
BVAI07(244-253).
Springer DOI 0710
BibRef

Ramella, G.[Giuliana], Sanniti di Baja, G.[Gabriella],
Detecting Foreground Components in Grey Level Images for Shift Invariant and Topology Preserving Pyramids,
ICIAR04(I: 57-64).
Springer DOI 0409
BibRef

Frucci, M.[Maria], di Baja, G.S.[Gabriella Sanniti],
A New Algorithm for Image Segmentation via Watershed Transformation,
CIAP11(II: 168-177).
Springer DOI 1109
BibRef

Audigier, R.[Romaric], de Alencar Lotufo, R.[Roberto],
Uniquely-Determined Thinning of the Tie-Zone Watershed Based on Label Frequency,
JMIV(27), No. 2, February 2007, pp. 157-173.
Springer DOI 0704
BibRef

Levner, I.[Ilya], Zhang, H.[Hong],
Classification-Driven Watershed Segmentation,
IP(16), No. 5, May 2007, pp. 1437-1445.
IEEE DOI 0704
BibRef

Levner, I.[Ilya], Greiner, R.[Russell], Zhang, H.[Hong],
Supervised image segmentation via ground truth decomposition,
ICIP08(737-740).
IEEE DOI 0810
BibRef

Trieu, D.B.K.[Dang Ba Khac], Maruyama, T.[Tsutomu],
Real-time image segmentation based on a parallel and pipelined watershed algorithm,
RealTimeIP(2), No. 4, December 2007, pp. 319-329.
Springer DOI 0712
BibRef

Trieu, D.B.K.[Dang Ba Khac], Maruyama, T.[Tsutomu],
Real-time color image segmentation based on mean shift algorithm using an FPGA,
RealTimeIP(10), No. 2, June 2015, pp. 345-356.
WWW Link. 1506
BibRef

Sofou, A., Maragos, P.[Petros],
Generalized Flooding and Multicue PDE-Based Image Segmentation,
IP(17), No. 3, March 2008, pp. 364-376.
IEEE DOI 0802
BibRef
Earlier:
PDE-based modeling of image segmentation using volumic flooding,
ICIP03(II: 431-434).
IEEE DOI 0312
BibRef

Meyer, F.[Fernand], Maragos, P.[Petros],
Multiscale Morphological Segmentations based on Watershed, Flooding, and Eikonal PDE,
ScaleSpace99(351-362). BibRef 9900

Meyer, F.[Fernand],
Watershed Segmentation with a Controlled Precision,
ISMM17(83-94).
Springer DOI 1706
BibRef
Earlier:
The Waterfall Hierarchy on Weighted Graphs,
ISMM15(325-336).
Springer DOI 1506
BibRef
And:
Flooding Edge on Node Weighted Graphs,
ISMM13(341-352).
Springer DOI 1305
BibRef

Meyer, F.[Fernand],
A Watershed Algorithm Progressively Unveiling Its Optimality,
ISMM15(717-728).
Springer DOI 1506
BibRef

Meyer, F.[Fernand], Lerallut, R.[Romain],
Morphological Operators for Flooding, Leveling and Filtering Images Using Graphs,
GbRPR07(158-167).
Springer DOI 0706
BibRef

Peter, Z., Bousson, V., Bergot, C., Peyrin, F.,
A constrained region growing approach based on watershed for the segmentation of low contrast structures in bone micro-CT images,
PR(41), No. 7, July 2008, pp. 2358-2368.
WWW Link. 0804
Image segmentation; Anisotropic diffusion; Bones; X-ray tomography BibRef

Dagher, I.[Issam], El Tom, K.[Kamal],
WaterBalloons: A hybrid watershed Balloon Snake segmentation,
IVC(26), No. 7, 2 July 2008, pp. 905-912.
WWW Link. 0804
Watershed; Active contour model; Snake balloon; Segmentation; WaterBalloons BibRef

Eom, S.[Seongeun], Shin, V.[Vladimir], Ahn, B.[Byungha],
Cellular Watersheds: A Parallel Implementation of the Watershed Transform on the CNN Universal Machine,
IEICE(E90-D), No. 4, April 2007, pp. 791-794.
DOI Link 0704
BibRef

Rao, A.R.[A. Ramachandra], Srinivas, V.V.,
Regionalization of Watersheds: An Approach Based on Cluster Analysis,
Springer2008, ISBN: 978-1-4020-6851-5
WWW Link. Buy this book: Regionalization of Watersheds: An Approach Based on Cluster Analysis (Water Science and Technology Library) (Water Science and Technology Library) BibRef 0800

Hamarneh, G.[Ghassan], Li, X.X.[Xiao-Xing],
Watershed segmentation using prior shape and appearance knowledge,
IVC(27), No. 1-2, January 2009, pp. 59-68.
WWW Link. 0811
BibRef
Earlier: A2, A1:
Modeling Prior Shape and Appearance Knowledge in Watershed Segmentation,
CRV05(27-33).
IEEE DOI 0505
Watershed transformation; Prior shape knowledge; Segmentation; k-Means clustering Medical applications. BibRef

Rittner, L.[Leticia], Flores, F.C.[Franklin César], de Alencar Lotufo, R.[Roberto],
A tensorial framework for color images,
PRL(31), No. 4, 1 March 2010, pp. 277-296.
Elsevier DOI 1002
Color image; Gradient; Tensor; Mathematical morphology; Watershed transform; Segmentation BibRef

de Smet, P.[Patrick],
Optimized high speed pixel sorting and its application in watershed based image segmentation,
PR(43), No. 7, July 2010, pp. 2359-2366.
Elsevier DOI 1003
Pixel sorting; Watershed; Optimization BibRef

Tarabalka, Y., Chanussot, J., Benediktsson, J.A.,
Segmentation and classification of hyperspectral images using watershed transformation,
PR(43), No. 7, July 2010, pp. 2367-2379.
Elsevier DOI 1003
Hyperspectral images; Mathematical morphology; Watershed; Segmentation; Classification See also Multiple Spectral-Spatial Classification Approach for Hyperspectral Data. BibRef

Tarabalka, Y., Chanussot, J., Benediktsson, J.A.,
Segmentation and Classification of Hyperspectral Images Using Minimum Spanning Forest Grown From Automatically Selected Markers,
SMC-B(40), No. 5, October 2010, pp. 1267-1279.
IEEE DOI 1003
BibRef

Bernard, K., Tarabalka, Y., Angulo, J., Chanussot, J., Benediktsson, J.A.,
Spectral-Spatial Classification of Hyperspectral Data Based on a Stochastic Minimum Spanning Forest Approach,
IP(21), No. 4, April 2012, pp. 2008-2021.
IEEE DOI 1204
BibRef
Earlier:
A Stochastic Minimum Spanning Forest approach for spectral-spatial classification of hyperspectral images,
ICIP11(1265-1268).
IEEE DOI 1201
BibRef

Ghamisi, P., Couceiro, M.S., Martins, F.M.L., Benediktsson, J.A.,
Multilevel Image Segmentation Based on Fractional-Order Darwinian Particle Swarm Optimization,
GeoRS(52), No. 5, May 2014, pp. 2382-2394.
IEEE DOI 1403
Classification BibRef

Audigier, R.[Romaric], de Alencar Lotufo, R.[Roberto],
Relationships between some watershed definitions and their tie-zone transforms,
IVC(28), No. 10, October 2010, pp. 1472-1482.
Elsevier DOI 1007
BibRef

Flores, F.C.[Franklin Cesar], de Alencar Lotufo, R.[Roberto],
Watershed from propagated markers: An interactive method to morphological object segmentation in image sequences,
IVC(28), No. 11, November 2010, pp. 1491-1514.
Elsevier DOI 1008
Morphological segmentation; Image sequences; Marker propagation; Motion estimation; Watershed from markers; Interactive segmentation BibRef

Li, D., Zhang, G.F.[Gui-Feng], Wu, Z.C.[Zhao-Cong], Yi, L.[Lina],
An Edge Embedded Marker-Based Watershed Algorithm for High Spatial Resolution Remote Sensing Image Segmentation,
IP(19), No. 10, October 2010, pp. 2781-2787.
IEEE DOI 1003
BibRef
Earlier: A2, A3, A4, Only:
Marker-based watershed segmentation embedded with edge information,
IASP10(375-380).
IEEE DOI 1004
BibRef

Yi, L.[Lina], Zhang, G.F.[Gui-Feng], Wu, Z.C.[Zhao-Cong],
A Scale-Synthesis Method for High Spatial Resolution Remote Sensing Image Segmentation,
GeoRS(50), No. 10, October 2012, pp. 4062-4070.
IEEE DOI 1210
BibRef

Derivaux, S.[Sébastien], Forestier, G.[Germain], Wemmert, C.[Cédric], Lefevre, S.,
Supervised image segmentation using watershed transform, fuzzy classification and evolutionary computation,
PRL(31), No. 15, 1 November 2010, pp. 2364-2374.
Elsevier DOI 1003
Supervised image segmentation; Watershed transform; Fuzzy classification; Genetic algorithm BibRef

Li, F.[Fang], Ng, M.K.[Michael K.], Zeng, T.Y.[Tie Yong], Shen, C.L.[Chun-Li],
A Multiphase Image Segmentation Method Based on Fuzzy Region Competition,
SIIMS(3), No. 3, 2010, pp. 277-299.
DOI Link multiphase; image segmentation; region competition; fuzzy membership function; alternative minimization BibRef 1000

Cai, X.H.[Xiao-Hao], Chan, R.[Raymond], Zeng, T.Y.[Tie-Yong],
A Two-Stage Image Segmentation Method Using a Convex Variant of the Mumford-Shah Model and Thresholding,
SIIMS(6), No. 1, 2013, pp. 368-390.
DOI Link 1304
See also Optimal Approximations by Piecewise Smooth Functions and Variational Problems. BibRef

Cai, X.H.[Xiao-Hao],
Variational image segmentation model coupled with image restoration achievements,
PR(48), No. 6, 2015, pp. 2029-2042.
Elsevier DOI 1503
Image segmentation BibRef

Duan, Y.P.[Yu-Ping], Chang, H.B.[Hui-Bin], Huang, W.M.[Wei-Min], Zhou, J.Y.[Jia-Yin], Lu, Z.K.[Zhong-Kang], Wu, C.L.[Chun-Lin],
The L_0 Regularized Mumford-Shah Model for Bias Correction and Segmentation of Medical Images,
IP(24), No. 11, November 2015, pp. 3927-3938.
IEEE DOI 1509
BibRef
Earlier: A1, A2, A3, A4, Only:
Simultaneous bias correction and image segmentation via L0 regularized Mumford-Shah model,
ICIP14(6-40)
IEEE DOI 1502
image segmentation. Biomedical imaging See also Optimal Approximations by Piecewise Smooth Functions and Variational Problems. BibRef

Duan, Y.P.[Yu-Ping], Huang, W.M.[Wei-Min], Zhou, J.Y.[Jia-Yin], Chang, H.B.[Hui-Bin], Zeng, T.Y.[Tie-Yong],
A Two-Stage Image Segmentation Method Using Euler's Elastica Regularized Mumford-Shah Model,
ICPR14(118-123)
IEEE DOI 1412
Approximation methods BibRef

Suphalakshmi, A., Narendran, S., Anandhakumar, P.,
An improved fast watershed algorithm for image segmentation,
IJCVR(1), No. 3, 2010, pp. 251-260.
DOI Link 1102
BibRef

Najman, L.[Laurent],
On the Equivalence Between Hierarchical Segmentations and Ultrametric Watersheds,
JMIV(40), No. 3, July 2011, pp. 231-247.
WWW Link. 1103
BibRef
Earlier:
Ultrametric Watersheds,
ISMM09(181-192).
Springer DOI 0908
BibRef

Couprie, C.[Camille], Grady, L.[Leo], Najman, L.[Laurent], Talbot, H.[Hugues],
Power Watershed: A Unifying Graph-Based Optimization Framework,
PAMI(33), No. 7, July 2011, pp. 1384-1399.
IEEE DOI 1106
BibRef
Earlier:
Anisotropic diffusion using power watersheds,
ICIP10(4153-4156).
IEEE DOI 1009
BibRef
Earlier:
Power watersheds: A new image segmentation framework extending graph cuts, random walker and optimal spanning forest,
ICCV09(731-738).
IEEE DOI 0909
Extend graph-based techniques includes graph cuts, random walk, shortest path. BibRef

Couprie, C.[Camille], Grady, L.[Leo], Talbot, H.[Hugues], Najman, L.[Laurent],
Combinatorial Continuous Maximum Flow,
SIIMS(4), No. 3, 2011, pp. 905-930.
WWW Link. 1110
BibRef

Corcoran, P.[Padraig], Winstanley, A.[Adam], Mooney, P.[Peter],
Complementary texture and intensity gradient estimation and fusion for watershed segmentation,
MVA(22), No. 6, November 2011, pp. 1027-1045.
WWW Link. 1110
BibRef

Bernander, K.B.[Karl B.], Gustavsson, K.[Kenneth], Selig, B.[Bettina], Sintorn, I.M.[Ida-Maria], Hendriks, C.L.L.[Cris L. Luengo],
Improving the stochastic watershed,
PRL(34), No. 9, July 2013, pp. 993-1000.
Elsevier DOI 1305
Mathematical morphology; Image segmentation; Random process; Stochastic watershed; Seeded watershed; Uniform grid BibRef

Selig, B.[Bettina], Malmberg, F.[Filip], Hendriks, C.L.L.[Cris L. Luengo],
Fast Evaluation of the Robust Stochastic Watershed,
ISMM15(705-716).
Springer DOI 1506
BibRef
Earlier: A2, A1, A3:
Exact Evaluation of Stochastic Watersheds: From Trees to General Graphs,
DGCI14(309-319).
Springer DOI 1410
BibRef

Singh, P.P.[Pankaj Pratap], Garg, R.D.,
A Hybrid Approach for Information Extraction from High Resolution Satellite Imagery,
IJIG(13), No. 2, April 2013, pp. 1340007.
DOI Link 1308
marker-controlled watershed transforms and a nonlinear derivative method. BibRef

Golodetz, S.M., Nicholls, C., Voiculescu, I.D., Cameron, S.A.,
Two tree-based methods for the waterfall,
PR(47), No. 10, 2014, pp. 3276-3292.
Elsevier DOI 1406
Image segmentation BibRef

Meyer, F.[Fernand],
Watersheds on weighted graphs,
PRL(47), No. 1, 2014, pp. 72-79.
Elsevier DOI 1408
Watershed BibRef

Brun, L.[Luc], Vautrot, P.[Philippe], Meyer, F.[Fernand],
Hierarchical Watersheds with Inter-pixel Boundaries,
ICIAR04(I: 840-847).
Springer DOI 0409
BibRef

Malmberg, F.[Filip], Luengo Hendriks, C.L.[Cris L.],
An efficient algorithm for exact evaluation of stochastic watersheds,
PRL(47), No. 1, 2014, pp. 80-84.
Elsevier DOI 1408
Mathematical morphology BibRef

Baldacci, F.[Fabien], Braquelaire, A.[Achille],
Oriented boundary graph: An efficient structuring model for segmentation of 3D images,
CVIU(143), No. 1, 2016, pp. 92-103.
Elsevier DOI 1601
3D segmentation See also Oriented Boundary Graph: A Framework to Design and Implement 3D Segmentation Algorithms. BibRef

Baldacci, F.[Fabien],
An Unbiased and Intervoxel Watershed Algorithm for 3D Image Segmentation,
ICIAR12(I: 330-337).
Springer DOI 1206
See also Oriented Boundary Graph: A Framework to Design and Implement 3D Segmentation Algorithms. BibRef

Hodneland, E., Tai, X.C., Kalisch, H.,
PDE Based Algorithms for Smooth Watersheds,
MedImg(35), No. 4, April 2016, pp. 957-966.
IEEE DOI 1604
biomedical optical imaging BibRef

Michaelsen, E.[Eckart],
Self-organizing maps and Gestalt organization as components of an advanced system for remotely sensed data: An example with thermal hyper-spectra,
PRL(83, Part 2), No. 1, 2016, pp. 169-177.
Elsevier DOI 1609
Hyperspectral data BibRef

González-Betancourt, A.[Aniel], Rodríguez-Ribalta, P.[Patricia], Meneses-Marcel, A.[Alfredo], Sifontes-Rodríguez, S.[Sergio], Lorenzo-Ginori, J.V.[Juan Valentín], Orozco-Morales, R.[Rubén],
Automated marker identification using the Radon transform for watershed segmentation,
IET-IPR(11), No. 3, March 2017, pp. 183-189.
DOI Link 1703
BibRef


Maia, D.S.[Deise Santana], de Albuquerque Araujo, A.[Arnaldo], Cousty, J.[Jean], Najman, L.[Laurent], Perret, B.[Benjamin], Talbot, H.[Hugues],
Evaluation of Combinations of Watershed Hierarchies,
ISMM17(133-145).
Springer DOI 1706
BibRef

Figliuzzi, B.[Bruno], Chang, K.[Kaiwen], Faessel, M.[Matthieu],
Hierarchical Segmentation Based Upon Multi-resolution Approximations and the Watershed Transform,
ISMM17(185-195).
Springer DOI 1706
BibRef

Dias, F.[Fabio], Mansour, M.R.[Moussa R.], Valdivia, P.[Paola], Cousty, J.[Jean], Najman, L.[Laurent],
Watersheds on Hypergraphs for Data Clustering,
ISMM17(211-221).
Springer DOI 1706
BibRef

Chabardès, T., Dokládal, P., Faessel, M., Bilodeau, M.,
A parallel, O(N) algorithm for unbiased, thin watershed,
ICIP16(2569-2573)
IEEE DOI 1610
Computer architecture BibRef

Chahine, C., El Berbari, R., Lagorre, C., Nakib, A., Petit, E.,
Evidence theory for image segmentation using information from stochastic Watershed and Hessian filtering,
WSSIP15(141-144)
IEEE DOI 1603
filtering theory BibRef

Zhang, C.[Chao], Makrogiannis, S.[Sokratis],
Finding the N-cuts of Watershed Partitions for Image Segmentation,
ISVC15(I: 221-230).
Springer DOI 1601
BibRef

Hu, Z.W.[Zhong-Wen], Zou, Q.[Qin], Li, Q.Q.[Qing-Quan],
Watershed superpixel,
ICIP15(349-353)
IEEE DOI 1512
image segmentation; spatial constraint; superpixel; watershed BibRef

Machairas, V.[Vaïa], Decencière, E.[Etienne], Walter, T.[Thomas],
Spatial Repulsion Between Markers Improves Watershed Performance,
ISMM15(194-202).
Springer DOI 1506
BibRef

Porter, R.[Reid], Oyen, D.[Diane], Zimmer, B.G.[Beate G.],
Learning Watershed Cuts Energy Functions,
ISMM15(497-508).
Springer DOI 1506
BibRef

Lopez-Mir, F., Naranjo, V., Morales, S., Angulo, J.,
Probability density function of object contours using regional regularized stochastic watershed,
ICIP14(4762-4766)
IEEE DOI 1502
Image edge detection BibRef

Pinto, T.W., de Carvalho, M.A.G., Pedronette, D.C.G., Martins, P.S.,
Image segmentation through combined methods: Watershed transform, unsupervised distance learning and Normalized Cut,
Southwest14(153-156)
IEEE DOI 1406
graph theory BibRef

Masi, G.[Giuseppe], Scarpa, G.[Giuseppe],
A Watershed-Based Segmentation Technique for Multiresolution Data,
CIAP13(I:241-250).
Springer DOI 1311
BibRef

Yang, D.[Di], Gould, S.[Stephen], Hutter, M.[Marcus],
A Noise Tolerant Watershed Transformation with Viscous Force for Seeded Image Segmentation,
ACCV12(I:775-789).
Springer DOI 1304
BibRef

Attig, A.[Anja], Perner, P.[Petra],
Incremental Learning of the Model for Watershed-Based Image Segmentation,
IWCIA12(209-222).
Springer DOI 1211
BibRef

Wang, D.D.[Da-Dong], Vallotton, P.[Pascal],
Improved marker-controlled watershed segmentation with local boundary priors,
IVCNZ10(1-6).
IEEE DOI 1203
BibRef

Shadkami, P.[Pasha], Bonnier, N.[Nicolas],
Watershed Based Document Image Analysis,
ACIVS10(I: 114-124).
Springer DOI 1012
BibRef

Swiercz, M.[Michal], Iwanowski, M.[Marcin],
Fast, Parallel Watershed Algorithm Based on Path Tracing,
ICCVG10(II: 317-324).
Springer DOI 1009
BibRef

Attia, D., Meurie, C.[Cyril], Ruichek, Y.[Yassine],
Eigen Combination of Colour and Texture Informations for Image Segmentation,
ICISP12(415-423).
Springer DOI 1208
BibRef

Meurie, C.[Cyril], Cohen, A.[Andrea], Ruichek, Y.[Yassine],
An Efficient Combination of Texture and Color Information for Watershed Segmentation,
ICISP10(147-156).
Springer DOI 1006
BibRef

Chen, L.[Li], Jiang, M.[Min], Chen, J.X.[Jian-Xun],
Image segmentation using iterative watersheding plus ridge detection,
ICIP09(4033-4036).
IEEE DOI 0911
BibRef

Chen, D.F.[Dong-Fang], Xu, T.[Tao],
Watershed Segmentation Using Curvelet and Morphological Filtering,
CISP09(1-5).
IEEE DOI 0910
BibRef

Hanselmann, M.[Michael], Köthe, U.[Ullrich], Renard, B.Y.[Bernhard Y.], Kirchner, M.[Marc], Heeren, R.M.A.[Ron M. A.], Hamprecht, F.A.[Fred A.],
Multivariate Watershed Segmentation of Compositional Data,
DGCI09(180-192).
Springer DOI 0909
BibRef

Meine, H.[Hans], Stelldinger, P.[Peer], Köthe, U.[Ullrich],
Pixel Approximation Errors in Common Watershed Algorithms,
DGCI09(193-202).
Springer DOI 0909
BibRef

Monteiro, F.C.[Fernando C.], Campilho, A.[Aurelio],
Watershed framework to region-based image segmentation,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Kauffmann, C.[Claude], Piche, N.[Nicolas],
Cellular automaton for ultra-fast watershed transform on GPU,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Chef d'Hotel, C.[Christophe], Sebbane, A.[Alexis],
Random Walk and Front Propagation on Watershed Adjacency Graphs for Multilabel Image Segmentation,
ICV07(1-7).
IEEE DOI 0710
BibRef

Delest, S.[Sebastien], Bone, R.[Romuald], Cardot, H.[Hubert],
Automatically Computed Markers for the 3D Watershed Segmentation,
ICIP07(VI: 533-536).
IEEE DOI 0709
BibRef

Corcoran, P.[Padraig], Winstanley, A.[Adam],
Watershed Segmentation Using a Multiscale Ramp Edge Merging Strategy,
IMVIP07(158-168).
IEEE DOI 0709
BibRef

Mory, B.[Benoit], Ardon, R.[Roberto], Thiran, J.P.[Jean-Philippe],
Variational Segmentation using Fuzzy Region Competition and Local Non-Parametric Probability Density Functions,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Mory, B.[Benoit], Ardon, R.[Roberto],
Fuzzy Region Competition: A Convex Two-Phase Segmentation Framework,
SSVM07(214-226).
Springer DOI 0705
BibRef

Lefèvre, S.[Sébastien],
Knowledge from Markers in Watershed Segmentation,
CAIP07(579-586).
Springer DOI 0708
BibRef

de Bock, J.[Johan], Philips, W.[Wilfried],
Line Segment Based Watershed Segmentation,
MIRAGE07(579-586).
Springer DOI 0703
BibRef

Huang, W.L.[Wen-Long], Jiao, L.C.[Li-Cheng],
Unsupervised Texture Segmentation Based on Watershed and a Novel Artificial Immune Antibody Competitive Network,
PSIVT06(495-503).
Springer DOI 0612
BibRef

Pina, P.[Pedro], Saraiva, J.[José], Bandeira, L.[Lourenço], Barata, T.[Teresa],
Identification of Martian Polygonal Patterns Using the Dynamics of Watershed Contours,
ICIAR06(II: 691-699).
Springer DOI 0610
BibRef

Macenko, M.[Marc], Celenk, M.[Mehmet], Ma, L.M.[Li-Min],
Lesion Detection Using Morphological Watershed Segmentation and Modelbased Inverse Filtering,
ICPR06(IV: 679-682).
IEEE DOI 0609
BibRef

Climent, J.[Joan], Sanfeliu, A.[Alberto],
Visually Significant Dynamics for Watershed Segmentation,
ICPR06(II: 341-344).
IEEE DOI 0609
BibRef

Pinidiyaarachchi, A.[Amalka], Wählby, C.[Carolina],
Seeded Watersheds for Combined Segmentation and Tracking of Cells,
CIAP05(336-343).
Springer DOI 0509
BibRef

Holting, P.[Per], Wählby, C.[Carolina],
Easy-to-Use Object Selection by Color Space Projections and Watershed Segmentation,
CIAP05(269-276).
Springer DOI 0509
BibRef

Guerfi, S., Gambotto, J.P., Lelandais, S.,
Implementation of the watershed method in the HSI color space for the face extraction,
AVSBS05(282-286).
IEEE DOI 0602
BibRef

Tek, H.[Huseyin], Akova, F.[Ferit], Ayvacy, A.[Alper],
Region Competition via Local Watershed Operators,
CVPR05(II: 361-368).
IEEE DOI 0507
BibRef

Huang, X.Q.[Xiao-Qiang], Fisher, M.[Mark], Zhu, Y.O.[Yan-Ong],
From Min Tree to Watershed Lake Tree: Theory and Implementation,
ICIAR04(I: 848-857).
Springer DOI 0409
BibRef

Huang, X.Q.[Xiao-Qiang], Fisher, M.[Mark],
From Min Tree to Watershed Lake Tree: Evaluation,
ICIAR04(I: 858-865).
Springer DOI 0409
BibRef

Gies, V., Bernard, T.M.,
Statistical solution to watershed over-segmentation,
ICIP04(III: 1863-1866).
IEEE DOI 0505
BibRef

Hu, Y.[Yi], Nagao, T.,
A matching method based on marker-controlled watershed segmentation,
ICIP04(I: 283-286).
IEEE DOI 0505
BibRef

Chen, Q.X.[Qiu-Xiao], Zhou, C.H.[Cheng-Hu], Luo, J.C.[Jian-Cheng], Ming, D.P.[Dong-Ping],
Fast Segmentation of High-Resolution Satellite Images Using Watershed Transform Combined with an Efficient Region Merging Approach,
IWCIA04(621-630).
Springer DOI 0505
BibRef

Park, C.B.[Chang-Beom], Lee, K.W.[Kwang-Woo], Lee, S.W.[Seong-Whan],
Automatic microarray image segmentation based on watershed transformation,
ICPR04(III: 786-789).
IEEE DOI 0409
BibRef

Kazanov, M.,
A new color image segmentation algorithm based on watershed transformation,
ICPR04(II: 590-593).
IEEE DOI 0409
BibRef

Soares, F., Muge, F.,
Watershed lines suppression by waterfall marker improvement and lineneighbourhood analysis,
ICPR04(I: 604-607).
IEEE DOI 0409
BibRef

Kazanov, M.,
Modification of watershed transformation for images, containing small objects,
ICPR04(I: 612-615).
IEEE DOI 0409
BibRef

Scheunders, P., Sijbers, J.,
Multiscale watershed segmentation of multivalued images,
ICPR02(III: 855-858).
IEEE DOI 0211
See also orthogonal wavelet representation of multivalued images, An. BibRef

Scheunders, P.,
Multivalued image segmentation based on first fundamental form,
CIAP01(185-190).
WWW Link. 0210
Combine edges and color info. Watershed. BibRef

Eom, S.[Sungeun], Chang, S.[Seokcheol], Ahn, B.[Byungha],
Watershed-based region merging using conflicting regions,
ICIP02(II: 781-784).
IEEE DOI 0210
BibRef

Vanderstockt, Y., Whyte, R.N.,
Watershed Transfromation: Reducing the Over-Segmentation Problem by Applying a Noice Reducer and a Region Merger,
WSCG02(POS-57).
HTML Version. 0209
BibRef

Mortensen, E.N.[Eric N.], Jia, J.[Jin],
Real-Time Semi-Automatic Segmentation Using a Bayesian Network,
CVPR06(I: 1007-1014).
IEEE DOI 0606
BibRef
Earlier:
A Bayesian Network Framework for Real-Time Object Selection,
PercOrg04(44).
IEEE DOI 0502
BibRef

Blaffert, T., Dippel, S., Stahl, M., Wiemker, R.,
The Laplace Integral for a Watershed Segmentation,
ICIP00(Vol III: 444-447).
IEEE DOI 0008
BibRef

Yuan, Y.[Yu], Barner, K.,
Color Image Segmentation Using Watersheds and Joint Homogeneity-Edge Integrity Region Merging Criteria,
ICIP06(1117-1120).
IEEE DOI 0610
BibRef

Hernandez, S., Barner, K.,
Joint Region Merging Criteria for Watershed-based Image Segmentation,
ICIP00(Vol II: 108-111).
IEEE DOI 0008
BibRef

Sporring, J.[Jon], Olsen, O.F.[Ole Fogh],
Segmenting by Compression using Linear Scale-Space and Watersheds,
ScaleSpace99(513-518). BibRef 9900

Shiji, A.[Ayako], Hamada, N.[Nozomu],
Color Image Segmentation Method using Watershed Algorithm and Contour Information,
ICIP99(IV:305-309).
IEEE DOI BibRef 9900

Patras, I., Hendriks, E.A., Lagendijk, R.L.,
An iterative motion estimation-segmentation method using watershed segments,
ICIP98(II: 642-646).
IEEE DOI 9810
BibRef

Olsen, O.F.[Ole Fogh], Nielsen, M.[Mads],
Multi-scale gradient magnitude watershed segmentation,
CIAP97(I: 6-13).
Springer DOI 9709
BibRef

Hagyard, D., Razaz, M., Atkin, P.,
Analysis of watershed algorithms for greyscale images,
ICIP96(III: 41-44).
IEEE DOI 9610
BibRef

Geraud, T., Mangin, J.F., Bloch, I., Maitre, H.,
Segmenting internal structures in 3D MR images of the brain by Markovian relaxation on a watershed based adjacency graph,
ICIP95(III: 548-551).
IEEE DOI 9510
BibRef

Ancin, H., Dufresne, T.E., Ridder, G.M., Turner, J.N., Roysam, B.,
An improved watershed algorithm for counting objects in noisy, anisotropic 3-D biological images,
ICIP95(III: 172-175).
IEEE DOI 9510
BibRef

Meijster, A., Roerdink, J.B.T.M.,
A proposal for the implementation of a parallel watershed algorithm,
CAIP95(790-795).
Springer DOI 9509
BibRef

Saarinen, K.,
Color image segmentation by a watershed algorithm and region adjacency graph processing,
ICIP94(III: 1021-1025).
IEEE DOI 9411
BibRef

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Segmentation by Split and Merge Techniques, Hierarchical .


Last update:Nov 11, 2017 at 13:31:57