8.7.1.2.3 Active Contours and Snakes, Segmentations, Flow, Gradient Flow

Chapter Contents (Back)
Deformable Curves. Snakes. Active Contours. Segmentation.

Tsai, A.[Andy], Yezzi, Jr., A.J.[Anthony J.], Willsky, A.S.[Alan S.],
Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification,
IP(10), No. 8, August 2001, pp. 1169-1186.
IEEE DOI 0108
See also Optimal Approximations by Piecewise Smooth Functions and Variational Problems. BibRef

Yezzi, Jr., A.J.[Anthony J.], Tsai, A.[Andy], Willsky, A.S.[Alan S.],
A Fully Global Approach to Image Segmentation via Coupled Curve Evolution Equations,
JVCIR(13), No. 1/2, March/June 2002, pp. 195-216.
DOI Link 0204
BibRef
Earlier: A2, A1, A3:
A Curve Evolution Approach to Smoothing and Segmentation Using the Mumford-Shah Functional,
CVPR00(I: 119-124).
IEEE DOI 0005
BibRef
Earlier:
Binary and ternary flows for image segmentation,
ICIP99(II:1-5).
IEEE DOI BibRef
And:
A Statistical Approach to Snakes for Bimodal and Trimodal Imagery,
ICCV99(898-903).
IEEE DOI See also Optimal Approximations by Piecewise Smooth Functions and Variational Problems. BibRef

Tsai, A.[Andy], Yezzi, Jr., A.J.[Anthony J.], Wells, III, W.M.[William M.], Tempany, C.[Clare], Tucker, D.[Dewey], Fan, A.[Ayres], Grimson, W.E.L.[W. Eric L.], Willsky, A.S.[Alan S.],
Model-Based Curve Evolution Technique for Image Segmentation,
CVPR01(I:463-468).
IEEE DOI 0110
Award, CVPR, Student, HM. For known objects. BibRef

Kim, J.[Junno], Tsai, A., Cetin, M., Willsky, A.S.,
A curve evolution-based variational approach to simultaneous image restoration and segmentation,
ICIP02(I: 109-112).
IEEE DOI 0210
BibRef

Tsai, A.,
Curve Evolution, Boundary-value Stochastic Processes, the Mumford-Shah Problem, and Missing Data Applications,
ICIP00(Vol III: 588-591).
IEEE DOI 0008
See also Optimal Approximations by Piecewise Smooth Functions and Variational Problems. BibRef

Unal, G.[Gozde], Krim, H.[Hamid], Yezzi, A.J.[Anthony J.],
Stochastic differential equations and geometric flows,
IP(11), No. 12, December 2002, pp. 1405-1416.
IEEE DOI 0301
Local stochastic interpretation of the basic curve smoothing equation, the geometric heat equation, this evolution amounts to a tangential diffusion movement of the particles along the contour. BibRef

Unal, G.[Gozde], Yezzi, A.J.[Anthony J.], Krim, H.[Hamid],
Information-Theoretic Active Polygons for Unsupervised Texture Segmentation,
IJCV(62), No. 3, May 2005, pp. 199-220.
Springer DOI 0501
BibRef

Unal, G.[Gozde], Krim, H.[Hamid], Yezzi, A.J.[Anthony J.],
Fast Incorporation of Optical Flow Into Active Polygons,
IP(14), No. 6, June 2005, pp. 745-759.
IEEE DOI 0505
BibRef
Earlier:
Active polygon for object tracking,
3DPVT02(696-699). 0206
BibRef

Unal, G.[Gozde], Krim, H.[Hamid],
Feature-preserving Flows: A Stochastic Differential Equation's View,
ICIP00(Vol I: 896-899).
IEEE DOI 0008
BibRef

Unal, G., Nain, D., Ben-Arous, G., Shimk-In, N., Tannenbaum, A., Zeitouni, O.,
Algorithms for stochastic approximations of curvature flows,
ICIP03(II: 651-654).
IEEE DOI 0312
BibRef

Li, C.M.[Chun-Ming], Liu, J.D.[Jun-Dong], Fox, M.D.[Martin D.],
Segmentation of external force field for automatic initialization and splitting of snakes,
PR(38), No. 11, November 2005, pp. 1947-1960.
WWW Link. 0509
BibRef
Earlier:
Segmentation of Edge Preserving Gradient Vector Flow: An Approach Toward Automatically Initializing and Splitting of Snakes,
CVPR05(I: 162-167).
IEEE DOI 0507
See also Distance Regularized Level Set Evolution and Its Application to Image Segmentation. BibRef

Michailovich, O.V.[Oleg V.], Rathi, Y.[Yogesh], Tannenbaum, A.[Allen],
Image Segmentation Using Active Contours Driven by the Bhattacharyya Gradient Flow,
IP(16), No. 11, November 2007, pp. 2787-2801.
IEEE DOI 0709
BibRef
Earlier: A2, A3, A1:
Segmenting Images on the Tensor Manifold,
CVPR07(1-8).
IEEE DOI 0706
See also high-resolution technique for ultrasound harmonic imaging using sparse representations in gabor frames, A. BibRef

Karasev, P., Kolesov, I., Fritscher, K., Vela, P., Mitchell, P., Tannenbaum, A.,
Interactive Medical Image Segmentation Using PDE Control of Active Contours,
MedImg(32), No. 11, 2013, pp. 2127-2139.
IEEE DOI 1312
biomedical MRI See also high-resolution technique for ultrasound harmonic imaging using sparse representations in gabor frames, A. BibRef

Hahn, J.Y.[Joo-Young], Lee, C.O.[Chang-Ock],
Geometric attraction-driven flow for image segmentation and boundary detection,
JVCIR(21), No. 1, January 2010, pp. 56-66.
Elsevier DOI 1002
Geometric attraction-driven flow; Binary edge function; Binary balloon force; Image segmentation; Weak edge; Multiple junctions; Concave boundary; Dual level set functions BibRef

Liu, L.X.[Li-Xiong], Bovik, A.C.[Alan C.],
Active contours with neighborhood-extending and noise-smoothing gradient vector flow external force,
JIVP(2012), No. 1 2012, pp. xx-yy.
DOI Link 1202
BibRef

Ye, J.T.[Jun-Tao], Xu, G.L.[Guo-Liang],
Geometric Flow Approach for Region-Based Image Segmentation,
IP(21), No. 12, December 2012, pp. 4735-4745.
IEEE DOI 1212
BibRef

Qin, L., Zhu, C., Zhao, Y., Bai, H., Tian, H.,
Generalized Gradient Vector Flow for Snakes: New Observations, Analysis, and Improvement,
CirSysVideo(23), No. 5, May 2013, pp. 883-897.
IEEE DOI 1305
BibRef

Cook, D.A., Mueller, M.F., Fedele, F., Yezzi, A.J.,
Adjoint Active Surfaces for Localization and Imaging,
IP(24), No. 1, January 2015, pp. 316-331.
IEEE DOI 1502
Helmholtz equations BibRef


Di, H., Shi, Q., Lv, F., Qin, M., Lu, Y.,
Contour Flow: Middle-Level Motion Estimation by Combining Motion Segmentation and Contour Alignment,
ICCV15(4355-4363)
IEEE DOI 1602
Computer vision BibRef

Derraz, F.[Foued], Boussahla, M.[Miloud], Peyrodie, L.[Laurent],
Globally Segmentation Using Active Contours and Belief Function,
ACIVS13(546-554).
Springer DOI 1311
BibRef
Earlier: A1, A3, Only:
Fast Unsupervised Segmentation Using Active Contours and Belief Functions,
CAIP13(278-285).
Springer DOI 1308
BibRef

Derraz, F., Peyrodie, L., Taleb-Ahmed, A., Forzy, G.,
Texture segmentation using globally active contours model and Cauchy-Schwarz distance,
IPTA12(391-395)
IEEE DOI 1503
image segmentation BibRef

Derraz, F.[Foued], Peyrodie, L.[Laurent], Thiran, J.P.[Jean-Philippe], Taleb-Ahmed, A.[Abdelmalik], Forzy, G.[Gerard],
Binary Active Contours using both inside and outside texture descriptors,
IPTA12(325-329)
IEEE DOI 1503
BibRef
And: A1, A3, A4, A2, A5:
Fast globally supervised segmentation by active contours with shape and texture descriptors,
ICIP12(2545-2548).
IEEE DOI 1302
image segmentation BibRef

Derraz, F.[Foued], Taleb-Ahmed, A.[Abdelmalik], Chikh, A.[Azzeddine], Boydev, C.[Christina], Peyrodie, L.[Laurent], Forzy, G.[Gerard],
Segmentation of Prostate Using Interactive Finsler Active Contours and Shape Prior,
ICISP12(397-405).
Springer DOI 1208
BibRef

Derraz, F.[Foued], Taleb-Ahmed, A.[Abdelmalik], Peyrodie, L.[Laurent], Forzy, G.[Gerard], Boydev, C.[Christina],
Fast Finsler Active Contours and Shape Prior Descriptor,
CIARP11(189-196).
Springer DOI 1111
BibRef

Derraz, F.[Foued], Taleb-Ahmed, A.[Abdelmalik], Betrouni, N.[Nacim], Chikh, A.[Azzeddine], Pinti, A.[Antonio], Bereksi-Reguig, F.[Fethi],
Unsupervised texture segmentation using active contours driven by the Chernoff gradient flow,
ICIP09(3005-3008).
IEEE DOI 0911
BibRef

Derraz, F.[Foued], Taleb-Ahmed, A.[Abdelmalik], Pinti, A.[Antonio], Peyrodie, L.[Laurent], Betrouni, N.[Nacim], Chikh, A.[Azzeddine], Bereksi-Reguig, F.[Fethi],
Fast Unsupervised Texture Segmentation Using Active Contours Model Driven by Bhattacharyya Gradient Flow,
CIARP09(193-200).
Springer DOI 0911
BibRef

Derraz, F., Taleb-Ahmed, A., Peyrodie, L., Pinti, A., Chikh, A., Bereksi-Reguig, F.,
Active Contours Based Battachryya Gradient Flow for Texture Segmentation,
CISP09(1-6).
IEEE DOI 0910
BibRef

Zhao, B.[Bin], Cheng, S.Y.[Si-Yuan], Zhang, X.W.[Xiang-Wei], Zhang, G.Y.[Guo-Ying],
B-Spline Curve Fitting Based on Gradient Vector Flow Deformable Models,
CISP09(1-4).
IEEE DOI 0910
BibRef

Wang, Y.Q., Chen, W.F., Yu, T.L., Zhang, Y.T.,
Hessian based image structure adaptive gradient vector flow for parametric active contours,
ICIP10(649-652).
IEEE DOI 1009
BibRef

Lu, S.P.[Shao-Pei], Wang, Y.Q.[Yuan-Quan],
A Reformative Gradient Vector Flow Based on Beltrami Flow,
CISP09(1-4).
IEEE DOI 0910
BibRef

Tang, J.S.[Jin-Shan], Acton, S.T.,
A DCT based gradient vector flow snake for object boundary detection,
Southwest04(157-161).
WWW Link. 0411
BibRef

Yu, Y.J.[Yang-Jian], Acton, S.T.,
Active contours with area-weighted binary flows for segmenting low SNR imagery,
ICIP03(I: 129-132).
IEEE DOI 0312
BibRef

Yu, H.G.[Hong-Gang], Pattichis, M.S., Goens, M.B.,
Robust Segmentation of Freehand Ultrasound Image Slices Using Gradient Vector Flow Fast Geometric Active Contours,
Southwest06(115-119).
IEEE DOI 0603
BibRef

Rivera-Rovelo, J.[Jorge], Herold, S.[Silena], Bayro-Corrochano, E.[Eduardo],
Object Segmentation Using Growing Neural Gas and Generalized Gradient Vector Flow in the Geometric Algebra Framework,
CIARP06(306-315).
Springer DOI 0611
See also Use of Geometric Algebra for 3D Modeling and Registration of Medical Data, The. BibRef

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Interactive Region Segmentations, Snakes, User-Assisted Segmentation .


Last update:Sep 18, 2017 at 11:34:11