Cordella, L.P.,
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Elsevier DOI As a parallel problem.
BibRef
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PR(11), No. 3, 1979, pp. 191-204.
Elsevier DOI
See also Boundary Detection of Radiographic Images by a Threshold Method.
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Pun, T.,
Entropic Thresholding: A New Approach,
CGIP(16), No. 3, July 1981, pp. 210-239.
Elsevier DOI Based on asymmetry of histograms.
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Pun, T.,
A New Method for Grey-Level Picture Thresholding Using the Entropy
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SP(2), No 3, July 1980, pp. 223-237.
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Sommer, R.[Ruediger],
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US_Patent4,315,285, Feb 9, 1982
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Segmentation by Thresholding,
PAMI(5), No. 1, January 1983, pp. 48-54.
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Deravi, F.,
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Gray Level Thresholding Using Second-Order Statistics,
PRL(1), 1983, pp. 417-422.
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Hassan, M.H.,
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Thresholding Based on Learning Theory,
PIEEE(76), 1988, pp. 1379-1381.
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Olafsson, S., and
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The Capacity of a Multilevel Threshold Functions,
PAMI(10), No. 2, March 1988, pp. 277-281.
IEEE DOI
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Lee, J.S.,
Yang, M.C.K.,
Threshold Selection Using Estimates from Truncated Normal Distribution,
SMC(19), No. 4, July 1989, pp. 422-429.
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Petilli, E.M.[Eugene M.],
Method for thresholding an image signal,
US_Patent4,912,569, Mar 27, 1990
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Apparatus for thresholding an image signal,
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Parker, J.R.,
Gray Level Thresholding in Badly Illuminated Images,
PAMI(13), No. 8, August 1991, pp. 813-819.
IEEE DOI
Segmentation, Binarization. A two-class technique which assumes the only alternative is to find
a single threshold. Find points with high gradients, grow regions
which have similar values. Essentially finds multiple thresholds
for different characters (character extraction experiments).
BibRef
9108
Dunn, S.M.,
Harwood, D., and
Davis, L.S.,
Local Estimation of the Uniform Error Threshold,
PAMI(6), No. 6, November 1984, pp. 742-747.
BibRef
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Wójcik, Z.M.[Zbigniew M.],
A Natural Approach in Image Processing and Pattern Recognition:
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Segmentation and Shape Recognition,
PR(18), No. 5, 1985, pp. 299-326.
Elsevier DOI Edge preserving.
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Brink, A.D.,
Gray-Level Thresholding of Images Using A Correlation Criterion,
PRL(9), No. 5, June 1989, pp. 335-341.
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Cseke, I., and
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Comments on Gray-Level Thresholding of Images Using a
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PRL(11), 1990, pp. 709-710.
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Brink, A.D.,
Comments on Grey-Level Thresholding of Images Using a
Correlation Criterion,
PRL(12), 1991, pp. 91-92.
BibRef
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Shanbhag, A.G.,
Utilization of Information Measure as a Means of Image Thresholding,
GMIP(56), No. 5, September 1994, pp. 414-419.
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Cheng, J.C.,
Don, H.S.,
Segmentation of Bilevel Images Using Mathematical Morphology,
PRAI(6), 1992, pp. 595-628.
BibRef
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Cho, S.Z.[Sung-Zoon],
Haralick, R.M.[Robert M.],
Yi, S.[Seungku],
Improvement of Kittler and Illingworth's Minimum Error Thresholding,
PR(22), No. 5, 1989, pp. 609-617.
Elsevier DOI
See also Minimum Error Thresholding.
BibRef
8900
Kittler, J.V.,
Illingworth, J.,
Föglein, J.,
Threshold Selection Based on a Simple Image Statistic,
CVGIP(30), No. 2, May 1985, pp. 125-147.
Elsevier DOI
Segmentation, Binarization. (SERC, UK) and (Hungary).
The threshold is selected on small windows (size depends on
differences) without using the histogram computation. It seems to
say that it is relevant only for the two class segmentation
problem. Some of the ideas could be applied to a general
histogram based segmentation scheme.
BibRef
8505
Kittler, J.V., and
Illingworth, J.,
Minimum Error Thresholding,
PR(19), No. 1, 1986, pp. 41-47.
Elsevier DOI
Segmentation, Unimodal.
Discusses the problems of unimodal histograms.
Compared in:
See also Comparative Performance Study of Several Global Thresholding Techniques for Segmentation, A.
BibRef
8600
Kittler, J.V., and
Illingworth, J.,
On Threshold Selection Using Clustering Criteria,
SMC(15), No. 5, September-October 1985, pp. 652-655.
Segmentation, Clustering.
Clustering. Also compares some techniques.
BibRef
8509
Kittler, J.V., and
Föglein, J.,
Contextual Classification of Multispectral Pixel Data,
IVC(2), No. 1, February 1984, pp. 13-29.
Elsevier DOI
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Kittler, J.V.,
Illingworth, J.,
Föglein, J.,
Paler, K.,
An Automatic Thresholding Algorithm and Its Performance,
ICPR84(287-289).
BibRef
8400
Yanowitz, S.D., and
Bruckstein, A.M.,
A New Method for Image Segmentation,
CVGIP(46), No. 1, April 1989, pp. 82-95.
Elsevier DOI
BibRef
8904
Earlier:
ICPR88(I: 270-275).
IEEE DOI
Segmentation, Edges.
Adaptive Threshold. Thresholds are selected based on high gradient points and
interpolation between scattered points in the image.
Mostly an adaptive threshold selection scheme rather than a
segmentation scheme.
In the evaluation, this postprocessing improved all others
to get the best results.
Compared in:
See also Evaluation of Binarization Methods for Document Images.
BibRef
Blanz, W.E.,
Shung, C.B.,
Cox, C.E.,
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Dom, B.E., and
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MVA(6), 1993, pp. 181-190.
BibRef
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Earlier:
ICPR90(II: 413-421).
IEEE DOI
9208
Hardware to do the binarization process. It seems to work well.
BibRef
Blanz, W.E.,
Sanz, J.L.C.,
Petkovic, D.,
Control Free, Low-Level Image Segmentation:
Theory, Architecture, and Experimentation,
ICCV87(439-443).
BibRef
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Blanz, W.E.,
Cox, C.E.,
Gish, S.L.,
Connectionist Architectures in Low Level Image Segmentation,
HPRCV97(Chapter V:5).
(IBM,Almaden Res. Ctr.)
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Blanz, W.E.,
Gish, S.L.,
A connectionist classifier architecture applied to image segmentation,
ICPR90(II: 272-277).
IEEE DOI
9208
BibRef
Song, S.,
Liao, M.,
Qin, J.,
Multiresolution Image Dynamic Thresholding,
MVA(3), 1990, pp. 13-16.
See also Multiresolution Image Motion Detection and Displacement Estimation.
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Brink, A.D.,
Thresholding Of Digital Images Using Two-Dimensional Entropies,
PR(25), No. 8, August 1992, pp. 803-808.
Elsevier DOI 2D entropies from 2D histogram.
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Chang, C.I.[Chein-I],
Chen, K.[Kebo],
Wang, J.W.[Jian-Wei],
Althouse, M.L.G.[Mark L.G.],
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Elsevier DOI
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Althouse, M.L.G.,
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Image segmentation by local entropy methods,
ICIP95(III: 61-64).
IEEE DOI
9510
BibRef
Lie, W.N.,
Automatic Target Segmentation by Locally Adaptive Image Thresholding,
IP(4), No. 7, July 1995, pp. 1036-1041.
IEEE DOI
Adaptive Threshold.
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Morii, F.[Fujiki],
An Image Thresholding Method Using a Minimum Weighted
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PR(28), No. 7, July 1995, pp. 1063-1071.
Elsevier DOI
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Brink, A.D.,
Minimum Spatial Entropy Threshold Selection,
VISP(142), No. 3, June 1995, pp. 128-132.
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Ramesh, N.,
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Sethi, I.K.,
Thresholding Based on Histogram Approximation,
VISP(142), No. 5, October 1995, pp. 271-279.
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Lee, Y.C.[Yong-Chun],
Basile, J.M.[Joseph M.],
Rudak, P.[Peter],
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US_Patent5,583,659, November 10, 1994.
HTML Version.
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Brink, A.D.,
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PRL(17), No. 1, January 10 1996, pp. 29-36.
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Li, C.H.,
Lee, C.K.,
Minimum Cross Entropy Thresholding,
PR(26), No. 4, April 1993, pp. 617-625.
Elsevier DOI minimize cross entropy between image and the segmentation.
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Li, C.H.,
Tam, P.K.S.,
An Iterative Algorithm For Minimum Cross-Entropy Thresholding,
PRL(19), No. 8, June 1998, pp. 771-776.
9808
BibRef
Brink, A.D.,
Pendock, N.E.,
Minimum Cross-Entropy Threshold Selection,
PR(29), No. 1, January 1996, pp. 179-188.
Elsevier DOI Optimal threshold
BibRef
9601
Gelfand, S.B.,
Fortmann, T.E.,
Bar-Shalom, Y.,
Adaptive Detection Threshold Optimization for Tracking in Clutter,
AeroSys(32), No. 2, April 1996, pp. 514-523.
9605
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Zhang, T.X.,
Peng, J.X.,
Li, Z.J.,
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SMC-B(26), No. 4, August 1996, pp. 619-627.
IEEE Top Reference. Finds small regions with a complex background.
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Leung, C.K.,
Lam, F.K.,
Performance Analysis for a Class of
Iterative Image Thresholding Algorithms,
PR(29), No. 9, September 1996, pp. 1523-1530.
Elsevier DOI
Image Thresholding.
Image Segmentation. Analyze 3 iterative thresholding algorithms.
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9609
Leung, C.K.,
Lam, F.K.,
Maximum A-Posteriori Spatial Probability Segmentation,
VISP(144), No. 3, June 1997, pp. 161-167.
9708
BibRef
Leung, C.K.,
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Maximum Segmented Image Information Thresholding,
GMIP(60), No. 1, January 1998, pp. 57-76.
BibRef
9801
Earlier:
Maximum Segmented-Scene Spatial Entropy Thresholding,
ICIP96(III: 963-966).
IEEE DOI
BibRef
Pal, N.R.[Nikhil R.],
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PR(29), No. 4, April 1996, pp. 575-580.
Elsevier DOI
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9604
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PR(29), No. 5, May 1996, pp. 829-843.
Elsevier DOI
9605
Segmentation for distinct objects.
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Groenewald, A.M.,
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Snyder, W.E.,
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Logenthiran, A.,
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Optimal Thresholding: A New Approach,
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Morii, F.,
A Note on Minimum Error Thresholding,
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Transition Region Determination Based Thresholding,
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Semantic Thresholding,
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Dutta Majumder, D.,
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Chanda, B.,
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See also Some Algorithms for Image Enhancement Incorporating Human Visual Response.
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Image Thresholding Based on Ali-Silvey Distance Measures,
PR(30), No. 7, July 1997, pp. 1161-1174.
Elsevier DOI
9707
BibRef
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Fast Iterative Segmentation of High-Resolution Medical Images,
NucSci(44), No. 3, Part 2, June 1997, pp. 1362-1367.
9707
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9801
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Adaptive Thresholding By Variational Method,
IP(7), No. 3, March 1998, pp. 468-473.
IEEE DOI
9803
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9806
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9808
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IEEE DOI Separating 2 populations -- object from background.
Use spatial covariance.
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Wu, X.J.[Xue-Jing],
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A fast recurring two-dimensional entropic thresholding algorithm,
PR(32), No. 12, December 1999, pp. 2055-2061.
Elsevier DOI
BibRef
9912
Heucke, L.,
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A New Image Segmentation Method Based on Human Brightness Perception
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IEEE Top Reference.
0006
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IP(10), No. 5, May 2001, pp. 708-714.
IEEE DOI
0105
BibRef
Park, Y.T.[Young-Tae],
Shape-resolving local thresholding for object detection,
PRL(22), No. 8, June 2001, pp. 883-890.
Elsevier DOI
0105
BibRef
Snidaro, L.,
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Real-time thresholding with Euler numbers,
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Elsevier DOI
0304
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Chen, H.C.[Hsin-Chia],
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IEEE Abstract.
0407
BibRef
Earlier:
Constrast based color segmentation with adaptive thresholds,
ICIP02(II: 73-76).
IEEE DOI
0210
BibRef
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Gesualdi Mello, A.R.,
Portes de Albuquerque, M.,
Image thresholding using Tsallis entropy,
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Elsevier DOI
0407
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Threshold selection based on cluster analysis,
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Elsevier DOI
0407
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And:
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PRL(30), No. 10, 15 July 2009, pp. 950.
Elsevier DOI
0906
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Elsevier DOI
0501
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Elsevier DOI
0506
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CRV05(57-64).
IEEE DOI
0505
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Elsevier DOI
0611
Block thresholding; Boundary mismatch; Image continuity; Image variance
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0711
Multilevel thresholding; Image segmentation; Histogram; Recursion; Sub-range
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Adaptive image thresholding for real-time particle monitoring,
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IEEE DOI
0706
Discrete energy functional, and implement differentiation.
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A Convex Approach for Variational Super-Resolution,
DAGM10(313-322).
Springer DOI
1009
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A Variational Model for Interactive Shape Prior Segmentation and
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SSVM09(200-211).
Springer DOI
0906
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Unger, M.[Markus],
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Pock, T.[Thomas],
Bischof, H.[Horst],
Tracking as Segmentation of Spatial-Temporal Volumes by Anisotropic
Weighted TV,
EMMCVPR09(193-206).
Springer DOI
0908
Total Variation (TV) regularization.
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Leistner, C.[Christian],
Saffari, A.[Amir],
Santner, J.[Jakob],
Bischof, H.[Horst],
Semi-Supervised Random Forests,
ICCV09(506-513).
IEEE DOI
0909
BibRef
Godec, M.[Martin],
Leistner, C.[Christian],
Saffari, A.[Amir],
Bischof, H.[Horst],
On-Line Random Naive Bayes for Tracking,
ICPR10(3545-3548).
IEEE DOI
1008
BibRef
Earlier: A2, A1, A3, A4:
On-Line Multi-view Forests for Tracking,
DAGM10(493-502).
Springer DOI
1009
BibRef
Saffari, A.[Amir],
Leistner, C.[Christian],
Santner, J.[Jakob],
Godec, M.[Martin],
Bischof, H.[Horst],
On-line Random Forests,
Learning09(1393-1400).
IEEE DOI
0910
See also On robustness of on-line boosting: a competitive study.
See also Online multi-class LPBoost.
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Santner, J.[Jakob],
Unger, M.[Markus],
Pock, T.[Thomas],
Leistner, C.[Christian],
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BMVC09(xx-yy).
PDF File.
0909
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Unger, M.,
Pock, T.,
Trobin, W.,
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PDF File.
0809
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Cremers, D.[Daniel],
Bischof, H.[Horst],
Fast and exact solution of Total Variation models on the GPU,
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IEEE DOI
0806
BibRef
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Bischof, H.[Horst],
A Probabilistic Multi-phase Model for Variational Image Segmentation,
DAGM06(71-80).
Springer DOI
0610
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Bustince, H.,
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Elsevier DOI
0711
Restricted equivalence functions; Restricted dissimilarity functions;
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Elsevier DOI
0902
BibRef
Earlier: A2, A1:
Edge Sensitive Variational Image Thresholding,
ICIP07(VI: 37-40).
IEEE DOI
0709
Minimax optimization; Variational calculus; Image thresholding
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Zheng, L.Y.[Li-Ying],
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0911
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Kamilov, U.S.,
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1209
1 bit quantization.
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Lai, Y.K.[Yu-Kun],
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computational complexity
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Compressive sensing
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Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Shadow Detection, Removal and Extraction .