Validation and Verification of Neural Network Systems,
2006.
Dataset, Segmentation.
HTML Version. Annotated data.
LHI Segmentation Dataset,
Subset of larger dataset.
Online2008
HTML Version.
Dataset, Segmentation.
See also Lotus Hill Institute.
BibRef
0800
Ranade, S., and
Prewitt, J.M.S.,
A Comparison of Some Segmentation Algorithms for Cytology,
ICPR80(561-564).
Survey, Segmentation.
Evaluation, Segmentation.
Segmentation, Histogram.
Segmentation, Survey.
Relaxation.
Segmentation, Evaluation. Compares 5 segmentation method for cell segmentation.
BibRef
8000
Hartley, R.L.,
Wang, C.Y.,
Kitchen, L., and
Rosenfeld, A.,
Segmentation of FLIR Images: A Comparative Study,
SMC(12), No. 4, July/August 1982, pp. 553-566.
BibRef
8207
Earlier:
DARPA82(323-341).
FLIR.
Evaluation, Segmentation.
Segmentation, Evaluation.
Relaxation. Compares super slice, pyramid spot detection, relaxation (2),
pyramid linking, and super spike. Superspike won. 88% of the
targets and 1.6 false alarms per true target (the second number
seems excessive?) using segmentation alone.
BibRef
Weszka, J.S.,
A Survey of Threshold Selection Techniques,
CGIP(7), No. 2, April 1978, pp. 259-265.
WWW Version.
Threshold Selection, Survey.
Survey, Segmentation.
Survey, Threshold Selection.
Segmentation, Thresholds.
Segmentation, Survey.
BibRef
7804
Gurari, E.M., and
Wechsler, H.,
On the Difficulties Involved in the Segmentation of Pictures,
PAMI(4), No. 3, May 1982, pp. 304-306.
BibRef
8205
Sahoo, P.K.,
Soltani, S.,
Wong, A.K.C., and
Chen, Y.C.,
A Survey of Thresholding Techniques,
CVGIP(41), No. 2, February 1988, pp. 233-260.
WWW Version.
Survey, Segmentation.
Survey, Threshold Selection.
Segmentation, Thresholds.
Threshold Selection, Survey. An update of
See also Survey of Threshold Selection Techniques, A. Analytic analysis of thresholding results.
BibRef
8802
Pal, N.R., and
Pal, S.K.,
A Review on Image Segmentation Techniques,
PR(26), No. 9, September 1993, pp. 1277-1294.
WWW Version.
PDF Version.
Survey, Segmentation.
Evaluation, Segmentation.
BibRef
9309
Nazif, A.M., and
Levine, M.D.,
Dynamic Measurement of Computer Generated Image Segmentations,
PAMI(7), No. 2, March 1985, pp. 155-164.
(McGill)
Evaluation, Segmentation.
The measurement of parameters that indicate how good the
segmentation is currently, are fed back to change the segmentation
so that it is optimized for the criterion being applied. This is a
companion paper with the following paper on a rule-based
segmentation method.
BibRef
8503
Nazif, A.M., and
Levine, M.D., (McGill)
Low Level Image Segmentation: An Expert System,
PAMI(6), No. 5, September 1984, pp. 555-577.
BibRef
8409
And:
Authors reply:
PAMI(8), No. 5, September 1986, pp. 676.
Segmentation, Expert system.
Segmentation, Evaluation. An expert system for segmentation. There are comparisons with
other methods (split and merge [With errors, see the comments
paper.] and histogram). The results are not overwhelming, they
look more like what would be expected with low tolerances for a
histogram based approach. Low level implies data driven rather
than model driven.
Analysis in:
See also Comment on Using the Uniformity Measure for Performance-Measure in Image Segmentation.
BibRef
Pavlidis, T.,
Comments on 'Low Level Image Segmentation: An Expert System',
PAMI(8), No. 5, September 1986, pp. 675-676.
BibRef
8609
Levine, M.D., and
Nazif, A.M.,
Rule-Based Image Segmentation: A Dynamic Control Strategy Approach,
CVGIP(32), No. 1, October 1985, pp. 104-126.
WWW Version.
Segmentation, Expert system. Control aspects of rule based segmentation
See also Low Level Image Segmentation: An Expert System.
BibRef
8510
Levine, M.D., and
Nazif, A.M.,
An Optimal Set of Image Segmentation Rules,
PRL(2), 1984, pp. 243-248.
BibRef
8400
Yasnoff, W.A.[William A.],
Mui, J.K.[Jack K.],
Bacus, J.W.[James W.],
Error Measures for Scene Segmentation,
PR(9), No. 4, 1977, pp. 217-231.
Evaluation, Segmentation.
Segmentation, Evaluation.
WWW Version. Subjective methods are inadequate for evaluations. Objective
measures created by correlation with human observation of multiple
segmentations of some scenes and multiple scenes with same
segmentation technique. Two measures are: percentage of area
misclassified (P); pixel error distance (sum of D^2 of each error
pixel (distance to the nearest correct pixel, SQRT of it divided by
image area)). Both can be helpful, but P is not always good since
there is no spatial information.
BibRef
7700
Jiang, H.,
Toriwaki, J.,
Suzuki, H.,
Comparative Performance Evaluation of Segmentation Methods Based
on Region Growing and Division,
SCJ(24), No. 13, 1993, pp. 28-42.
Evaluation, Segmentation.
BibRef
9300
Zhang, Y.J.,
A Survey on Evaluation Methods for Image Segmentation,
PR(29), No. 8, August 1996, pp. 1335-1346.
WWW Version.
9608
Evaluation, Segmentation.
Survey, Segmentation.
Segmentation, Evaluation.
BibRef
Kaushal, T.P.,
Towards Visually Convincing Image Segmentation,
IVC(10), No. 9, November 1992, pp. 617-624.
WWW Version.
BibRef
9211
Zhang, Y.J.,
Evaluation and Comparison of Different Segmentation Algorithms,
PRL(18), No. 10, October 1997, pp. 963-974.
9802
Evaluation, Segmentation.
BibRef
Beauchemin, M.,
Thomson, K.P.B.,
The Evaluation of Segmentation Results and the Overlapping Area Matrix,
JRS(18), No. 18, December 1997, pp. 3895-3899.
9801
Evaluation, Segmentation.
BibRef
Zhang, Y.J.,
Gerbrands, J.J.,
Objective and quantitative segmentation evaluation and comparison,
SP(39), No. 1-2, 1994, pp. 43-54.
Evaluation, Segmentation.
BibRef
9400
Earlier:
Comparison of thresholding techniques using synthetic images and
ultimate measurement accuracy,
ICPR92(III:209-213).
IEEE DOI Reference
9208
BibRef
Correia, P.L.[Paulo Lobato],
Pereira, F.[Fernando],
Stand-Alone Objective Segmentation Quality Evaluation,
JASP(2002), No. 4, 2002, pp. 389-400.
HTML Version.
0204
Evaluation, Segmentation.
BibRef
Earlier:
Objective Evaluation of Relative Segmentation Quality,
ICIP00(Vol I: 308-311).
IEEE Abstract. IEEE Top Reference.
0008
BibRef
Correia, P.L.[Paulo Lobato],
Pereira, F.[Fernando],
Objective evaluation of video segmentation quality,
IP(12), No. 2, February 2003, pp. 186-200.
IEEE DOI Reference
0304
Evaluation, Video Segmentation.
BibRef
Lucieer, A.,
Stein, A.,
Existential uncertainty of spatial objects segmented from satellite
sensor imagery,
GeoRS(40), No. 11, November 2002, pp. 2518-2521.
IEEE Top Reference.
0301
BibRef
Lei, T.[Tianhu],
Udupa, J.K.,
Performance evaluation of finite normal mixture model-based image
segmentation techniques,
IP(12), No. 10, October 2003, pp. 1153-1169.
IEEE DOI Reference
0310
BibRef
Warfield, S.K.,
Zou, K.H.,
Wells, III, W.M.[William M.],
Simultaneous Truth and Performance Level Estimation (STAPLE):
An Algorithm for the Validation of Image Segmentation,
MedImg(23), No. 7, July 2004, pp. 903-921.
IEEE Abstract. IEEE Top Reference.
0407
BibRef
Paglieroni, D.W.[David W.],
Design considerations for image segmentation quality assessment
measures,
PR(37), No. 8, August 2004, pp. 1607-1617.
WWW Version.
0407Assessment requires 1 manual segmentation for reference.
BibRef
Zouagui, T.,
Benoit-Cattin, H.,
Odet, C.,
Image segmentation functional model,
PR(37), No. 9, September 2004, pp. 1785-1795.
WWW Version.
0407Describe segmentation in general with 5 different operations. Compose these
into particular algorithms.
BibRef
Villegas, P.,
Marichal, X.,
Perceptually-Weighted Evaluation Criteria for Segmentation Masks in
Video Sequences,
IP(13), No. 8, August 2004, pp. 1092-1103.
IEEE DOI Reference
0409
Evaluation, Video Segmentation. Automatic evaluation of segmentations.
BibRef
Yong, X.[Xia],
Feng, D.[Dagan],
Zhao, R.C.[Rong-Chun],
Petrou, M.[Maria],
Learning-based algorithm selection for image segmentation,
PRL(26), No. 8, June 2005, pp. 1059-1068.
WWW Version.
0506
BibRef
Cardoso, J.S.,
Corte-Real, L.,
Toward a Generic Evaluation of Image Segmentation,
IP(14), No. 11, November 2005, pp. 1773-1782.
IEEE DOI Reference
0510
Evaluation, Segmentation.
BibRef
Cardoso, J.S.,
Corte-Real, L.,
A Measure for Mutual Refinements of Image Segmentations,
IP(15), No. 8, August 2006, pp. 2358-2363.
IEEE DOI Reference
0606
BibRef
Carleer, A.P.,
Debeir, O.,
Wolff, E.,
Assessment of Very High Spatial Resolution Satellite Image
Segmentations,
PhEngRS(71), No. 11, November 2005, pp. 1285-1294.
WWW Version.
0602
Evaluation, Segmentation. An evaluation of several segmentation algorithms carried out with
empirical discrepancy methods.
BibRef
Martin, A.[Arnaud],
Laanaya, H.[Hicham],
Arnold-Bos, A.[Andreas],
Evaluation for uncertain image classification and segmentation,
PR(39), No. 11, November 2006, pp. 1987-1995.
WWW Version.
0608
Evaluation, Classifiers. Image classification; Image segmentation; Uncertain environment; Expert fusion
BibRef
Wolf, C.[Christian],
Jolion, J.M.[Jean-Michel],
Object count/area graphs for the evaluation of object detection and
segmentation algorithms,
IJDAR(8), No. 4, September 2006, pp. 280-296.
Springer DOI Reference
0609
BibRef
Ortiz, A.[Alberto],
Oliver, G.[Gabriel],
On the use of the overlapping area matrix for image segmentation
evaluation: A survey and new performance measures,
PRL(27), No. 16, December 2006, pp. 1916-1926.
WWW Version.
0611
Evaluation, Segmentation.
BibRef
Earlier:
A Novel Segmentation Strategy Based on Colour Channels Coupling,
CIAP05(328-335).
Springer DOI Reference
0509Performance evaluation; Image segmentation; Overlapping area matrix
BibRef
Crum, W.R.[William R.],
Camara, O.,
Hill, D.L.G.,
Generalized Overlap Measures for Evaluation and Validation in Medical
Image Analysis,
MedImg(25), No. 11, November 2006, pp. 1451-1461.
IEEE DOI Reference
0611
Evaluation, Segmentation.
overlap for registration or segmentation evaluation.
See also Phenomenological Model of Diffuse Global and Regional Atrophy Using Finite-Element Methods.
BibRef
Chang, C.I.,
Du, Y.,
Wang, J.,
Guo, S.M.,
Thouin, P.D.,
Survey and comparative analysis of entropy and relative entropy
thresholding techniques,
VISP(153), No. 6, December 2006, pp. 837-850.
WWW Version.
0702
Survey, Segmentation.
BibRef
Chen, H.C.,
Wang, S.J.,
Visible colour difference-based quantitative evaluation of colour
segmentation,
VISP(153), No. 5, October 2006, pp. 598-609.
WWW Version.
0702
Evaluation, Segmentation.
BibRef
Unnikrishnan, R.[Ranjith],
Pantofaru, C.[Caroline],
Hebert, M.[Martial],
Toward Objective Evaluation of Image Segmentation Algorithms,
PAMI(29), No. 6, June 2007, pp. 929-944.
IEEE DOI Reference
0704
Evaluation, Segmentation.
BibRef
Earlier:
A Measure for Objective Evaluation of Image Segmentation Algorithms,
EEMCV05(III: 34-34).
IEEE DOI Reference
0507Segmentation is usually subjective, no one ground truth.
Use Normalized Probabilistic Rand index to compare segmentations.
See also Objective Criteria for the Evaluation of Clustering Methods.
BibRef
Pantofaru, C.[Caroline],
Hebert, M.[Martial],
A Comparison of Image Segmentation Algorithms,
CMU-RI-TR-05-40, September, 2005.
WWW Version.
BibRef
0509
Barnard, K.[Kobus],
Fan, Q.F.[Quan-Fu],
Swaminathan, R.[Ranjini],
Hoogs, A.[Anthony],
Collins, R.[Roderic],
Rondot, P.[Pascale],
Kaufhold, J.[John],
Evaluation of Localized Semantics: Data, Methodology, and Experiments,
IJCV(77), No. 1-3, May 2008, pp. 199-217.
Springer DOI Reference
0803
Dataset, Segmentation. Dataset with hand segmentations.
WWW Version.
BibRef
Zhang, H.[Hui],
Fritts, J.E.[Jason E.],
Goldman, S.A.[Sally A.],
Image segmentation evaluation: A survey of unsupervised methods,
CVIU(110), No. 2, May 2008, pp. 260-280.
WWW Version.
0804
Evaluation, Segmentation.
Survey, Segmentation. Image segmentation; Objective evaluation; Unsupervised evaluation;
Empirical goodness measure
BibRef
Zhang, H.[Hui],
Cholleti, S.R.[Sharath R.],
Goldman, S.A.[Sally A.],
Fritts, J.E.[Jason E.],
Meta-Evaluation of Image Segmentation Using Machine Learning,
CVPR06(I: 1138-1145).
IEEE DOI Reference
0606 See also Localized Content-Based Image Retrieval.
BibRef
Letscher, D.[David],
Fritts, J.E.[Jason E.],
Image Segmentation Using Topological Persistence,
CAIP07(587-595).
Springer DOI Reference
0708
BibRef
Zhang, H.[Hui],
Goldman, S.A.[Sally A.],
Perceptual Information of Images and the Bias in Homogeneity-based
Segmentation,
PercOrg06(181).
IEEE DOI Reference
0609
BibRef
Hanbury, A.[Allan],
How Do Superpixels Affect Image Segmentation?,
CIARP08(178-186).
Springer DOI Reference
0809
BibRef
Bagon, S.[Shai],
Boiman, O.[Oren],
Irani, M.[Michal],
What Is a Good Image Segment? A Unified Approach to Segment Extraction,
ECCV08(IV: 30-44).
Springer DOI Reference
0810
BibRef
Pantofaru, C.[Caroline],
Schmid, C.[Cordelia],
Hebert, M.[Martial],
Object Recognition by Integrating Multiple Image Segmentations,
ECCV08(III: 481-494).
Springer DOI Reference
0810Combination of segmentations.
BibRef
Goldmann, L.[Lutz],
Adamek, T.[Tomasz],
Vajda, P.[Peter],
Karaman, M.[Mustafa],
Mörzinger, R.[Roland],
Galmar, E.[Eric],
Sikora, T.[Thomas],
O'Connor, N.E.[Noel E.],
Thien, H.M.[Ha-Minh],
Ebrahimi, T.[Touradj],
Schallauer, P.[Peter],
Huet, B.[Benoit],
Towards Fully Automatic Image Segmentation Evaluation,
ACIVS08(xx-yy).
Springer DOI Reference
0810
BibRef
Haja, A.[Andreas],
Abraham, S.[Steffen],
Jähne, B.[Bernd],
A Comparison of Region Detectors for Tracking,
DAGM08(xx-yy).
Springer DOI Reference
0806
BibRef
Wattuya, P.[Pakaket],
Jiang, X.Y.[Xiao-Yi],
Ensemble Combination for Solving the Parameter Selection Problem in
Image Segmentation,
SSPR08(392-401).
Springer DOI Reference
0812
BibRef
Wattuya, P.[Pakaket],
Jiang, X.Y.[Xiao-Yi],
Rothaus, K.[Kai],
Combination of Multiple Segmentations by a Random Walker Approach,
DAGM08(xx-yy).
Springer DOI Reference
0806
BibRef
Al-Muhairi, H.,
Fleury, M.,
Clark, A.F.,
A computationally efficient evaluation environment for image
segmentation,
ICMV07(129-134).
IEEE DOI Reference
0712
BibRef
Maška, M.[Martin],
Hubený, J.[Jan],
Svoboda, D.[David],
Kozubek, M.[Michal],
A Comparison of Fast Level Set-Like Algorithms for Image Segmentation
in Fluorescence Microscopy,
ISVC07(II: 571-581).
Springer DOI Reference
0711
BibRef
Cárdenes, R.[Rubén],
Bach, M.[Meritxell],
Chi, Y.[Ying],
Marras, I.[Ioannis],
de Luis, R.[Rodrigo],
Anderson, M.[Mats],
Cashman, P.[Peter],
Bultelle, M.[Matthieu],
Multimodal Evaluation for Medical Image Segmentation,
CAIP07(229-236).
Springer DOI Reference
0708
BibRef
Hafiane, A.[Adel],
Chabrier, S.[Sébastien],
Rosenberger, C.[Christophe],
Laurent, H.[Hélène],
A New Supervised Evaluation Criterion for Region Based Segmentation
Methods,
ACIVS07(439-448).
Springer DOI Reference
0708
BibRef
Rosenberger, C.[Christopher],
Adaptative evaluation of image segmentation results,
ICPR06(II: 399-402).
WWW Version.
0609
BibRef
Mashtalir, V.,
Mikhnova, E.,
Shlyakhov, V.,
Yegorova, E.,
A Novel Metric on Partitions for Image Segmentation,
AVSBS06(18-18).
IEEE DOI Reference
0611
BibRef
Neubert, M.,
Herold, H.,
Meinel, G.,
Evaluation of remote sensing image segmentation quality:
Further results and concepts,
OBIA06(xx-yy).
PDF Version.
0607
BibRef
Charles, J.J.,
Kuncheva, L.I.,
Wells, B.,
Lim, I.S.,
An Evaluation Measure of Image Segmentation Based on Object Centres,
ICIAR06(I: 283-294).
Springer DOI Reference
0610
BibRef
Monteiro, F.C.[Fernando C.],
Campilho, A.C.[Aurélio C.],
Performance Evaluation of Image Segmentation,
ICIAR06(I: 248-259).
Springer DOI Reference
0610
BibRef
Monteiro, F.C.[Fernando C.],
Campilho, A.C.[Aurélio C.],
Spectral Methods in Image Segmentation:
A Combined Approach,
IbPRIA05(II:191).
Springer DOI Reference
0509
BibRef
MacDonald, D.,
Lang, J.,
McAllister, M.,
Evaluation of Colour Image Segmentation Hierarchies,
CRV06(27-27).
IEEE DOI Reference
0607
BibRef
Hodge, V.J.[Victoria J.],
Hollier, G.[Garry],
Eakins, J.[John],
Austin, J.[Jim],
Eliciting Perceptual Ground Truth for Image Segmentation,
CIVR06(320-329).
Springer DOI Reference
0607
BibRef
Ge, F.[Feng],
Wang, S.[Song],
Liu, T.C.[Tie-Cheng],
Image-Segmentation Evaluation From the Perspective of Salient Object
Extraction,
CVPR06(I: 1146-1153).
IEEE DOI Reference
0606Compare normalized-cut:
See also Normalized Cuts and Image Segmentation. Efficient Graph:
See also Efficient Graph-Based Image Segmentation. Mean Shift:
See also Mean Shift: A Robust Approach Toward Feature Space Analysis. Level Set:
See also Level Set Methods: Evolving Interfaces in Geometry, Fluid Mechanics, Computer Vision and Materials Science. (and
See also Level-set image segmenation software. )
Ratio-Coutour:
See also Salient Closed Boundary Extraction with Ratio Contour. (and
See also Salient Closed Boundary Extraction with Ratio Contour. ).
BibRef
Jiang, X.Y.[Xiao-Yi],
Marti, C.[Cyril],
Irniger, C.[Christophe],
Bunke, H.[Horst],
Image Segmentation Evaluation by Techniques of Comparing Clusterings,
CIAP05(344-351).
Springer DOI Reference
0509
BibRef
Ndjiki-Nya, P.[Patrick],
Simo, G.[Ghislain],
Wiegand, T.[Thomas],
Evaluation of Color Image Segmentation Algorithms Based on Histogram
Thresholding,
VLBV05(214-222).
Springer DOI Reference
0509
BibRef
Huart, J.,
Bertolino, P.,
Similarity-Based and Perception-Based Image Segmentation,
ICIP05(III: 1148-1151).
IEEE DOI Reference
0512
BibRef
Van Droogenbroeck, M.[Marc],
Barnich, O.[Olivier],
Design of Statistical Measures for the Assessment of Image Segmentation
Schemes,
CAIP05(280).
Springer DOI Reference
0509
BibRef
Vergés-Llahí, J.[Jaume],
Sanfeliu, A.[Alberto],
Evaluation of Distances Between Color Image Segmentations,
IbPRIA05(II:263).
Springer DOI Reference
0509
BibRef
Estrada, F.J.[Francisco J.],
Jepson, A.D.[Allan D.],
Quantitative Evaluation of a Novel Image Segmentation Algorithm,
CVPR05(II: 1132-1139).
IEEE DOI Reference
0507
BibRef
Gelasca, E.D.,
Ebrahimi, T.,
Farias, M.C.Q.,
Carli, M.,
Mitra, S.K.,
Annoyance of spatio-temporal artifacts in segmentation quality
assessment,
ICIP04(I: 345-348).
IEEE DOI Reference
0505
BibRef
Gelasca, E.D.[Elisa Drelie],
Ebrahimi, T.[Touradj],
Farias, M.C.Q.[Mylène C. Q.],
Carli, M.[Marco],
Mitra, S.K.[Sanjit K.],
Towards Perceptually Driven Segmentation Evaluation Metrics,
PercOrg04(52).
IEEE DOI Reference
0502
BibRef
Cavallaro, A.,
Gelasca, E.D.[Elisa Drelie],
Ebrahimi, T.[Touradj],
Objective evaluation of segmentation quality using spatio-temporal
context,
ICIP02(III: 301-304).
IEEE Abstract. IEEE Top Reference.
0210
BibRef
Stauffer, C.[Chris],
Learning a Probabilistic Similarity Function for Segmentation,
PercOrg04(50).
IEEE DOI Reference
0502
BibRef
Unnikrishnan, R.[Ranjith],
Hebert, M.[Martial],
Measures of Similarity,
WACV05(I: 394).
WWW Version.
0502Measures to compare one segmentation to another.
BibRef
Zhou, Q.A.[Qi-Ang],
Ma, L.M.[Li-Min],
Zhou, M.[Min],
Chelberg, D.,
Strong image segmentation from a data-driven perspective: impossible?,
Southwest04(56-60).
IEEE Abstract. IEEE Top Reference.
0411
BibRef
Chabrier, S.,
Emile, B.,
Laurent, H.,
Rosenberger, C.,
Marche, P.,
Unsupervised evaluation of image segmentation application to
multi-spectral images,
ICPR04(I: 576-579).
IEEE DOI Reference
0409
BibRef
Goumeidane, A.B.,
Khamadja, M.,
Belaroussi, B.,
Benoit-Cattin, H.,
Odet, C.,
New discrepancy measures for segmentation evaluation,
ICIP03(II: 411-414).
IEEE Abstract. IEEE Top Reference.
0312
BibRef
Letournel, V.[Valérie],
Sankur, B.[Bülent],
Pradeilles, F.[Frédéric],
Maître, H.[Henri],
Feature Extraction for Quality Assessment of Aerial Image Segmentation,
PCV02(A: 199).
0305
BibRef
Odet, C.,
Belaroussi, B.,
Cattin, H.B.,
Scalable discrepancy measures for segmentation evaluation,
ICIP02(I: 785-788).
IEEE Abstract. IEEE Top Reference.
0210
BibRef
Everingham, M.,
Muller, H.,
Thomas, B.,
Evaluating Image Segmentation Algorithms Using the Pareto Front,
ECCV02(IV: 34 ff.).
HTML Version.
0205Allows for multiple metrics.
BibRef
Freixenet, J.,
Muñoz, X.,
Raba, D.,
Martí, J.,
Cufí, X.,
Yet Another Survey on Image Segmentation:
Region and Boundary Information Integration,
ECCV02(III: 408 ff.).
HTML Version.
0205
Survey, Segmentation. Edge and region integration approaches.
BibRef
Everingham, M.,
Muller, H.,
Thomas, B.,
Evaluating image segmentation algorithms using monotonic hulls in
fitness/cost space,
BMVC01(Session 4: Segmentation).
HTML Version. University of Bristol
0110
BibRef
Wenyin, L.,
Zhai, J.,
Dori, D.,
Long, T.,
A system for performance evaluation of arc segmentation algorithms,
EEMCV01(xx-yy).
0110
BibRef
Southall, B.,
Buxton, B.,
Marchant, J.,
Hague, T.,
On the Performance Characterisation of Image Segmentation Algorithms:
A Case Study,
ECCV00(II: 351-365).
WWW Version.
0003
BibRef
Anderson, H.L.,
Bajcsy, R., and
Mintz, M.,
A Modular Feedback System for Image Segmentation,
UPennGRASP Lab 110 MS-CIS-87-56, 1987.
Uses apriori knowledge about desired scale of segmentation
as well as underlying geometric structure to drive feedback
system. Human-generated segmentations used for comparison.
BibRef
8700
Schachter, B.J.,
A Survey and Evaluation of FLIR
Target Detection/Segmentation Algorithms,
DARPA82(49-57).
Survey, Segmentation.
ATR.
FLIR.
BibRef
8200
Ashjaei, B.[Bahram], and
Soltanian-Zadeh, H.[Hamid],
A Comparative Study of Segmentation Methodologies for
Magnetic Resonance Imaging,
SCIA97(xx-yy)
9705
HTML Version.
BibRef
Earlier:
A comparative analysis of neural network methodologies for segmentation
of magnetic resonance images,
ICIP96(II: 257-260).
IEEE DOI Reference
9610
BibRef
Yang, L.[Luren],
Albregtsen, F.[Fritz],
Lønnestad, T.[Tor],
Grøttum, P.[Per],
A supervised approach to the evaluation of image segmentation methods,
CAIP95(759-765).
Springer DOI Reference
9509
BibRef
Huang, Q.[Qian],
Dom, B.,
Quantitative methods of evaluating image segmentation,
ICIP95(III: 53-56).
IEEE DOI Reference
9510
BibRef
de Graaf, C.N.,
Koster, A.S.E.,
Vincken, K.L.,
Viergever, M.A.,
Task-directed evaluation of image segmentation methods,
ICPR92(III:219-222).
IEEE DOI Reference
9208
BibRef
Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Global - Threshold Based Segmentation Techniques .