8.3.7 Histogram Analysis for Threshold Selection and Segmentation

Chapter Contents (Back)
Threshold Selection. Segmentation, Thresholds. Segmentation, Histogram. Histogram Analysis. These tend to assume that the thresholds can be performed all at once, thus are doing more work than is really necessary.

Hummel, R.A.[Robert A.],
Histogram Modification Techniques,
CGIP(4), No. 3, September 1975, pp. 209-224.
Elsevier DOI Analysis of transformations. BibRef 7509

Frei, W.[Werner],
Image Enhancement by Histogram Hyperbolization,
CGIP(6), No. 3, June 1977, pp. 286-294.
Elsevier DOI Contrast enhancement. BibRef 7706

Blumenthal, A.F., Davis, L.S., Rosenfeld, A.,
Detecting Natural 'Plateaus' in One-Dimensional Patterns,
TC(26), 1977, pp. 178-179. BibRef 7700

Leboucher, G., Lowitz, G.E.,
What a Histogram Can Really Tell the Classifier,
PR(10), No. 5-6, 1978, pp. 351-357.
Elsevier DOI
See also What the Fourier Transform Can Really Bring to Clustering. BibRef 7800

Nahin, P.J.,
A Simplified Derivation of Frei's Histogram Hyperbolization for Image Enhancement,
PAMI(1), No. 4, October 1979, 414-415.
See also Image Enhancement by Histogram Hyperbolization. BibRef 7910

Ridler, T.W., and Calvard, S.,
Picture Thresholding Using an Iterative Selection Method,
SMC(8), No. 8, August 1978, pp. 629-632. Segmentation, Binarization. Guess the object and background level, choose a threshold, update the guess and the threshold. For bi-modal histograms, to find a threshold between the means. BibRef 7808

Suk, M.[Min_Soo], Chung, S.M.[Soon-Myoung],
A New Image Segmentation Technique Based on Partition Mode Test,
PR(16), No. 5, 1983, pp. 469-480.
Elsevier DOI Can be used for finding multiple motions. BibRef 8300

Rix, H.,
Separation of Equal Shape Overlapping Peaks,
SP(5), 1983, pp. 97-103. BibRef 8300

Ku, F.N.[Fu-Nian],
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CVGIP(26), No. 1, April 1984, pp. 107-117.
Elsevier DOI BibRef 8404

Kautsky, J.[Jaroslav], Nichols, N.K.[Nancy K.], Jupp, D.L.B.[David L.B.],
Smoothed Histogram Modification for Image Processing,
CVGIP(26), No. 3, June 1984, pp. 271-291.
Elsevier DOI BibRef 8406

Jain, R., and Chlamtac, I.,
The P(2) Algorithm for Dynamic Calculation of Quantiles and Histograms without Storing Observations,
CACM(28), No. 10, October 1985, pp. 1076-1085. BibRef 8510

Zito, R.R.[Richard R.],
The Shape of SAR Histograms,
CVGIP(43), No. 3, September 1988, pp. 281-293.
Elsevier DOI Allow the mode of the Rayleigh distribution to possess a distribution of values all its own. BibRef 8809

Lee, S.U.[Sang Uk], Chung, S.Y.[Seok Yoon], Park, R.H.[Rae Hong],
A Comparative Performance Study of Several Global Thresholding Techniques for Segmentation,
CVGIP(52), No. 2, November 1990, pp. 171-190.
Elsevier DOI Evaluation, Segmentation. Segmentation, Evaluation. Thresholds, Evaluation. Compares 5 different techniques (
See also Minimum Error Thresholding.
See also Threshold Selection Method from Grey-Level Histograms, A.
See also New Method for Gray-Level Picture Thresholding Using the Entropy of the Histogram, A.
See also Moment-Preserving Thresholding: A New Approach. and
See also Threshold Selection Using Quadtrees. ). The first two were rated best (Simple image statistic and Between class variance). BibRef 9011

Rosenfeld, A., and Davis, L.S.,
Iterative Histogram Modification,
SMC(8), No. 4, 1978, pp. 300-302. BibRef 7800

Peleg, S.,
Iterative Histogram Modification,
SMC(8), No. 7, 1978, pp. 555-556. BibRef 7800

Otsu, N.,
A Threshold Selection Method from Grey-Level Histograms,
SMC(9), No. 1, January 1979, pp. 62-66. A Variance measure for threshold selection. Compared in:
See also Comparative Performance Study of Several Global Thresholding Techniques for Segmentation, A. Analysis in:
See also Comment on Using the Uniformity Measure for Performance-Measure in Image Segmentation. Code:
See also C++ Implementation of Otsu's Image Segmentation Method, A. BibRef 7901

Kurita, T., Otsu, N., and Abdelmalek, N.,
Maximum Likelihood Thresholding Based on Population Mixture Models,
PR(25), No. 10, October 1992, pp. 1231-1240.
Elsevier DOI BibRef 9210

Rosenfeld, A., and de la Torre, F.[Fernando],
Histogram Concavity Analysis as an Aid in Threshold Selection,
SMC(13), No. 3, March 1983, pp. 231-235. BibRef 8303

Boukharouba, S., Rebordao, J.M., and Wendel, P.L.,
An Amplitude Segmentation Method Based on the Distribution Function of an Image,
CVGIP(29), No. 1, January 1985, pp. 47-59.
Elsevier DOI Use the curvature of the cumulative histogram for determining the place to perform the threshold. Results are unclear, since they are using it for image compression or coding rather than standard segmentation. Further derivation:
See also Peak Detection Algorithm and Its Application to Histogram-Based Image Data Reduction, A. BibRef 8501

Wang, S.[Shyuan], and Haralick, R.M.[Robert M.],
Automatic Multithreshold Selection,
CVGIP(25), No. 1, January 1984, pp. 46-67.
Elsevier DOI A recursive segmentation technique that looks at edge pixel values separated by those on the "bright" and "dark" side of the edge. BibRef 8401

Wu, A.Y., Hong, T.H., and Rosenfeld, A.,
Threshold Selection Using Quadtrees,
PAMI(4), No. 1, January 1982, pp. 90-94. Segmentation, Multi-Level. Histogram based thresholds using the quadtree representation to eliminate small features. Compared in :
See also Comparative Performance Study of Several Global Thresholding Techniques for Segmentation, A. BibRef 8201

Weszka, J.S., Nagel, R.N., and Rosenfeld, A.,
A Threshold Selection Technique,
TC(23), 1974, pp. 1322-1326. BibRef 7400
Earlier:
A Technique for Facilitating Threshold Selection for Object Extraction from Digital Pictures,
UMDTR, 1973. BibRef

Weszka, J.S., and Rosenfeld, A.,
Histogram Modification for Threshold Selection,
SMC(9), No. 1, January 1979, pp. 38-52. BibRef 7901

Weszka, J.S., and Rosenfeld, A.,
Threshold Evaluation Techniques,
SMC(8), 1978, pp. 622-629. Thresholds, Evaluation. BibRef 7800

Pal, S.K., and Pal, N.R.,
Segmentation Based on Measures of Contrast, Homogeneity, and Region Size,
SMC(17), No. 5, Sept/October 1987, pp. 857-868. It also includes some region merging. BibRef 8710

Murthy, C.A., Pal, S.K.,
Histogram Thresholding by Minimizing Graylevel Fuzziness,
IS(60), 1992, pp. 107-135. BibRef 9200

Sahasrabudhe, S.C., Das Gupta, K.S.,
A Valley-Seeking Threshold Selection Technique,
CVIP92(55-65). BibRef 9200

Pal, S.K., Das Gupta, A.,
Spectral Fuzzy Sets and Soft Thresholding,
IS(65), 1992, pp. 65-97. BibRef 9200

Kapur, J.N., Sahoo, P.K., and Wong, A.K.C.,
A New Method for Gray-Level Picture Thresholding Using the Entropy of the Histogram,
CVGIP(29), No. 3, 1985, pp. 273-285.
Elsevier DOI Histogram based threshold selection of a single threshold to binarize the image based on the entropy measure. Bi-modal histograms. Interesting results, not clear what it means for region segmentation. Has a set of references of threshold selection methods. The extension to mulit-modal has efficiency problems. (
See also Parallel Entropic Auto-Thresholding. ) Compared in :
See also Comparative Performance Study of Several Global Thresholding Techniques for Segmentation, A. BibRef 8500

Kapur, J.N.,
Application of entropic measures of stochastic dependence in pattern recognition,
PR(19), No. 6, 1986, pp. 473-476.
Elsevier DOI 0309
BibRef

Wong, A.K.C., and Sahoo, P.K.,
A Gray-Level Threshold Selection Method Based on Maximum Entropy Principle,
SMC(19), No. 4, July 1989, pp. 866-871. BibRef 8907

Sahoo, P.K.[Prasanna K.], Wilkins, C.[Carrye], Yeager, J.[Jerry],
Threshold Selection Using Renyis Entropy,
PR(30), No. 1, January 1997, pp. 71-84.
Elsevier DOI 9702
BibRef

Sahoo, P.K.[Prasanna K.], Arora, G.[Gurdial],
A thresholding method based on two-dimensional Renyi's entropy,
PR(37), No. 6, June 2004, pp. 1149-1161.
Elsevier DOI 0405
BibRef

Sahoo, P.K.[Prasanna K.], Arora, G.[Gurdial],
Image thresholding using two-dimensional Tsallis-Havrda-Charvát entropy,
PRL(27), No. 6, 15 April 2006, pp. 520-528.
Elsevier DOI Image segmentation; Thresholding; Tsallis-Havrda-Charvát entropy 0604
BibRef

Borjigin, S.[Surina], Sahoo, P.K.[Prasanna K.],
Color image segmentation based on multi-level Tsallis-Havrda-Charvát entropy and 2D histogram using PSO algorithms,
PR(92), 2019, pp. 107-118.
Elsevier DOI 1905
Color image segmentation, Multi-level thresholding, Two-dimensional histogram, Tsallis-Havrda-Charvát entropy, PSO BibRef

Lim, Y.W.[Young Won], Lee, S.U.[Sang Uk],
On the Color Image Segmentation Algorithm Based on the Thresholding and the Fuzzy C-Means Techniques,
PR(23), No. 9, 1990, pp. 935-952.
Elsevier DOI Hierarchical segmentation using a scale space filter. BibRef 9000

Tsai, W.H.,
Moment-Preserving Thresholding: A New Approach,
CVGIP(29), No. 3, March 1985, pp. 377-393. Another threshold selection method based on histogram analysis, the moments are preserved in the thresholded image. Compared in :
See also Comparative Performance Study of Several Global Thresholding Techniques for Segmentation, A.
See also Moment-Preserving Sharpening: A New Approach to Digital Picture Deblurring. BibRef 8503

Carlotto, M.J.[Mark J.],
Histogram Analysis Using A Scale Space Approach,
PAMI(9), No. 1, January 1987, pp. 121-129. BibRef 8701
Earlier: CVPR85(334-340). Scale Space. The Analytic Sciences Corp. Approximate the histogram by a sum of gaussian distributions. This gives better threshold choices. The modeling is done using different size gaussian smoothing functions. BibRef

Pizer, S.M.[Stephen M.], Amburn, E.P.[E. Philip], Austin, J.D.[John D.], Cromartie, R.[Robert], Geselowitz, A.[Ari], Greer, T.[Trey], ter Haar Romeny, B.M.[Bart M.], Zimmerman, J.B.[John B.], Zuiderveld, K.[Karel],
Adaptive Histogram Equalization and Its Variations,
CVGIP(39), No. 3, September 1987, pp. 355-368.
Elsevier DOI BibRef 8709

Touzani, A., and Postaire, J.G.,
Mode Detection by Relaxation,
PAMI(10), No. 6, November 1988, pp. 970-978.
IEEE DOI BibRef 8811

Sezan, M.I.[M. Ibrahim],
A Peak Detection Algorithm and Its Application to Histogram-Based Image Data Reduction,
CVGIP(49), No. 1, January 1990, pp. 36-51.
Elsevier DOI Find the peaks and use them to quantize the image for data reduction and reconstruction. Derived from
See also Amplitude Segmentation Method Based on the Distribution Function of an Image, An. using a simpler filter on the histogram. BibRef 9001

Jolion, J.M.[Jean-Michel], and Rosenfeld, A.[Azriel],
Coarse-Fine Bimodality Analysis of Circular Histogram,
PRL(10), 1989, pp. 201-207. Pyramid Technique. BibRef 8900

Leszczynski, K.W.[Konrad W.], Shalev, S.[Shlomo],
A Robust Algorithm for Contrast Enhancement by Local Histogram Modification,
IVC(7), No. 3, August 1989, pp. 205-209.
Elsevier DOI Moving Histogram Equalization. BibRef 8908

O'Gorman, L.[Lawrence],
A Note on Histogram Equalization for Optimal Intensity Range Utilization,
CVGIP(41), No. 2, February 1988, pp. 229-232.
Elsevier DOI HE does not optimally use the intensity range. BibRef 8802

McCallum, A.J., Bowman, C.C., Daniels, P.A., Batchelor, B.G.,
A Histogram Modification Unit for Real-Time Image Enhancement,
CVGIP(42), No. 3, June 1988, pp. 387-398.
Elsevier DOI For TV frames that don't change much between frames. BibRef 8806

Chochia, P.A.[Pavel A.],
Image Enhancement Using Sliding Histograms,
CVGIP(44), No. 2, November 1988, pp. 211-229.
Elsevier DOI BibRef 8811

Brunelli, R.,
Optimal Histogram Partitioning Using a Simulated Annealing Technique,
PRL(13), 1992, pp. 581-586. Relaxation algorithm to select appropriate thresholds. BibRef 9200

Tsai, D.M., and Chen, Y.H.,
A Fast Histogram-Clustering Approach for Multi-Level Thresholding,
PRL(13), 1992, pp. 245-252. Number of peaks must be known or spurious thresholds will be selected. BibRef 9200

Tsai, D.M.,
A Fast Thresholding Selection Procedure for Multimodal and Unimodal Histograms,
PRL(16), No. 6, June 1995, pp. 653-666. Segmentation, Unimodal. BibRef 9506

Gauch, J.M.[John M.],
Investigations of Image Contrast Space Defined by Variations on Histogram Equalization,
GMIP(54), No. 4, July 1992, pp. 269-280. BibRef 9207

Glasbey, C.A.,
An Analysis of Histogram-Based Thresholding Algorithms,
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Hayat, L., Fleury, M., Clark, A.F.,
Candidate Functions For A Parallel Multilevel Thresholding Technique,
GMIP(58), No. 4, July 1996, pp. 360-381. 9609
Find modes in a gray-level histogram. Compares most standard techniques that can be parallelized. BibRef

Fleury, M., Hayat, L., Clark, A.F.,
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Elsevier DOI 9607
Attempts to extend
See also New Method for Gray-Level Picture Thresholding Using the Entropy of the Histogram, A. to multiple modes. Peaks are selected by simple clipping approach. BibRef

Caglioti, V., Maniezzo, V.,
Mode Determination in Noisy Bimodal Images by Histogram Comparison,
PRL(16), No. 12, December 1995, pp. 1237-1248. BibRef 9512

Stark, J.A., Fitzgerald, W.J.,
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Yang, C.W., Chung, P.C., Chang, C.,
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Chen, W.T.[Wen-Tsuen], Wen, C.H.[Chia-Hsien], Yang, C.W.[Chin-Wen],
A Fast 2-Dimensional Entropic Thresholding Algorithm,
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Jansen, R.C., Reinink, K., van der Heijden, G.W.A.M.,
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Davies, E.R.,
Lateral Histograms for Efficient Object Location: Speed Versus Ambiguity,
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Davies, E.R.,
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DOI Link 0110

See also skimming technique for fast accurate edge detection, A. BibRef

Guo, R., Pandit, S.M.,
Automatic Threshold Selection Based on Histogram Modes and a Discriminant Criterion,
MVA(10), No. 5-6, April 1998, pp. 331-338.
Springer DOI 9805
BibRef

Li, C.H., Tam, P.K.S.,
Modular Expert Network Approach to Histogram Thresholding,
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Kurugollu, F.[Fatih], Sankur, B.[Bülent], Harmanc, A.E.[A. Emre],
Color image segmentation using histogram multithresholding and fusion,
IVC(19), No. 13, November 2001, pp. 915-928.
Elsevier DOI 0111

See also Image segmentation by relaxation using constraint satisfaction neural network. BibRef

Bonnet, N., Cutrona, J., Herbin, M.,
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Elsevier DOI 0206
BibRef

Shah-Hosseini, H.[Hamed], Safabakhsh, R.[Reza],
Automatic Multilevel Thresholding for Image Segmentation by the Growing Time Adaptive Self-Organizing Map,
PAMI(24), No. 10, October 2002, pp. 1388-1393.
IEEE Abstract. 0210
Compare to
See also New Approach For Multilevel Threshold Selection, A.
See also New Method for Gray-Level Picture Thresholding Using the Entropy of the Histogram, A. and
See also Image Segmentation by a Parallel, Non-Parametric Histogram Based Clustering Algorithm. BibRef

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Wang, Q.[Qing], Chi, Z.[Zheru], Zhao, R.C.[Rong-Chun],
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DOI Link 0210
BibRef

Tobias, O.J., Seara, R.[Rui],
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IP(11), No. 12, December 2002, pp. 1457-1465.
IEEE DOI 0301
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Cheng, H.D., Jiang, X.H., Wang, J.L.[Jing-Li],
Color image segmentation based on homogram thresholding and region merging,
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Elsevier DOI 0201
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Baradez, M.O., McGuckin, C.P., Forraz, N., Pettengell, R., Hoppe, A.,
Robust and automated unimodal histogram thresholding and potential applications,
PR(37), No. 6, June 2004, pp. 1131-1148.
Elsevier DOI 0405
BibRef

Hoppe, A., Baradez, M.O.,
Thresholding based on linear diffusion for feature segmentation,
BMVC03(xx-yy).
HTML Version. 0409
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Park, S.J.[Soo Jun], Won, C.S.[Chee Sun], Park, D.K.[Dong Kwon], Choi, D.S.[Dong See], Yoo, S.J.[Seong Joon], Kim, H.J.[Hyun Jin],
Method for generating a block-based image histogram,
US_Patent6,807,298, Oct 19, 2004
WWW Link. BibRef 0410
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WWW Link. include color, brightness, and edge components BibRef

Arifin, A.Z.[Agus Zainal], Asano, A.[Akira],
Image segmentation by histogram thresholding using hierarchical cluster analysis,
PRL(27), No. 13, 1 October 2006, pp. 1515-1521.
Elsevier DOI Image thresholding; Clustering; Inter-class variance; Intra-class variance 0606
BibRef

Qiao, Y.[Yu], Hu, Q.M.[Qing-Mao], Qian, G.Y.[Guo-Yu], Luo, S.[Suhuai], Nowinski, W.L.[Wieslaw L.],
Thresholding based on variance and intensity contrast,
PR(40), No. 2, February 2007, pp. 596-608.
Elsevier DOI 0611
Histogram; Intensity contrast; Small object segmentation; Prior knowledge BibRef

Hu, Q.M.[Qing-Mao], Luo, S.[Suhuai], Qiao, Y.[Yu], Qian, G.Y.[Guo-Yu],
Supervised grayscale thresholding based on transition regions,
IVC(26), No. 12, 1 December 2008, pp. 1677-1684.
Elsevier DOI 0810
Grayscale thresholding; Transition region; Supervision; Prior knowledge BibRef

Zhang, C.L.[Chao-Lin], Zhang, X.G.[Xue-Gong], Zhang, M.Q.[Michael Q.], Li, Y.[Yanda],
Neighbor number, valley seeking and clustering,
PRL(28), No. 2, 15 January 2007, pp. 173-180.
Elsevier DOI 0611
Nonparametric density estimation; Neighbor number; Valley seeking; Shape-free clustering; Image segmentation BibRef

Delon, J.[Julie], Desolneux, A.[Agnes], Lisani, J.L.[Jose Luis], Petro, A.B.[Ana Belen],
A Nonparametric Approach for Histogram Segmentation,
IP(16), No. 1, January 2007, pp. 253-261.
IEEE DOI 0701
BibRef
Earlier:
Color Image Segmentation Using Acceptable Histogram Segmentation,
IbPRIA05(II:239).
Springer DOI 0509
Applied to documents. Find small modes in the histogram.
See also Automatic 1D Histogram Segmentation and Application to the Computation of Color Palettes. BibRef

Shortt, A.E., Naughton, T.J., Javidi, B.[Bahram],
Histogram Approaches for Lossy Compression of Digital Holograms of Three-Dimensional Objects,
IP(16), No. 6, June 2007, pp. 1548-1556.
IEEE DOI 0706
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McElhinney, C.P., McDonald, J.B., Castro, A.[Albertina], Frauel, Y.[Yann], Javidi, B.[Bahram], Naughton, T.J.,
Segmentation of three-dimensional objects from background in digital holograms,
IMVIP07(41-46).
IEEE DOI 0709
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Nakib, A., Oulhadj, H., Siarry, P.[Patrick],
Non-supervised image segmentation based on multiobjective optimization,
PRL(29), No. 1, 15 January 2008, pp. 161-172.
Elsevier DOI 0711
Image segmentation; Otsu method; Gaussian curve fitting; Multiobjective optimization; Simulated annealing
See also Threshold Selection Method from Grey-Level Histograms, A. BibRef

Nakib, A., Oulhadj, H., Siarry, P.,
A thresholding method based on two-dimensional fractional differentiation,
IVC(27), No. 9, 3 August 2009, pp. 1343-1357.
Elsevier DOI 0906
Two-dimensional fractional differentiation; Image thresholding; Image segmentation BibRef

Nakib, A., Schulze, Y., Petit, E.,
Image thresholding framework based on two-dimensional digital fractional integration and Legendre moments',
IET-IPR(6), No. 6, 2012, pp. 717-727.
DOI Link 1210
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Hammouche, K.[Kamal], Diaf, M.[Moussa], Siarry, P.[Patrick],
A multilevel automatic thresholding method based on a genetic algorithm for a fast image segmentation,
CVIU(109), No. 2, February 2008, pp. 163-175.
Elsevier DOI 0711
Thresholding; Image segmentation; Genetic algorithm BibRef

Losson, O.[Olivier], Botte-lecocq, C.[Claudine], Macaire, L.[Ludovic],
Fuzzy Mode Enhancement and Detection for Color Image Segmentation,
JIVP(2008), No. 2008, pp. xx-yy.
DOI Link 0804
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Ni, K.Y.[Kang-Yu], Bresson, X.[Xavier], Chan, T.[Tony], Esedoglu, S.[Selim],
Local Histogram Based Segmentation Using the Wasserstein Distance,
IJCV(84), No. 1, August 2009, pp. xx-yy.
Springer DOI 0905
BibRef
Earlier: A3, A4, A1, Only:
Histogram Based Segmentation Using Wasserstein Distances,
SSVM07(697-708).
Springer DOI 0705
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Vieira Lopes, N., Mogadouro do Couto, P.A., Bustince, H., Melo-Pinto, P.,
Automatic Histogram Threshold Using Fuzzy Measures,
IP(19), No. 1, January 2010, pp. 199-204.
IEEE DOI 1001
BibRef

Wang, N.[Na], Li, X.[Xia], Chen, X.H.[Xiao-Hong],
Fast three-dimensional Otsu thresholding with shuffled frog-leaping algorithm,
PRL(31), No. 13, 1 October 2010, pp. 1809-1815.
Elsevier DOI 1003

See also Threshold Selection Method from Grey-Level Histograms, A. Image segmentation; 3-D Otsu thresholding; Shuffled frog-leaping algorithm; Optimization BibRef

Krstinic, D., Skelin, A.K., Slapnicar, I.,
Fast two-step histogram-based image segmentation,
IET-IPR(5), No. 1, February 2011, pp. 63-72.
DOI Link 1103
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Yang, W.J.[Wen-Jia], Dou, L.H.[Li-Hua], Zhan, J.[Juan],
A Multi-histogram Clustering Approach Toward Markov Random Field For Foreground Segmentation,
IJIG(11), No. 1, January 2011, pp. 65-81.
DOI Link 1103
BibRef

Vazquez, E.[Eduard], Baldrich, R.[Ramon], van de Weijer, J.[Joost], Vanrell, M.[Maria],
Describing Reflectances for Color Segmentation Robust to Shadows, Highlights, and Textures,
PAMI(33), No. 1, January 2011, pp. 917-930.
IEEE DOI 1104
Segment single material even with variations from shape, etc. Multilocal creaseness analysis of the histogram which results in a set of ridges representing the material reflectances. BibRef

Khan, F.S.[Fahad Shahbaz], van de Weijer, J.[Joost], Vanrell, M.[Maria],
Modulating Shape Features by Color Attention for Object Recognition,
IJCV(98), No. 1, May 2012, pp. 49-64.
WWW Link. 1204
BibRef
Earlier:
Top-down color attention for object recognition,
ICCV09(979-986).
IEEE DOI 0909
BibRef

Khan, F.S.[Fahad Shahbaz], Anwer, R.M.[Rao Muhammad], van de Weijer, J.[Joost], Bagdanov, A.D.[Andrew D.], Vanrell, M.[Maria], Lopez, A.M.[Antonio M.],
Color attributes for object detection,
CVPR12(3306-3313).
IEEE DOI 1208

See also Learning Color Names for Real-World Applications. BibRef

Khan, F.S.[Fahad Shahbaz], van de Weijer, J.[Joost],
Evaluating the Impact of Color on Texture Recognition,
CAIP13(154-162).
Springer DOI 1308
BibRef

van de Weijer, J.[Joost], Khan, F.S.[Fahad Shahbaz],
Fusing Color and Shape for Bag-of-Words Based Object Recognition,
CCIW13(25-34).
Springer DOI 1304
BibRef

Rojas Vigo, D.A.[David Augusto], Khan, F.S.[Fahad Shahbaz], van de Weijer, J.[Joost], Gevers, T.[Theo],
The Impact of Color on Bag-of-Words Based Object Recognition,
ICPR10(1549-1553).
IEEE DOI 1008
BibRef

Vazquez, E.[Eduard], Baldrich, R.[Ramon], Vazquez, J.[Javier], Vanrell, M.[Maria],
Topological Histogram Reduction Towards Colour Segmentation,
IbPRIA07(I: 55-62).
Springer DOI 0706
BibRef

Xue, J.H.[Jing-Hao], Titterington, D.M.[D. Michael],
Median-based image thresholding,
IVC(29), No. 9, August 2011, pp. 631-637.
Elsevier DOI 1109
Image segmentation; Image thresholding; Laplace distributions; Mean absolute deviation from the median (MAD); Minimum error thresholding (MET); Otsu's method
See also Threshold Selection Method from Grey-Level Histograms, A. BibRef

Fan, J.L.[Jiu-Lun], Lei, B.[Bo],
A modified valley-emphasis method for automatic thresholding,
PRL(33), No. 6, 15 April 2012, pp. 703-708.
Elsevier DOI 1203
Image segmentation; Otsu method; Valley point; Valley-emphasis method BibRef

Chen, Q., Zhao, L., Lu, J., Kuang, G., Wang, N., Jiang, Y.,
Modified two-dimensional Otsu image segmentation algorithm and fast realisation,
IET-IPR(6), No. 4, 2012, pp. 426-433.
DOI Link 1205

See also Threshold Selection Method from Grey-Level Histograms, A. BibRef

Zhang, H.L.[Hai-Li], Chen, Y.M.[Yun-Mei], Shi, J.L.[Jiang-Li],
Nonparametric Image Segmentation Using Rényi's Statistical Dependence Measure,
JMIV(44), No. 3, November 2012, pp. 330-340.
WWW Link. 1209
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Lu, S.J.[Shi-Jian], Tan, C.[Cheston], Lim, J.H.[Joo-Hwee],
Robust and Efficient Saliency Modeling from Image Co-Occurrence Histograms,
PAMI(36), No. 1, 2014, pp. 195-201.
IEEE DOI 1312
BibRef
Earlier: A1, A3, Only:
Saliency Modeling from Image Histograms,
ECCV12(VII: 321-332).
Springer DOI 1210
Computational modeling BibRef

Boulmerka, A.[Aďssa], Allili, M.S.[Mohand Saďd], Ait-Aoudia, S.[Samy],
A generalized multiclass histogram thresholding approach based on mixture modelling,
PR(47), No. 3, 2014, pp. 1330-1348.
Elsevier DOI 1312
Image segmentation BibRef

Sarkar, S., Das, S.,
Multilevel Image Thresholding Based on 2D Histogram and Maximum Tsallis Entropy: A Differential Evolution Approach,
IP(22), No. 12, 2013, pp. 4788-4797.
IEEE DOI 1312
evolutionary computation BibRef

Mukherjee, S., Acton, S.T.[Scott T.],
Region Based Segmentation in Presence of Intensity Inhomogeneity Using Legendre Polynomials,
SPLetters(22), No. 3, March 2015, pp. 298-302.
IEEE DOI 1410
Computational modeling BibRef

Balarini, J.P.[Juan Pablo], Nesmachnow, S.[Sergio],
A C++ Implementation of Otsu's Image Segmentation Method,
IPOL(6), 2016, pp. 155-164.
DOI Link 1608
Code, Segmentation. Code, Otsu Segmentation. Code, Segmentation, C++.
See also Threshold Selection Method from Grey-Level Histograms, A. BibRef

Cavallaro, G.[Gabriele], Falco, N.[Nicola], Mura, M.D.[Mauro Dalla], Benediktsson, J.A.[Jón Atli],
Automatic Attribute Profiles,
IP(26), No. 4, April 2017, pp. 1859-1872.
IEEE DOI 1704
Biomedical imaging BibRef

Cavallaro, G.[Gabriele], Falco, N.[Nicola], Mura, M.D.[Mauro Dalla], Bruzzone, L.[Lorenzo], Benediktsson, J.A.[Jón Atli],
Automatic Threshold Selection for Profiles of Attribute Filters Based on Granulometric Characteristic Functions,
ISMM15(169-181).
Springer DOI 1506
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Ngatchou, A., Bitjoka, L., Mfoumou, E., Boukar, O., Ngatcheu, M., Ngueguim, M.,
Robust and Fast Segmentation Based on Fuzzy Clustering Combined with Unsupervised Histogram Analysis,
IEEE_Int_Sys(32), No. 5, September 2017, pp. 6-13.
IEEE DOI 1710
Clustering algorithms, Histograms, Mathematical model, Partitioning algorithms, Prototypes, artificial intelligence, beans (Phaseolus vulgaris), fuzzy logic, intelligent systems, intensity transformation, unsupervised, histogram, analysis BibRef

Hao, D.[Duo], Li, Q.M.[Qiu-Ming], Li, C.W.[Cheng-Wei],
Histogram-based image segmentation using variational mode decomposition and correlation coefficients,
SIViP(11), No. 8, November 2017, pp. 1411-1418.
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Meng, Y., Hu, Z., Chen, X., Yao, J.,
Subtracted Histogram: Utilizing Mutual Relation Between Features for Thresholding,
GeoRS(56), No. 12, December 2018, pp. 7415-7435.
IEEE DOI 1812
Histograms, Robustness, Feature extraction, Vgetation mapping, Correlation, Entropy, Remote sensing, Automatic thresholding, vegetation detection BibRef

Xing, J.W.[Jiang-Wa], Yang, P.[Pei], Qingge, L.[Letu],
Automatic thresholding using a modified valley emphasis,
IET-IPR(14), No. 3, 28 February 2020, pp. 536-544.
DOI Link 2002
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Yue, X.F.[Xiao-Feng], Zhang, H.B.[Hong-Bo],
A multi-level image thresholding approach using Otsu based on the improved invasive weed optimization algorithm,
SIViP(14), No. 3, April 2020, pp. 575-582.
WWW Link. 2004
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Lisani, J.L.[Jose-Luis], Petro, A.B.[Ana Belén],
Automatic 1D Histogram Segmentation and Application to the Computation of Color Palettes,
IPOL(11), 2021, pp. 76-104.
DOI Link 2104
Code, Segmentation.
See also Nonparametric Approach for Histogram Segmentation, A. BibRef

Guan, J.[Junyi], Li, S.[Sheng], He, X.X.[Xiong-Xiong], Chen, J.J.[Jia-Jia],
Peak-Graph-Based Fast Density Peak Clustering for Image Segmentation,
SPLetters(28), 2021, pp. 897-901.
IEEE DOI 2106
Resource management, Image segmentation, Clustering algorithms, Vegetation, Signal processing algorithms, Image reconstruction, peak-graph BibRef

Li, S.[Shuang], Shan, J.[Jie],
Adaptive Geometric Interval Classifier,
IJGI(11), No. 8, 2022, pp. xx-yy.
DOI Link 2209
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Zhou, W.[Wei], Wang, L.M.[Li-Min], Han, X.M.[Xu-Ming], Li, M.Y.[Ming-Yang],
A novel deviation density peaks clustering algorithm and its applications of medical image segmentation,
IET-IPR(16), No. 14, 2022, pp. 3790-3804.
DOI Link 2212
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Barron, J.T.[Jonathan T.],
A Generalization of Otsu's Method and Minimum Error Thresholding,
ECCV20(V:455-470).
Springer DOI 2011

See also Threshold Selection Method from Grey-Level Histograms, A. BibRef

Tanizaki, K., Hashimoto, N., Inatsu, Y., Hontani, H., Takeuchi, I.,
Computing Valid P-Values for Image Segmentation by Selective Inference,
CVPR20(9550-9559)
IEEE DOI 2008
Image segmentation, Reliability, Testing, Inference algorithms, Data analysis, Histograms BibRef

Shaus, A.[Arie], Turkel, E.[Eli],
Chan-Vese Revisited: Relation to Otsu's Method and a Parameter-Free Non-PDE Solution via Morphological Framework,
ISVC16(I: 203-212).
Springer DOI 1701
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Kiadtikornthaweeyot, W.[Warinthorn], Tatnall, A.R.L.[Adrian R. L.],
Region Of Interest Detection Based On Histogram Segmentation For Satellite Image,
ISPRS16(B7: 249-255).
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Chevallier, E.[Emmanuel], Chevallier, A.[Augustin], Angulo, J.[Jesus],
Computing Histogram of Tensor Images Using Orthogonal Series Density Estimation and Riemannian Metrics,
ICPR14(900-905)
IEEE DOI 1412
Density measurement BibRef

Al Saeed, D.H.[Duaa H.], Bouridane, A.[Ahmed], El Zaart, A.[Ali],
A new image segmentation method based On 3-dimensional entropic thresholding using a 3-dimensional (GLLALE) histogram,
WSSIP14(235-238) 1406
Face BibRef

Martín-Rodríguez, F.[Fernando],
New Tools for Gray Level Histogram Analysis, Applications in Segmentation,
ICIAR13(326-335).
Springer DOI 1307
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Guo, X.[Xin], Zhao, Z.C.[Zhi-Cheng], Cai, A.N.[An-Ni],
Find dominant bins of a histogram by sparse representation,
ICPR12(3038-3041).
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Berger, R.[Raoul], Dubuisson, S.[Severine], Gonzales, C.[Christophe],
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ICIP12(2373-2376).
IEEE DOI 1302
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Dubuisson, S.[Séverine], Gonzales, C.[Christophe],
Min-Space Integral Histogram,
ECCV12(II: 188-201).
Springer DOI 1210
compute histograms BibRef

Catańo, M.A.[Miguel Angel], Climent, J.[Joan],
A New Morphological Measure of Histogram Bimodality,
CIARP12(390-397).
Springer DOI 1209
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Nazareth, V.M., Amulya, K., Manikantan, K.,
Optimal Multilevel Thresholding for Image Segmentation Using Contrast-Limited Adaptive Histogram Equalization and Enhanced Convergence Particle Swarm Optimization,
NCVPRIPG11(207-210).
IEEE DOI 1205
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Ma, L.Y.[Li-Yan], Yu, J.[Jian],
Texture segmentation based on local feature histograms,
ICIP11(3349-3352).
IEEE DOI 1201
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Sthitpattanapongsa, P.[Puthipong], Srinark, T.[Thitiwan],
An Equivalent 3D Otsu's Thresholding Method,
PSIVT11(I: 358-369).
Springer DOI 1111

See also Threshold Selection Method from Grey-Level Histograms, A. BibRef

Kulkarni, M.[Mandar],
Histogram-based foreground object extraction for indoor and outdoor scenes,
ICCVGIP10(148-154).
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Ferone, A.[Alessio], Pal, S.K.[Sankar Kumar], Petrosino, A.[Alfredo],
A Rough-Fuzzy HSV Color Histogram for Image Segmentation,
CIAP11(I: 29-37).
Springer DOI 1109
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Xue, F.[Fei], Zhang, Y.J.[Yu-Jin],
Image Class Segmentation via Conditional Random Field over Weighted Histogram Classifier,
ICIG11(477-481).
IEEE DOI 1109
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Ramella, G.[Giuliana], di Baja, G.S.[Gabriella Sanniti],
Color Histogram-Based Image Segmentation,
CAIP11(I: 76-83).
Springer DOI 1109
BibRef
And:
Multiresolution Histogram Analysis for Color Reduction,
CIARP10(22-29).
Springer DOI 1011
BibRef
Earlier:
Color Quantization by Multiresolution Analysis,
CAIP09(525-532).
Springer DOI 0909
BibRef

Bellens, P.[Pieter], Palaniappan, K.[Kannappan], Badia, R.M.[Rosa M.], Seetharaman, G.[Guna], Labarta, J.[Jesus],
Parallel Implementation of the Integral Histogram,
ACIVS11(586-598).
Springer DOI 1108
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Frias-Velazquez, A.[Andres], Morros, R.[Ramon],
Histogram computation based on image bitwise decomposition,
ICIP09(3269-3272).
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Lin, A.Y.[Ai-Ying], Wu, L.L.[Li-Li], Zheng, B.Z.[Bao-Zhou], Zan, H.Y.[Hong-Ying],
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CISP09(1-4).
IEEE DOI 0910
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Deng, H.G.[Hong-Gui], Wu, R.L.[Rang-Liang], Lai, Z.R.[Zheng-Rong],
Image Segmentation of Drosophila's Compound Eyes via Two-Dimensional Otsu Thresholding on the Basis of AGA,
CISP09(1-5).
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Thomas, G.[Gabriel],
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ICIP08(589-592).
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Brancati, N.[Nadia], Frucci, M.[Maria], Sanniti di Baja, G.[Gabriella],
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ICIAR08(xx-yy).
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Pardo, A.[Alvaro],
Pixel-Wise Histograms for Visual Segment Description and Applications,
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Schroff, F., Criminisi, A., Zisserman, A.,
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Earlier:
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ICCVGIP06(82-93).
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Martinez-de Dios, J.R., Ollero, A.,
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ICIAR04(I: 90-97).
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Thresholding Image Segmentation Based on the Volume Analysis of Spatial Regions,
CAIP01(620).
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Ińesta, J.M.[José M.], Sanz, P.J.[Pedro J.], del Pobil, Á.P.[Ángel P.],
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Mlsna, P.A., Zhang, Q., Rodriguez, J.J.,
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ICIP96(III: 959-962).
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Luchowski, L.[Leszek],
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Vossepoel, A.M., Stoel, B.C., Meershoek, A.P.,
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Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Fuzzy Threshold Segmentation .


Last update:Mar 16, 2024 at 20:36:19