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.,
Histogram Modification Techniques,
CGIP(4), No. 3, September 1975, pp. 209-224.
WWW Link. BibRef 7509

Frei, W.,
Image Enhancement by Histogram Hyperbolization,
CGIP(6), No. 3, June 1977, pp. 286-294.
WWW Link. 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.
WWW Link. 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.S., and Jung, S.M.,
A New Image Segmentation Technique Based on Partition Mode Test,
PR(16), No. 5, 1983, pp. 469-480.
WWW Link. 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.,
The Principles and Methods of Histogram Modification Adapted for Visual Perception,
CVGIP(26), No. 1, April 1984, pp. 107-117.
WWW Link. BibRef 8404

Kautsky, J., Nichols, N.K., Jupp, D.L.B.,
Smoothed Histogram Modification for Image Processing,
CVGIP(26), No. 3, June 1984, pp. 271-291.
WWW Link. 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.,
The Shape of SAR Histograms,
CVGIP(43), No. 3, September 1988, pp. 281-293.
WWW Link. BibRef 8809

Lee, S.U., Chung, S.Y., and Park, R.H.,
A Comparative Performance Study of Several Global Thresholding Techniques for Segmentation,
CVGIP(52), No. 2, November 1990, pp. 171-190.
WWW Link. 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.
WWW Link. BibRef 9210

Rosenfeld, A., and de la Torre, P.,
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.
WWW Link. 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.
WWW Link. 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.
WWW Link. 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.
WWW Link. 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., Wilkins, C., Yeager, J.,
Threshold Selection Using Renyis Entropy,
PR(30), No. 1, January 1997, pp. 71-84.
WWW Link. 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.
WWW Link. 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.
WWW Link. Image segmentation; Thresholding; Tsallis-Havrda-Charvát entropy 0604
BibRef

Lim, Y.W., and Lee, S.U.,
On the Color Image Segmentation Algorithm Based on the Thresholding and the Fuzzy C-Means Techniques,
PR(23), No. 9, 1990, pp. 935-952.
WWW Link. 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., Amburn, E.P., Austin, J.D., Cromartie, R., Geselowitz, A., Greer, T., ter Haar Romeny, B.M., Zimmerman, J.B., Zuiderveld, K.,
Adaptive Histogram Equalization and Its Variations,
CVGIP(39), No. 3, September 1987, pp. 355-368.
WWW Link. 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.,
A Peak Detection Algorithm and Its Application to Histogram-Based Image Data Reduction,
CVGIP(49), No. 1, January 1990, pp. 36-51.
WWW Link. 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., Shalev, S.,
A Robust Algorithm for Contrast Enhancement by Local Histogram Modification,
IVC(7), No. 3, August 1989, pp. 205-209.
WWW Link. BibRef 8908

O'Gorman, L.,
A Note on Histogram Equalization for Optimal Intensity Range Utilization,
CVGIP(41), No. 2, February 1988, pp. 229-232.
WWW Link. 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.
WWW Link. BibRef 8806

Chochia, P.A.,
Image Enhancement Using Sliding Histograms,
CVGIP(44), No. 2, November 1988, pp. 211-229.
WWW Link. 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,
GMIP(55), No. 6, November 1993, pp. 532-yy. BibRef 9311

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.,
Parallel Entropic Auto-Thresholding,
IVC(14), No. 4, May 1996, pp. 247-263.
WWW Link. 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.,
An Alternative Algorithm for Adaptive Histogram Equalization,
GMIP(58), No. 2, March 1996, pp. 180-185. BibRef 9603

Yang, C.W., Chung, P.C., Chang, C.,
Hierarchical Fast 2-Dimensional Entropic Thresholding Algorithm Using a Histogram Pyramid,
OptEng(35), No. 11, November 1996, pp. 3227-3241. 9612
BibRef

Chen, W.T., Wen, C.H., Yang, C.W.,
A Fast 2-Dimensional Entropic Thresholding Algorithm,
PR(27), No. 7, July 1994, pp. 885-893.
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Jansen, R.C., Reinink, K., van der Heijden, G.W.A.M.,
Analysis of Gray Level Histograms by Using Statistical Methods for Mixtures of Distributions,
PRL(14), 1993, pp. 585-590. BibRef 9300

Davies, E.R.,
Lateral Histograms for Efficient Object Location: Speed Versus Ambiguity,
PRL(6), 1987, pp. 189-198. BibRef 8700

Davies, E.R.,
A Sampling Approach to Ultra-fast Object Location,
RealTimeImg(7), No. 4, August 2001, pp. 339-355.
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,
JEI(6), No. 3, July 1997, pp. 286-293. 9807
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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.
WWW Link. 0111
See also Image segmentation by relaxation using constraint satisfaction neural network. BibRef

Bonnet, N., Cutrona, J., Herbin, M.,
A 'no-threshold' histogram-based image segmentation method,
PR(35), No. 10, October 2002, pp. 2319-2322.
WWW Link. 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

Shah-Hosseini, H.[Hamed], Safabakhsh, R.[Reza],
A TASOM-based algorithm for active contour modeling,
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A new active contour model based on the Conscience, Archiving and Mean-Movement mechanisms and the SOM,
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Elsevier DOI 1108
Active contour model; Self-organizing map; Conscience; Archiving; Mean-movement; Concavity extraction; CAMSOM BibRef

Wang, Q.[Qing], Chi, Z.[Zheru], Zhao, R.C.[Rong-Chun],
Image Thresholding by Maximizing the Index of Nonfuzziness of the 2-D Grayscale Histogram,
CVIU(85), No. 2, February 2002, pp. 100-116.
DOI Link 0210
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Tobias, O.J., Seara, R.[Rui],
Image segmentation by histogram thresholding using fuzzy sets,
IP(11), No. 12, December 2002, pp. 1457-1465.
IEEE DOI 0301
BibRef

Cheng, H.D., Jiang, X.H., Wang, J.L.[Jing-Li],
Color image segmentation based on homogram thresholding and region merging,
PR(35), No. 2, February 2002, pp. 373-393.
WWW Link. 0201
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Baradez, M.O., McGuckin, C.P., Forraz, N., Pettengell, R., Hoppe, A.,
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Hoppe, A., Baradez, M.O.,
Thresholding based on linear diffusion for feature segmentation,
BMVC03(xx-yy).
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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,
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WWW Link. BibRef 0410
And: US_Patent7,106,900, Sep 12, 2006
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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.
WWW Link. Image thresholding; Clustering; Inter-class variance; Intra-class variance 0606
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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.
WWW Link. 0611
Histogram; Intensity contrast; Small object segmentation; Prior knowledge BibRef

Hu, Q.M.[Qing-Mao], Luo, S.[Suhuai], Qiao, Y.[Yu], Qian, G.[Guoyu],
Supervised grayscale thresholding based on transition regions,
IVC(26), No. 12, 1 December 2008, pp. 1677-1684.
WWW Link. 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.
WWW Link. 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. 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,
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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.
WWW Link. 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.
WWW Link. 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
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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.[Wenjia], Dou, L.[Lihua], 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
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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
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Earlier:
Top-down color attention for object recognition,
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IEEE DOI 0909
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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
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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
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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
BibRef

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
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CAIP11(I: 76-83).
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Multiresolution Histogram Analysis for Color Reduction,
CIARP10(22-29).
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Color Quantization by Multiresolution Analysis,
CAIP09(525-532).
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ICIAR08(xx-yy).
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Earlier:
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CAIP01(620).
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ICPR88(I: 351-353).
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Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Fuzzy Threshold Segmentation .


Last update:Jul 15, 2017 at 20:56:55