8.3.7 Histogram Analysis for Threshold Selection and Segmentation

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

Frei, W.,
Image Enhancement by Histogram Hyperbolization,
CGIP(6), No. 3, June 1977, pp. 286-294.
WWW Version. 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 Version. 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 Version. 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 Version. 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 Version. 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 Version. 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 Version. 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. 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 Version. 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 Version. 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 Version. 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 Version. 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 Version. 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 Version. 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 Version. 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 Version. 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 Version. 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 Version. BibRef 8709

Touzani, A., and Postaire, J.G.,
Mode Detection by Relaxation,
PAMI(10), No. 6, November 1988, pp. 970-978.
IEEE Abstract. IEEE Top Reference.
WWW Version. 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 Version. 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 Version. 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 Version. 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 Version. BibRef 8806

Chochia, P.A.,
Image Enhancement Using Sliding Histograms,
CVGIP(44), No. 2, November 1988, pp. 211-229.
WWW Version. 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. 9609Find 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 Version. 9607Attempts 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.
WWW Version. BibRef 9407

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.
WWW Version. 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.
HTML Version. 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 BibRef

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 Version. 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 Version. 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. IEEE Top Reference. 0210Compare 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,
PRL(24), No. 9-10, June 2003, pp. 1361-1373.
WWW Version. 0304TASOM: Time Adaptive Self-Organizing Map. 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.
WWW Version. 0210 BibRef

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 may work or IEEE-CS DOI may work. 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 Version. 0201 BibRef

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.
WWW Version. 0405 BibRef

Hoppe, A., Baradez, M.O.,
Thresholding based on linear diffusion for feature segmentation,
BMVC03(xx-yy).
HTML Version. 0409 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.
WWW Version. 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.
WWW Version. 0611Histogram; Intensity contrast; Small object segmentation; 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 Version. 0611Nonparametric 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 may work or IEEE-CS DOI may work. 0701 BibRef
Earlier:
Color Image Segmentation Using Acceptable Histogram Segmentation,
IbPRIA05(II:239).
WWW Version. 0509Applied 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 may work or IEEE-CS DOI may work. 0706 BibRef

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 may work or IEEE-CS DOI may work. 0709 BibRef

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 Version. 0711Image segmentation; Otsu method; Gaussian curve fitting; Multiobjective optimization; Simulated annealing See also Threshold Selection Method from Grey-Level Histograms, A. BibRef

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 Version. 0711Thresholding; 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.
WWW Version. 0804 BibRef

Chan, T.[Tony], Esedoglu, S.[Selim], Ni, K.Y.[Kang-Yu],
Histogram Based Segmentation Using Wasserstein Distances,
SSVM07(697-708).
WWW Version. 0705 BibRef

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

Pardo, A.[Alvaro],
Pixel-Wise Histograms for Visual Segment Description and Applications,
CIARP06(873-882).
WWW Version. 0611 BibRef

Schroff, F., Criminisi, A., Zisserman, A.,
Object Class Segmentation using Random Forests,
BMVC08(xx-yy).
PDF Version. 0809 BibRef
Earlier:
Single-Histogram Class Models for Image Segmentation,
ICCVGIP06(82-93).
WWW Version. 0612 BibRef

Martinez-de Dios, J.R., Ollero, A.,
A Multiresolution Threshold Selection Method Based on Training,
ICIAR04(I: 90-97).
WWW Version. 0409 BibRef

Sankowski, D.[Dominik], Mosorov, V.[Volodymyr],
Thresholding Image Segmentation Based on the Volume Analysis of Spatial Regions,
CAIP01(620).
HTML Version. 0210 BibRef

Gibson, S., Harvey, R.,
Analysing and simplifying histograms using scale-trees,
CIAP01(84-89).
IEEE Top Reference. 0210 BibRef

Ińesta, J.M.[José M.], Sanz, P.J.[Pedro J.], del Pobil, Á.P.[Ángel P.],
An automatic transformation from bimodal to pseudo-binary images,
CIAP97(I: 231-238).
WWW Version. 9709 BibRef

Mlsna, P.A., Zhang, Q., Rodriguez, J.J.,
3-D Histogram Modification of Color Images,
ICIP96(III: 1015-1018).
IEEE DOI may work or IEEE-CS DOI may work. BibRef 9600

Mlsna, P.A., Rodriguez, J.J.,
Explosion of multidimensional image histograms,
ICIP94(III: 958-962).
IEEE DOI may work or IEEE-CS DOI may work. 9411 BibRef

Dingle, A.A.[Alison A.], Morrison, M.W.[Mark W.],
Unsupervised Image Segmentation Based on the Comparison of Local and Regional Histograms,
ICIP96(III: 959-962).
IEEE DOI may work or IEEE-CS DOI may work. BibRef 9600

Luchowski, L.[Leszek],
A new method to threshold images of flat binary scenes under uneven lighting,
CAIP95(594-599).
WWW Version. 9509 BibRef

Vossepoel, A.M., Stoel, B.C., Meershoek, A.P.,
Adaptive Histogram Equalization Using Variable Regions,
ICPR88(I: 351-353).
IEEE DOI may work or IEEE-CS DOI may work.
IEEE Top Reference. BibRef 8800

Bracho, R.[Rafael], and Sanderson, A.C.,
Segmentation of Images Based on Intensity Gradient Information,
CVPR85(341-347). Schlumberger Palo Alto Research and CMU. Shaded regions are extracted along with an indication of the surface which could generate them. BibRef 8500

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Fuzzy Threshold Segmentation .