8.3.3 Segmentation by Thresholding, Quantization, or Relaxation

Chapter Contents (Back)
Quantization. Relaxation. Segmentation, Thresholds. Segmentation, Binarization. Segmentation, Relaxation. Adaptive Threshold. Multiple Thresholds.

Conners, R.W., and Harlow, C.A.,
Equal Probability Quantizing and Texture Analysis of Radiographic Images,
CGIP(8), 1978, pp. 447-463. Segmentation, Texture. BibRef 7800

Smith, R.C., Rosenfeld, A.,
Thresholding Using Relaxation,
PAMI(3), No. 5, September 1981, pp. 598-605. See also Shape Segmentation Using Relaxation. BibRef 8109

Richards, J.A., Landgrebe, D.A., and Swain, P.H.,
Supervised Pixel Relaxation Labeling as a Means for Utilizing Ancillary Information in the Classification of Remote Sensing Image Data,
RSE(12), 1982, pp. 463-477. BibRef 8200

Richards, J.A., Landgrebe, D.A., and Swain, P.H.,
Pixel Labeling by Supervised Probabilistic Relaxation,
PAMI(3), No. 2, March 1981, pp. 188-191. BibRef 8103

Richards, J.A., Landgrebe, D.A., and Swain, P.H.,
Overcoming Accuracy Deterioration in Pixel Relaxation Labeling,
ICPR80(61-65). BibRef 8000

Pal, S.K., King, R.A., and Hashim, A.A.,
Automatic Grey Level Thresholding Through Index of Fuzziness and Entropy,
PRL(1), 1983, pp. 141-146. BibRef 8300

Reddi, S.S., Rudin, S.F., and Keshavan, H.R.,
An Optimal Multiple Threshold Scheme for Image Segmentation,
SMC(14), No. 4, July/August 1984, pp. 661-665. Segmentation, Quantization. Iterative technique to choose the optimal threshold values so that the mapping of the image values to the averages of the thresholds results in the minimum error. It is a simple technique that seems to get all there is in one histogram, there are references to other origins for the basic idea. BibRef 8407

Cohen, M.[Martin],
Explicit Derivation and Analysis of an Optimal Multiple Threshold Scheme,
NTRC Report#85-12R, Northrop Research and Technology Center, 1985. This explicitly derives a technique for the See also Optimal Multiple Threshold Scheme for Image Segmentation, An. technique for multiple thresholds. BibRef 8500

Khotanzad, A., and Bouarfa, A.,
Image Segmentation by a Parallel, Non-Parametric Histogram Based Clustering Algorithm,
PR(23), No. 9, 1990, pp. 961-973.
WWW Version. Segmentation, Histogram. Clustering. Use mode analysis of the multi-dimensional histogram, find the clusters. BibRef 9000

Rodriguez, A.A.[Arturo A.], Mitchell, O.R.[O. Robert],
Image Segmentation by Succesive Background Extraction,
PR(24), No. 5, 1991, pp. 409-420.
WWW Version. BibRef 9100

Mitchell, O.R., and Lutton, S.M.,
Segmentation and Classification of Targets in FLIR Imagery,
DARPAN78(59-65). BibRef 7800

Lutton, S.M., and Mitchell, O.R.,
Adaptive Segmentation of Unique Objects,
ICPR80(548-550). BibRef 8000

Ackah-Miezan, A., and Gagalowicz, A.,
Discrete Models for Energy-Minimizing Segmentation,
ICCV93(200-207).
WWW Version. Segment the image and generate an approximation to it (values for the regions). BibRef 9300

Chou, P.B., and Brown, C.M.,
The Theory and Practice of Bayesian Image Labeling,
IJCV(4), No. 3, 1990, pp. 185-210.
WWW Version. Bayes Nets. BibRef 9000
Earlier:
Multimodal Reconstruction and Segmentation with Markov Random Fields and HCF Optimization,
DARPA88(214-221). BibRef
And:
Probabilistic Information Fusion for Multi-Modal Image Segmentation,
IJCAI87(779-782). Segmentation, Histogram. BibRef

Chen, P.B., Brown, C.M.,
Multi-Modal Segmentation Using Markov Random Fields,
DARPA87(663-670). BibRef 8700

Postaire, J.G., Ameziane, M.,
A Pattern Classification Approach to Multilevel Thresholding for Image Segmentation,
CVIP92(307-328). BibRef 9200

Papamarkos, N., Gatos, B.,
A New Approach For Multilevel Threshold Selection,
GMIP(56), No. 5, September 1994, pp. 357-370. BibRef 9409

Papamarkos, N., Strouthopoulos, C., Andreadis, I.,
Multithresholding of color and gray-level images through a neural network technique,
IVC(18), No. 3, February 2000, pp. 213-222.
WWW Version. 0001 See also On estimation of the number of image principal colors and color reduction through self-organized neural networks. BibRef

Tseng, D.C., and Huang, M.Y.,
Automatic Thresholding Based on Human Visual-Perception,
IVC(11), No. 9, November 1993, pp. 539-548.
WWW Version. BibRef 9311

Tseng, D.C., Chang, C.H.,
Color segmentation using perceptual attributes,
ICPR92(III:228-231).
WWW Version. 9208 BibRef

Banerjee, S.[Saibal], Rosenfeld, A.[Azriel],
MAP Estimation of Piecewise Constant Digital Signals,
CVGIP(57), No. 1, January 1993, pp. 63-80.
WWW Version. BibRef 9301

Keeler, K.,
MAP Representations and Coding-Based Priors for Segmentation,
CVPR91(420-425).
IEEE Abstract. IEEE Top Reference. Choose the parameters in the stocastic process that created the image. BibRef 9100

Kundu, A.,
A Quantization Approach to Image Segmentation,
Draft1988. This did the same as the earlier See also Optimal Multiple Threshold Scheme for Image Segmentation, An. but did try to do multiple thresholds all at once. BibRef 8800

Mardia, K.V., and Hainsworth, T.J.,
A Spatial Thresholding Method for Image Segmentation,
PAMI(10), No. 6, November 1988, pp. 919-927.
IEEE Abstract. IEEE Top Reference.
WWW Version. Segmentation, Binarization. A heavily statistical based analysis for the two class case. Generate segmentations and apply a spatial (median) processing to correct the errors. BibRef 8811

Arnulfo, P.[Perez], and Gonzalez, R.C.,
An Iterative Thresholding Algorithm for Image Segmentation,
PAMI(9), No. 6, November 1987, pp. 742-751. Segmentation, Binarization. Segmentation, Histogram. This method is designed for bimodal distributions and works in a raster format so that local variations in overall lighting can be handled. It computes an adaptive threshold by row scan or column scan and then ORs the result. BibRef 8711

Davis, L.S., Rosenfeld, A., and Weszka, J.S.,
Region Extraction by Averaging and Thresholding,
SMC(5), May 1975, pp. 383-388. Smoothing. Local smoothing before thresholding to reduce the effects of texture. See also Note on Thinning, A. BibRef 7505

Narayanan, K.A., O'Leary, D.P.[Dianne P.], and Rosenfeld, A.,
Image Smoothing and Segmentation by Cost Minimization,
SMC(12), 1982, pp. 91-96. BibRef 8200

Narayanan, K.A., O'Leary, D.P.[Dianne P.], and Rosenfeld, A.,
Multi-Resolution Relaxation,
PR(16), No. 2, 1983, pp. 223-230.
WWW Version. Relaxation. First find the solution at a low resolution, then apply a few iterations at a higher resolution, thus reducing the number of high resolution iterations. BibRef 8300

White, J.M., and Rohrer, G.D.,
Image Thresholding for Optical Character Recognition and Other Applications Requiring Character Image Extraction,
IBMRD(27), No. 4, July 1983, pp. 400-411. OCR. Character Recognition. A dynamic thresholding technique. BibRef 8307

Scott, K.C.[Kevin C.],
System and method for bidirectional adaptive thresholding,
US_Patent5,313,533, May 17, 1994.
HTML Version. BibRef 9405

Venkateswarlu, N.B.,
Implementation of Some Image Thresholding Algorithms on a Connection Machine-200,
PRL(16), No. 7, July 1995, pp. 759-768. BibRef 9507

Hannah, I., Patel, D., Davies, E.R.,
The Use of Variance and Entropic Thresholding Methods for Image Segmentation,
PR(28), No. 8, August 1995, pp. 1135-1143.
WWW Version. BibRef 9508

Patel, D., Hannah, I., Davies, E.R.,
Foreign object detection via texture analysis,
ICPR94(A:586-588).
WWW Version. 9410 BibRef

Patel, D., Davies, E.R., Hannah, I.,
The Use of Convolution-Operators for Detecting Contaminants in Food Images,
PR(29), No. 6, June 1996, pp. 1019-1029.
WWW Version. 9606 BibRef

Huang, L.K.[Liang-Kai], Wang, M.J.J.[Mao-Jiun J.],
Image thresholding by minimizing the measures of fuzziness,
PR(28), No. 1, January 1995, pp. 41-51.
WWW Version. 0401 BibRef

Beghdadi, A., LeNegrate, A., Delesegno, P.V.,
Entropic Thresholding Using a Block Source Model,
GMIP(57), No. 3, May 1995, pp. 197-205. BibRef 9505

Messelodi, S., Modena, C.M.,
Context Driven Text Segmentation and Recognition,
PRL(17), No. 1, January 10 1996, pp. 47-56. BibRef 9601

Philips, T.Y., Rosenfeld, A., and Sher, A.C.,
O(log n) Bimodality Analysis,
PR(22), No. 6, 1989, pp. 741-746.
WWW Version. BibRef 8900

Bhattacharya, P., Yan, Y.K.,
Iterative Histogram-Modification of Gray Images,
SMC(25), No. 3, March 1995, pp. 521-523. BibRef 9503

Venkatesh, S., Rosin, P.L.,
Dynamic Threshold Determination by Local and Global Edge Evaluation,
GMIP(57), No. 2, March 1995, pp. 146-160. BibRef 9503
Earlier: SPIE(1964), 1993, pp. 40-50. Code, Segmentation. The code is available on the vision list archive:
WWW Version. BibRef

Rosin, P.L.,
Edges: Saliency Measures and Automatic Thresholding,
MVA(9), No. 4, 1997, pp. 139-159.
HTML Version. BibRef 9700
Earlier: Techical note No. I.95.58 TRInstitute of Remote Sensing Applications, Ispra Italy., 1995. Extensions of the GMIP paper above.
PDF Version. BibRef

Rosin, P.L.[Paul L.],
Unimodal Thresholding,
PR(34), No. 11, November 2001, pp. 2083-2096.
WWW Version. 0108 BibRef
Earlier: SCIA99(633-642).
PDF Version. See also Thresholding for Change Detection. BibRef

Yen, J.C., Chang, F.J., and Chang, S.,
A New Criterion for Automatic Multilevel Thresholding,
IP(4), No. 3, March 1995, pp. 370-378.
WWW Version. A variation on the entropy function to move the log to outside the loop. BibRef 9503

Robinson, D.C.[David C.],
Apparatus and method for segmenting an input image in one of a plurality of modes,
US_Patent5,339,172, August 16, 1994.
WWW Version. BibRef 9408

Pan, H.P.[He-Ping],
Two-Level Global Optimization for Image Segmentation,
PandRS(49), No. 2, 1994, pp. 21-32. Two levels. Pixel and Region. MDL principle. BibRef 9400

Naveen, T., Woods, J.W.,
Subband Finite-State Scalar Quantization,
IP(5), No. 1, January 1996, pp. 150-155.
WWW Version. BibRef 9601

Ng, W.S., Lee, C.K.,
Comment on Using the Uniformity Measure for Performance-Measure in Image Segmentation,
PAMI(18), No. 9, September 1996, pp. 933-934.
IEEE Abstract. IEEE Top Reference.
WWW Version. Thresholding. The measure by Levine and Nazif ( See also Dynamic Measurement of Computer Generated Image Segmentations. ) is the same as that by Otsu ( See also Threshold Selection Method from Grey-Level Histograms, A. ). BibRef 9609

Wiman, H.,
Array Algebra Polynomial Fitting for Image Segmentation,
JMIV(6), No. 1, January 1996, pp. 7-13. 9608 BibRef

Yan, H.,
Unified Formulation of a Class of Image Thresholding Techniques,
PR(29), No. 12, December 1996, pp. 2025-2032.
WWW Version. 9701 BibRef

Chang, J.S., Liao, H.Y.M., Hor, M.K., Hsieh, J.W., Chern, M.Y.,
New Automatic Multilevel Thresholding Technique for Segmentation of Thermal Images,
IVC(15), No. 1, January 1997, pp. 23-34.
WWW Version. 9702 BibRef

Karssemeijer, N.,
A Relaxation Method for Image Segmentation Using a Spatially Dependent Stochastic Model,
PRL(11), 1990, pp. 13-23. BibRef 9000

Pal, S.K., Rosenfeld, A.,
Image Enhancement and Thresholding by Optimization of Fuzzy Compactness,
PRL(7), 1988, pp. 77-86. BibRef 8800

Pal, S.K., Pal, N.R.,
Segmentation Using Contrast and Homogeneity Measures,
PRL(5), 1987, pp. 293-304. BibRef 8700

Pal, N.R., Pal, S.K.,
Image Model, Poisson Distribution and Object Extraction,
PRAI(5), 1991, pp. 459-483. BibRef 9100

Pal, S.K., Pal, N.R.,
Object Extraction from Image Using Higher Order Entropy,
ICPR88(I: 348-350).
WWW Version.
IEEE Top Reference. BibRef 8800

Lu, F.S., Wise, G.L.,
A Further Investigation of Max's Algorithm for Optimum Quantization,
Commun(33), 1985, pp. 746-750. BibRef 8500

Swaszek, P.F.,
Uniform Spherical Coordinate Quantization of Spherically Symmetric Sources,
Commun(33), 1985, pp. 518-521. BibRef 8500

Vasquez, G.,
Comments on 'A Simple Approximation for Minimum Mean-Square Error Symmetric Uniform Quantization',
Commun(34), 1986, pp. 298-300. BibRef 8600

Swaszek, P.F., Thomas, J.B.,
Design of Quantizers from Histograms,
Commun(32), 1984, pp. 240-245. BibRef 8400

Scheunders, P.,
A Genetic C-Means Clustering-Algorithm Applied to Color Image Quantization,
PR(30), No. 6, June 1997, pp. 859-866.
WWW Version. 9706 BibRef

Scheunders, P.,
A Comparison of Clustering Algorithms Applied to Color Image Quantization,
PRL(18), No. 11-13, November 1997, pp. 1379-1384. 9806 BibRef

Scheunders, P.[Paul],
A Genetic Approach Towards Optimal Color Image Quantization,
ICIP96(III: 1031-1034).
WWW Version. BibRef 9600

Scheunders, P., van Hove, H., Livens, S.,
On the Local Optimality of Image Quantizers,
ICPR96(IV: 664-668).
WWW Version. 9608(RUCA, Univ. of Antwerp, B) BibRef

Livens, S.[Stefan], van Roost, C.[Chris], Scheunders, P.[Paul], and van Dyck, D.[Dirk],
Granulometric Segmentation Using a Gradient Convergence Map,
SCIA97(xx-yy) 9705
HTML Version. BibRef

Hansen, M.W.[Michael W.], Higgins, W.E.[William E.],
Relaxation Methods for Supervised Image Segmentation,
PAMI(19), No. 9, September 1997, pp. 949-962.
IEEE Abstract. IEEE Top Reference.
WWW Version. 9710 BibRef
Earlier:
Watershed-driven relaxation labeling for image segmentation,
ICIP94(III: 460-464).
WWW Version. 9411Watershed driven relaxation labeling. Applied to 3D medical images. Use cues that indicate region shape. BibRef

Friel, N.[Nial], Molchanov, I.S.[Ilya S.],
A new thresholding technique based on random sets,
PR(32), No. 9, September 1999, pp. 1507-1517.
WWW Version. BibRef 9909

Saha, P.K.[Punam K.], Udupa, J.K.[Jayaram K.],
Optimum Image Thresholding via Class Uncertainty and Region Homogeneity,
PAMI(23), No. 7, July 2001, pp. 689-706.
IEEE Abstract. IEEE Top Reference.
WWW Version. 0108Account for intensity information (histograms) and region homogeneity with a scale-based formulation. Compared with: See also Maximum Segmented Image Information Thresholding. See also Fuzzy connectedness and image segmentation. BibRef

Comaniciu, D.[Dorin], Meer, P.[Peter],
Mean Shift: A Robust Approach Toward Feature Space Analysis,
PAMI(24), No. 5, May 2002, pp. 603-619.
IEEE Abstract. IEEE Top Reference.
WWW Version. 0205 BibRef
Earlier:
Mean Shift Analysis and Applications,
ICCV99(1197-1203).
WWW Version. An estimator of the density gradient. Generate regions from values. For the code: See also Edison: Edge Detection and Image SegmentatiON system. BibRef

Comaniciu, D.[Dorin], Meer, P.[Peter],
Robust Analysis of Feature Spaces: Color Image Segmentation,
CVPR97(750-755).
IEEE Abstract. IEEE Top Reference.
WWW Version. 9704 Code, Segmentation. For the C++ code:
HTML Version. Color quantization for segmentation. Map into another feature space. BibRef

Georgescu, B., Shimshoni, I., Meer, P.,
Mean shift based clustering in high dimensions: A Texture Classification Example,
ICCV03(456-463).
WWW Version. 0311 BibRef

Stanford, D.C.[Derek C.], Raftery, A.E.[Adrian E.],
Approximate Bayes Factors for Image Segmentation: The Pseudolikelihood Information Criterion (PLIC),
PAMI(24), No. 11, November 2002, pp. 1517-1520.
IEEE Abstract. IEEE Top Reference. 0211Segmentation by quantization. BibRef

Jiang, X.Y.[Xiao-Yi], Mojon, D.,
Adaptive local thresholding by verification-based multithreshold probing with application to vessel detection in retinal images,
PAMI(25), No. 1, January 2003, pp. 131-138.
IEEE Abstract. IEEE Top Reference.
WWW Version. 0301Applied to retina images. Find the blood vessels. BibRef

Sund, T., Eilertsen, K.,
An algorithm for fast adaptive image binarization with applications in radiotherapy imaging,
MedImg(22), No. 1, January 2003, pp. 22-28.
IEEE Top Reference. 0304 BibRef

Lin, K.C.[Ku Chin],
Fast image thresholding by finding the zero(s) of the first derivative of between-class variance,
MVA(13), No. 5-6, 2003, pp. 254-262.
HTML Version. 0304 BibRef

Murtagh, F., Starck, J.L.,
Quantization from Bayes factors with application to multilevel thresholding,
PRL(24), No. 12, August 2003, pp. 2001-2007.
WWW Version. 0304 BibRef

Murtagh, F., Barreto, D., Marcello, J.,
Decision Boundaries Using Bayes Factors: The Case of Cloud Masks,
GeoRS(41), No. 12, December 2003, pp. 2952-2958.
IEEE Abstract. IEEE Top Reference. 0402 BibRef

Murtagh, F.[Fionn], Raftery, A.E.[Adrian E.], Starck, J.L.[Jean-Luc],
Bayesian inference for multiband image segmentation via model-based cluster trees,
IVC(23), No. 6, 1 June 2005, pp. 587-596.
WWW Version. 0505 BibRef

Chung, K.L.[Kuo-Liang], Chen, W.Y.[Wan-Yu],
Fast adaptive PNN-based thresholding algorithms,
PR(36), No. 12, December 2003, pp. 2793-2804.
WWW Version. 0310 BibRef

Meyer, F.[Fernand],
Levelings, Image Simplification Filters for Segmentation,
JMIV(20), No. 1-2, January-March 2004, pp. 59-72.
WWW Version. 0403 BibRef

Hanbury, A.[Allan], Marcotegui, B.[Beatriz],
Waterfall Segmentation of Complex Scenes,
ACCV06(I:888-897).
WWW Version. 0601 BibRef

Zanoguera, M.F.[M. Francisca], Marcotegui, B.[Beatriz], Meyer, F.[Fernand],
A Toolbox for Interactive Segmentation Based on Nested Partitions,
ICIP99(I:21-25).
IEEE Abstract. IEEE Top Reference. BibRef 9900

Demirkaya, O.[Omer], Asyali, M.H.[Musa H.],
Determination of image bimodality thresholds for different intensity distributions,
SP:IC(19), No. 6, July 2004, pp. 507-516.
WWW Version. 0409 BibRef

Benabdelkader, S.[Souad], Boulemden, M.[Mohammed],
Recursive algorithm based on fuzzy 2-partition entropy for 2-level image thresholding,
PR(38), No. 8, August 2005, pp. 1289-1294.
WWW Version. 0505Entropy approach for threshold selection. BibRef

Tong, C.S.[Chong Sze], Zhang, Y.P.[Yong-Ping], Zheng, N.N.[Nan-Ning],
Variational Image Binarization and its Multi-Scale Realizations,
JMIV(23), No. 2, September 2005, pp. 185-198.
WWW Version. 0505 BibRef

Yang, Y.[Yong], Zheng, C.X.[Chong-Xun], Lin, P.[Pan],
Spatially Weighted Fuzzy C-Means Clustering Algorithm for Image Thresholding,
GVIP(05), No. V3, 2005, pp. xx-yy
HTML Version. BibRef 0500

Tizhoosh, H.R.[Hamid R.],
Image thresholding using type II fuzzy sets,
PR(38), No. 12, December 2005, pp. 2363-2372.
WWW Version. 0510 BibRef

Tizhoosh, H.R.[Hamid R.],
Interval-valued versus intuitionistic fuzzy sets: Isomorphism versus semantics,
PR(41), No. 5, May 2008, pp. 1829-1830.
WWW Version. 0711 BibRef

Shokri, M., Tizhoosh, H.R.,
Q-Lambda -based image thresholding,
CRV04(504-508).
IEEE Abstract. IEEE Top Reference. 0408 BibRef

Vlachos, I.K.[Ioannis K.], Sergiadis, G.D.[George D.],
Comment on: 'Image thresholding using type II fuzzy sets',
PR(41), No. 5, May 2008, pp. 1827-1828.
WWW Version. 0711 See also Image thresholding using type II fuzzy sets. BibRef

Wang, S.T.[Shi-Tong], Chung, F.L.,
Note on the equivalence relationship between Renyi-entropy based and Tsallis-entropy based image thresholding,
PRL(26), No. 14, 15 October 2005, pp. 2309-2312.
WWW Version. 0510 BibRef

Blayvas, I.[Ilya], Bruckstein, A.M.[Alfred M.], Kimmel, R.[Ron],
Efficient Computation of Adaptive Threshold Surfaces for Image Binarization,
PR(39), No. 1, January 2006, pp. 89-101.
WWW Version. 0512 BibRef
Earlier: CVPR01(I:737-742).
IEEE Abstract. IEEE Top Reference. 0110 BibRef

Sifre-Maunier, L.[Laurence], Taylor, R.G.[Richard G.], Berge, P.[Philippe], Culioli, J.[Joseph], Bonny, J.M.[Jean-Marie],
A global unimodal thresholding based on probabilistic reference maps for the segmentation of muscle images,
IVC(24), No. 10, 1 October 2006, pp. 1080-1089.
WWW Version. 0609Unimodal thresholding; Segmentation; Muscle BibRef

Bazi, Y.[Yakoub], Bruzzone, L.[Lorenzo], Melgani, F.[Farid],
Image thresholding based on the EM algorithm and the generalized Gaussian distribution,
PR(40), No. 2, February 2007, pp. 619-634.
WWW Version. 0611Image thresholding; Expectation-Maximization algorithm; Generalized Gaussian distribution; Genetic algorithms BibRef

Peng, T.G.[Tie-Gen], Wang, Y.H.[Yin-Hua], Wu, T.H.[Ti-Hua],
Mean shift algorithm equipped with the intersection of confidence intervals rule for image segmentation,
PRL(28), No. 2, 15 January 2007, pp. 268-277.
WWW Version. 0611Keywords: Intersection of confidence intervals (ICI); Mean shift; Image segmentation; Kernel function; Bandwidth selection BibRef

Wang, S.T.[Shi-Tong], Chung, F.L.[Fu-Lai], Xiong, F.[Fusong],
A novel image thresholding method based on Parzen window estimate,
PR(41), No. 1, January 2008, pp. 117-129.
WWW Version. 0710Parzen window; Thresholding; Image segmentation BibRef

Cao, L.[Li], Bao, P.[Paul], Shi, Z.[Zhongke],
The strongest schema learning GA and its application to multilevel thresholding,
IVC(26), No. 5, May 2008, pp. 716-724.
WWW Version. 0803Multilevel thresholding; Otsu method; Kapur method; Genetic algorithms; Schema BibRef

Chabrier, S., Rosenberger, C.[Christophe], Emile, B., Laurent, H.[Helene],
Optimization-Based Image Segmentation by Genetic Algorithms,
JIVP(2008), No. 2008, pp. xx-yy.
WWW Version. 0804 BibRef


Lu, Z.W.[Zhi-Wu], Peng, Y.X.[Yu-Xin], Xiao, J.G.[Jian-Guo],
Unsupervised learning of finite mixtures using entropy regularization and its application to image segmentation,
CVPR08(1-8).
WWW Version. 0806 BibRef

Paris, S.[Sylvain], Durand, F.[Fredo],
A Topological Approach to Hierarchical Segmentation using Mean Shift,
CVPR07(1-8).
WWW Version. 0706 BibRef

Yang, L.[Lin], Meer, P.[Peter], Foran, D.J.[David J.],
Multiple Class Segmentation Using A Unified Framework over Mean-Shift Patches,
CVPR07(1-8).
WWW Version. 0706 BibRef

Rodríguez, R.[Roberto], Suarez, A.G.[Ana G.],
An Image Segmentation Algorithm Using Iteratively the Mean Shift,
CIARP06(326-335).
WWW Version. 0611 BibRef

Liu, J.D.[Jun-Dong],
Robust Image Segmentation using Local Median,
CRV06(31-31).
WWW Version. 0607 BibRef

Sahba, F., Tizhoosh, H.R., Salama, M.M.A.,
Increasing Object Recognition Rate using Reinforced Segmentation,
ICIP06(781-784). 0610
WWW Version. BibRef

Rahnamayan, S., Tizhoosh, H.R., Salama, M.M.A.,
Weighted Voting-Based Robust Image Thresholding,
ICIP06(1129-1132). 0610
WWW Version. BibRef

Olhede, S.C.,
Hyperanalytic Thresholding,
ICIP06(1421-1424). 0610
WWW Version. BibRef

Malisia, A.R., Tizhoosh, H.R.,
Applying Ant Colony Optimization to Binary Thresholding,
ICIP06(2409-2412). 0610
WWW Version. BibRef
Earlier:
Image Thresholding Using Ant Colony Optimization,
CRV06(26-26).
WWW Version. 0607 BibRef

Singh, M., Ahuja, N.,
Regression Based Bandwidth Selection for Segmentation Using Parzen Windows,
ICCV03(2-9).
WWW Version. 0311Represent the image as piecewise continuous. Find modes. BibRef

Wu, S.[Sue], Amin, A.,
Automatic thresholding of gray-level using multi-stage approach,
ICDAR03(493-497).
IEEE Abstract. IEEE Top Reference. 0311 BibRef

Cho, W.H., Kim, S.H.,
Mean Field Annealing EM for Image Segmentation,
ICIP00(Vol III: 568-571).
IEEE Abstract. IEEE Top Reference. 0008 BibRef

Smolka, B.[Bogdan], Wojciechowski, K.W.[Konrad W.],
A new method of texture binarization,
CAIP97(629-636).
WWW Version. 9709 BibRef

Kindratenko, V.V.[Volodymyr V.], Treiger, B.A.[Boris A.], Van Espen, P.J.M.[Piet J. M.],
Binarization of inhomogeneously illuminated images,
CIAP95(483-487).
WWW Version. 9509 BibRef

Madarasmi, S., Kersten, D., and Pong, T.C.,
Multi-Layer Surface Segmentation Using Energy Minimization,
CVPR93(774-775).
IEEE Abstract. IEEE Top Reference. BibRef 9300

Pong, T.C., Madarasmi, S., Chu, Y.L.,
Texture Segmentation Using Topographic Labels,
CVIP92(537-554). BibRef 9200

Tao, W., Burkhardt, H.,
An Effective Image Thresholding Method Using a Fuzzy Compactness Measure,
ICPR94(A:47-51).
WWW Version. BibRef 9400

Kiryati, N., Bruckstein, A.M.,
On piecewise-planar representation of images,
ICPR92(III:451-454).
WWW Version. 9208 BibRef

Jiang, T., Merickel, M.B., Parrish, Jr., E.A.,
Automated Threshold Detection Using A Pyramid Structure,
ICPR88(II: 689-692).
WWW Version. 8811 BibRef

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Clustering for Region Segmentation .


Last update:Aug 27, 2008 at 19:16:50