New techniques for data clustering and color image segmentation

[1]  Paola Campadelli,et al.  Quantitative evaluation of color image segmentation results , 1998, Pattern Recognit. Lett..

[2]  Greg Mori,et al.  Guiding model search using segmentation , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[3]  Daniel P. Huttenlocher,et al.  Efficient Graph-Based Image Segmentation , 2004, International Journal of Computer Vision.

[4]  Christoph Schnörr,et al.  Natural Image Statistics for Natural Image Segmentation , 2005, International Journal of Computer Vision.

[5]  James C. Bezdek,et al.  Some new indexes of cluster validity , 1998, IEEE Trans. Syst. Man Cybern. Part B.

[6]  Riyadh Kenaya,et al.  Euclidean ART Neural Networks , 2008 .

[7]  Y. P. Kosta,et al.  A seeded region growing algorithm for spot detection in medical image segmentation , 2011, 2011 International Conference on Image Information Processing.

[8]  T. Kanade,et al.  Color information for region segmentation , 1980 .

[9]  M.U. Akram,et al.  Improved fingerprint image segmentation using new modified gradient based technique , 2008, 2008 Canadian Conference on Electrical and Computer Engineering.

[10]  Jeremy S. Smith,et al.  An image-processing based algorithm to automatically identify plant disease visual symptoms. , 2009 .

[11]  Jean Ponce,et al.  Computer Vision: A Modern Approach , 2002 .

[12]  Jerry L Prince,et al.  Current methods in medical image segmentation. , 2000, Annual review of biomedical engineering.

[13]  Tony Lindeberg,et al.  Segmentation and Classification of Edges Using Minimum Description Length Approximation and Complementary Junction Cues , 1996, Comput. Vis. Image Underst..

[14]  N. Senthilkumaran,et al.  Image Segmentation - A Survey of Soft Computing Approaches , 2009, 2009 International Conference on Advances in Recent Technologies in Communication and Computing.

[15]  John Yearwood,et al.  Unsupervised Color Textured Image Segmentation Using Cluster Ensembles and MRF Model , 2007, SCSS.

[16]  Xavier Bresson,et al.  Local Histogram Based Segmentation Using the Wasserstein Distance , 2009, International Journal of Computer Vision.

[17]  M. Vuskovic,et al.  Mahalanobis distance-based ARTMAP network , 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

[18]  Hans-Peter Kriegel,et al.  OPTICS: ordering points to identify the clustering structure , 1999, SIGMOD '99.

[19]  Long Quan,et al.  Normalized tree partitioning for image segmentation , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[20]  Ki-Sang Hong,et al.  Image segmentation by unsupervised sparse clustering , 2006, Pattern Recognit. Lett..

[21]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[22]  D J Field,et al.  Relations between the statistics of natural images and the response properties of cortical cells. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[23]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[24]  V. J. Rayward-Smith,et al.  Fuzzy Cluster Analysis: Methods for Classification, Data Analysis and Image Recognition , 1999 .

[25]  Christophe Rosenberger,et al.  Genetic fusion: application to multi-components image segmentation , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[26]  Maurício Pamplona Segundo,et al.  Automatic Face Segmentation and Facial Landmark Detection in Range Images , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[27]  Garrett Johnson Color and Image Appearance Models , 2008 .

[28]  Mark Q. Shaw,et al.  Automatic Image Segmentation by Dynamic Region Growth and Multiresolution Merging , 2009, IEEE Transactions on Image Processing.

[29]  Stephen Grossberg,et al.  Adaptive Resonance Theory , 2010, Encyclopedia of Machine Learning.

[30]  Fang Liu,et al.  Real-time recognition with the entire Brodatz texture database , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[31]  Jitendra Malik,et al.  A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[32]  Hui Zhang,et al.  An entropy-based objective evaluation method for image segmentation , 2003, IS&T/SPIE Electronic Imaging.

[33]  Lakhmi C. Jain,et al.  Innovations in ART neural networks , 2000 .

[34]  Frank Y. Shih,et al.  Automatic seeded region growing for color image segmentation , 2005, Image Vis. Comput..

[35]  Rolf Adams,et al.  Seeded Region Growing , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[36]  Marina Mueller,et al.  Edge- and region-based segmentation technique for the extraction of large, man-made objects in high-resolution satellite imagery , 2004, Pattern Recognit..

[37]  Hans-Peter Kriegel,et al.  Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications , 1998, Data Mining and Knowledge Discovery.

[38]  Azriel Rosenfeld,et al.  Threshold Evaluation Techniques , 1978, IEEE Transactions on Systems, Man, and Cybernetics.

[39]  David M. W. Powers,et al.  Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation , 2011, ArXiv.

[40]  L. Joshua Leon,et al.  Watershed-Based Segmentation and Region Merging , 2000, Comput. Vis. Image Underst..

[41]  Hui Zhang,et al.  Image segmentation evaluation: A survey of unsupervised methods , 2008, Comput. Vis. Image Underst..

[42]  Hans-Peter Kriegel,et al.  Clustering high-dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering , 2009, TKDD.

[43]  Sheng-Jyh Wang,et al.  The use of visible color difference in the quantitative evaluation of color image segmentation , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[44]  Michael Ball,et al.  Analyzing Visual Data , 1992 .

[45]  Hong Zhang,et al.  An evaluation metric for image segmentation of multiple objects , 2009, Image Vis. Comput..

[46]  Adolfo Martínez Usó,et al.  Unsupervised colour image segmentation by low-level perceptual grouping , 2011, Pattern Analysis and Applications.

[47]  Alexandre X. Falcão,et al.  Links Between Image Segmentation Based on Optimum-Path Forest and Minimum Cut in Graph , 2009, Journal of Mathematical Imaging and Vision.

[48]  Stephen Grossberg,et al.  Competitive Learning: From Interactive Activation to Adaptive Resonance , 1987, Cogn. Sci..

[49]  John A. Hartigan,et al.  Clustering Algorithms , 1975 .

[50]  Luís Corte-Real,et al.  HAIRIS: A Method for Automatic Image Registration Through Histogram-Based Image Segmentation , 2011, IEEE Transactions on Image Processing.

[51]  David S. Watkins,et al.  Fundamentals of matrix computations , 1991 .

[52]  Christian Böhm,et al.  Computing Clusters of Correlation Connected objects , 2004, SIGMOD '04.

[53]  Hélène Laurent,et al.  Unsupervised evaluation of image segmentation application to multi-spectral images , 2004, ICPR 2004.

[54]  B. S. Manjunath,et al.  Unsupervised Segmentation of Color-Texture Regions in Images and Video , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[55]  Shital A. Raut,et al.  Image Segmentation – A State-Of-Art Survey for Prediction , 2009, 2009 International Conference on Advanced Computer Control.

[56]  R. Fisher THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[57]  Doheon Lee,et al.  On cluster validity index for estimation of the optimal number of fuzzy clusters , 2004, Pattern Recognit..

[58]  Anil K. Jain Data clustering: 50 years beyond K-means , 2010, Pattern Recognit. Lett..

[59]  Richard A. Johnson,et al.  Applied Multivariate Statistical Analysis , 1983 .

[60]  Sameer Singh,et al.  Novelty detection: a review - part 2: : neural network based approaches , 2003, Signal Process..