Unsupervised classification of images in RGB color model and cluster validation techniques

Proceedings of the 2010 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2010

Volumn 2, Issue , 2010, Pages 526-532

  Macedo Cruz, A ^a   Pajares Martinsanz, G ^a   Santos Penas M ^a  

^a UNIVERSIDAD COMPLUTENSE DE MADRID   (Spain)

Author keywords

Clustering; Color image thresholding; Otsu's method; Pattern recognition

Indexed keywords

AERIAL IMAGES; AUTOMATIC THRESHOLDING; CLUSTER VALIDATION; CLUSTER VALIDITY; CLUSTERING; COLOR IMAGES; EFFECTIVE TOOL; LAND COVER; MEAN SHIFT; OTSU'S METHOD; QUANTITATIVE INDICES; RGB COLOR MODEL; RGB COLOR SPACE; THRESHOLDING; UNSUPERVISED APPROACHES; UNSUPERVISED CLASSIFICATION;

COLOR IMAGE PROCESSING; PATTERN RECOGNITION; REMOTE SENSING;

COMPUTER VISION;

EID: 84864932747     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (29)

1. D. Lu, and Q. Weng. 2007. A survey of image classification methods and techniques for improving classification performance, Int. J. Remote Sensing 28(5):823-870.
2. A. K. Jain, M. N. Murty and P. J. Flynn. 1999. Data clustering: a review, ACM Computing Surveys, Vol. 31 (3):264-323.
3. Y. Du, C. I. Chang, and P.D. Thouin. 2004. Unsupervised approach to color video thresholding. Optical Eng. 43(2):282-289.
4. X. Xie, and Majid Mirmehdi. 2007. Colour Image Segmentation using Texems, Annals of the British Machine Vision Association, (6):1-10.
5. X. Xie, 2008. A Review of Recent Advances in Surface Defect Detection using Texture Analysis Techniques, Electronic Letters on Computer Vision and Image Analysis, Special Issue on Quality Control by Artificial Vision, vol. 7(3): 1-25.
6. M. Haindl, and V. Havlicek. 2002. A simple multispectral multiresolution Markov texture model. in International Workshop on Texture Analysis and Synthesis, pp: 63-66.
7. M. Dubuisson-Jolly, and A. Gupta. 2000. Color and texture fusion: Application to aerial image segmentation and GIS updating. Image and Vision Computing, 18:823-832.
8. C. Palm, 2004. Color texture classification by integrative co-occurrence matrices. Pattern Recognition, 37(5):965-976
9. M. Mirmehdi, and M. Petrou. 2000. Segmentation of color textures. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(2):142-159.
10. N. Otsu, 1979. A threshold selection method from gray-level histogram. IEEE Transactions on System Man Cybernetics 9(1):62-66.
11. D. Comaniciu, and Meer, P. 2002. Mean shift: a robust approach toward feature space analysis. IEEE PAML, Vol. 24(5):603-619
12. K. Fukunaga, and L.D. Hostetler. 1975. The Estimation of the Gradient of a Density Function, UIT Application in Pattern Recognition. IEEE Trans. Information Theory. Vol. 21. pp 32-40.
13. M. Halkidi, Y. Batistakis and M. Vazirgiannis. 2002a. Cluster validity methods: part I, SIGMOD Rec., Vol.31(2):40-45.
14. M. Halkidi, Y. Batistakis and M. Vazirgiannis. 2002b. Cluster validity methods: part II, SIGMOD Rec, Vol. 31, (3). 19-27.
15. K. Wang, B. Wang, and L. Peng. 2009. CVAP: Validation for Cluster Analyses. Data Science. Journal 8(20), 88-93
16. M. Halkidi, Y. Batistakis, and M. Vazirgiannis. 2001. On Clustering Validation Techniques. Intelligent Information Systems Journal, 17 (2-3): 107-145.
17. J. Dunn. 1974. Well separated clusters and optimal fuzzy partitions. J. Cybernetics, Vol. 4, pp. 95-104
18. J.C. Bezdek, and N.R. Pal. 1998. Some new indexes of cluster validity, IEEE Transactions on Systems, Man and Cybernetics, Vol. 28 (B):301-315
19. N. Bolshakova, and F. Azuaje. 2003 Cluster validation techniques for genome expression data. Signal Processing, 83(4): 825-833.
20. D.L. Davies, and D.W. Bouldin. 1979. A cluster separation measure. IEEE Transactions on Pattern Recognition and Machine Intelligence, Vol. 1(2):224-227
21. E. Dimitriadou, S. Dolnicar, and A. Weingessel. 2002 An examination of indexes for determining the Number of Cluster in binary data sets. Psychometrika, 67(1): 137-160.
22. S. Dudoit, and J. Fridlyand. 2002. A prediction-based resampling method for estimating the number of clusters in a dataset. Genome Biology, 3(7): 0036.1-21.
23. G. Shu, B. Zeng, Y. P Chen, and O. H. Smith. (2003) Performance assessment of kernel density clustering for gene expression profile data. Comparative and Functional Genomics, 4(3): 287-299.
24. R. Calinski, and J. Harabasz. 1974. A dendrite method for cluster analysis. Commun Statistics 3:1-27.
25. W. Krzanowski, and Y. Lai. 1985. A criterion for determining the number of groups in a dataset using sum of squares clustering. Biometrics. 44:23-34.
26. J.A. Hartigan. 1985. Statistical theory in clustering. J Classification., 2:63-76.
27. Liao, P.S., T.S. Chen, and P.C. Chung. 2001. A fast algorithm for multilevel thresholding. J. Comput. Information Sci. and Eng. 17:713-727.
28. Y. Cheng. 1995. Mean Shift, Mode Seeking, and Clustering. IEEE Trans. Pattern Analysis and Machine Intelligence. Vol 17(8):790-799.
29. F. Kovács, C. Legány, and A. Babos. 2005. Cluster validity measurement techniques. Proceedings of the 6th International Symposium of Hungarian Researchers on Computational Intelligence, Budapest, Nov. 2005, 18-19.