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![]() ReferencesAbutaleb, A. S. (1989). Automatic Thresholding of gray-level pictures using two-dimensional entropy, Computer Vision, Graphics and Image Processing 47:22-32. Bertolo, D. (2001). Image thresholding using probabilistic distance criteria. Honours Thesis, School of Computer Science and Software Engineering, Monash University. Chang, C., Chen, K., Wang, J. & Althouse, M. L. G. (1994). A relative entropy based approach to image thresholding, Pattern Recognition 27(9): 1275-1289. Cheriet, M., Said, J. N. & Suen, C. Y. (1998). A recursive thresholding technique for image segmentation, IEEE Transactions on Image Processing 7(6) :918-921. Cho, W.-H., Kim, S.-H., Park, S.-Y., & Park, J.-H. (2000). Mean field annealing EM for image segmentation, IEEE Transactions on Image Processing, Vol. 3, pp. 568-571. Figueiredo, M. A. T. & Jain, A. K. (2002). Unsupervised learning of finite mixture models, IEEE Transactions on Pattern Analysis and Machine Intelligence 24(3): 381-396. Glasby, C. A. (1993). An analysis of histogram-based thresholding algorithms, CVGIP: Graphical Models and Image Processing 55(6): 532-537. Gonzalez, R. C. & Woods, R. E. (2002). Digital Image Processing, 2nd edn, Prentice-Hall, New Jersey. Jansen, R. C., Reinink, K. & van der Heijden, G. W. A. M. (1993). Analysis of grey level histograms by using statistical methods for mixture distributions, Pattern Recognition 14: 585-590. Kapur, J. N., Sahoo, P. K. & Wong, A. K. C. (1985). A new method for gray-level picture thresholding using the entropy of the histogram, Computer Vision, Graphics and Image Processing 29: 273-285. Kittler, J. & Illingworth, J. (1986). Minimum error thresholding, Pattern Recognition 19(1): 41-47. Kurita, T., Otsu, N. & Abdelmalek, N. (1992). Maximum likelihood thresholding based on population mixture models, Pattern Recognition 25(10): 1231-1240. Lee, S. U., Chung, S. Y. & Park, R. H. (1990). A comparative performance study of several global thresholding techniques for segmentation, Computer vision, Graphics and Image Processing 52: 171-190. Lee, T.-W. & Lewicki, M. S. (2002). Unsupervised image classification, segmentation and enhancement using ICA mixture models, IEEE Transactions on Image Processing 11(3): 270-279. Levine, M. D. & Nazif, A. M. (1995). Dynamic measurement of computer generated image segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence 7: 155-164. Lindarto, T. (1996). MML segementation-based image coding, Masters Thesis, School of Computer Science and Software Engineering, Monash University. Mclachlan, G. J. & Basford, K. E. (1988). Mixture models: inference and applications to clustering, Marcel Dekker, New York. Pal, N. R. & Pal, S. K. (1989a). Entropic thresholding, Signal Processing 16: 97-108. Pal, N. R. & Pal, S. K. (1989b). Object-background segmentation using new definitions of entropy, IEEE Proceedings on ? 139: 284-295. Ray, S. (1993). Entropy-based image segmentation, Third International Conference on Advances in Pattern Recognition and Digital Techniques, pp. 698-715. Ray, S., Shakya, R. & Srinivasan, B. (1997). New approaches to image segmentation based on probabilistic distance criteria, IASTED International Conference on Image and Signal Processing, pp. 698-715. Reddi, S. S., Rudin, S. F. & Keshavan, H. R. (1984). An optimal threshold scheme for image segmentation, IEEE Transactions on Systems, Man and Cybernetics 14(4): 661-665. Roberts, S. J., Husmeirer, D., Rezek, I. & Penny, W. (1998). Bayesian approaches to gaussian mixture modelling, IEEE Transactions on Pattern Analysis and Machine Intelligence 20(11): 1133-1142. Sahoo, P. K., Soltani, S., Wong, A. K. C. & Chen, Y. C. (1988). A survey of thresholding techniques, Computer Vision, Graphics and Image Processing 41: 233-260. S T W Y I'm sorry, this website is still under construction. Here is my bibtex file LAST UPDATED: 4 March 2003 |