By John G. Webster (Editor)
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Additional info for 24.Fuzzy Systems
For example, if the image is smooth, the disk will not have abrupt change in its values. On the other hand, it will have abrupt change in case the image has salt and pepper noise or edginess. The concept of fuzzy MAT can therefore be used as spatial ﬁltering (both high pass and low pass) of an image by manipulating the disk values to the extent desired and then putting them back while reconstructing the processed image. A gray-scale thinning algorithm is described in References 60 and 87 based on the concept of fuzzy connectedness between two pixels; the dark regions can be thinned without ever being explicitly segmented.
IEEE Trans. Comp. 1986, 35, pp 145–156. Lee, E. ; Zadeh, L. A. Note on Fuzzy Languages. Inform. Sci. 1969, 1, pp 421–434. Thomason, M. G. Finite Fuzzy Automata, Regular Fuzzy Languages, and Pattern Recognition. Pattern Recog. 1973, 5, pp 383–390. DePalme, G. ; Yan, S. S. Fractionally Fuzzy Grammars with Applications to Pattern Recognition. In Fuzzy Sets and Their Applications to Cognitive and Decision Processess, Zadeh, L. ; Academic Press: London, 1975. Wachs, J. ; Edan, Y. Cluster Labeling and Parameter Estimation for the Automated Setupt of a Hand-Gesture Recognition System.
115. ; Kundu, M. ; Chanda, B. Segmentation of Brain MR Images Using Fuzzy Sets and Modiﬁed Co-occurrence Matrix; IEEE Proc. International Conference on Visual Information Engineering (VIE-06);India, September, 2006. 116. ; Dougherty, E. ; Batman, S. Design and Analysis of Fuzzy Morphological Algorithm for Image Processing. IEEE Trans. Fuzz. Syst. 1997, 5(4), pp 570–584. 117. ; Tsalides, P. Fuzzy Soft Mathematical Morphology. - Vision, Image and Signal Processing; 1998, 145(1), pp 41–49. 118. Bloch, I.
24.Fuzzy Systems by John G. Webster (Editor)