24.Fuzzy Systems by John G. Webster (Editor) PDF

By John G. Webster (Editor)

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Hilton, A. Estimation of Fuzzy Gaussian Mixture and Unsupervised Statistical Image Segmentation. IEEE Trans. Image Proc. 1997, 6(3), pp 425– 440. ; Flores-Mangas, F. Classification of Anatomical Structures in MR Brain Images Using Fuzzy Parameters. IEEE Trans. Biomed. Eng. 2004, 51(9), pp 1599–1608. ; Lui, Y. ; Freimanis, R. I. A Novel Approach to Microcalcification Detection Using Fuzzy Logic Technique. IEEE Trans. Med. Imag. 1998, 17(3) pp 442–450. Udupa, J. ; Samarasekera, S. Fuzzy Connectedness and Object Definition: Theory, Algorithms and Applications in Image Segmentation.

Using fuzzy techniques. Before leaving this section, we mention the work in Reference (81), which defines the concept of fuzzy objects and describes algorithms for their extraction. Contour Detection Edge detection is also an image segmentation technique where the contours/boundaries of various regions are extracted based on the detection of discontinuity in grayness. Here we present a method for fuzzy edge detection using an edginess measure based on H 1 (Eq. 2), which denotes an amount of difficulty in deciding whether a pixel can be 3 called an edge (19).

39. ; Tizhoosh, H. ; Moore, C. ; Michaelis, B. Fuzzy Image Enhancement and Associative Feature Matching in Radio Therapy. Proc. Int. Conf. Neural Networks (ICNN’97); 1997, 3, 1490–1495. 40. ; Plataniotis, K. ; Venetsanopoulos, A. N. cDNA Microarray Image Processing using Fuzzy Vector Filtering Frameworks. Fuzzy Sets Syst. 2005, 152 (1), pp 17–35. 41. ; Ramponi, G. Nonlinear Fuzzy Operators for Image Processing. Signal Proc. 1994, 38, pp 429–440. 42. ; Ramponi, G. A fuzzy Operator for the Enhancement of Blurred and Noise Images.

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24.Fuzzy Systems by John G. Webster (Editor)


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