Fuzzy Techniques in Image Processing / Edition 1by Etienne E. Kerre, Mike Nachtegael
Pub. Date: 06/28/2000
Publisher: Physica-Verlag HD
Since time immemorial, vision in general and images in particular have played an important and essential role in human life. Nowadays, the field of image processing also has numerous scientific, commercial, industrial and military applications. All these applications result from the interaction between fun damental scientific research on the one hand, and the development of new and high-standard technology on the other hand. Regarding the scientific com ponent, quite recently the scientific community became familiar with "fuzzy techniques" in image processing, which make use of the framework of fuzzy sets and related theories. The theory of fuzzy sets was initiated in 1965 by Zadeh, and is one of the most developed models to treat imprecision and uncertainty. Instead of the classical approach that an object belongs or does not belong to a set, the concept of a fuzzy set allows a gradual transition from membership to nonmembership, providing partial degrees of member ship. Fuzzy techniques are often complementary to existing techniques and can contribute to the development of better and more robust methods, as has already been illustrated in numerous scientific branches. With this vol ume, we want to demonstrate that the introduction and application of fuzzy techniques can also be very successful in the area of image processing. This book contains high-quality contributions of over 30 field experts, covering a wide range of both theoretical and practical applications of fuzzy techniques in image processing.
Table of ContentsPreface.- Part I: Fuzzy Mathematical Morphology.- M. Nachtegael, E.E. Kerre: Classical and Fuzzy Approaches towards Mathematical Morphology.- B. De Baets: Generalized Idempotence in Fuzzy Mathematical Morphology.- E.R.. Dougherty, A.T. Popov: Fuzzy Mathematical Morphology Based on Fuzzy Inclusion.- I. Bloch: Fuzzy Mathematical Morphology and Derived Spatial Relationships.- Part II: Fuzzy Image Filtering: H.R. Tizhoosh: Fuzzy Image Enhancement: An Overview.- C.-S. Lee, Y.-H. Kuo: Adaptive Fuzzy Filter and Its Application to Image Enhancement.- F. Farbiz, M. Bagher Menhaj: A Fuzzy Logic Control Based Approach for Image Filtering.- K. Arakawa: Fuzzy Rule-Based Image Processing with Optimization.- C. Vertan, V. Buzuloiu: Fuzzy Nonlinear Filtering of Color Images: A Survey.- Part III: Applications of Fuzzy Techniques in Image Processing: L. Hildebrand, B. Reusch: Fuzzy Color Processing.- Z. Lu, Z. Chi, P. Shi, E.K. Teoh: Ranking Segmentation Paths Using Fuzzified Decision Rules.- A. Rick, S. Bothorel, B. Bouchon-Meunier, S. Muller, M. Rifqi: Fuzzy Techniques in Mammographic Image Processing.- D. Van De Ville, W. Philips, I. Lemahieu: Fuzzy-Based Motion Detection and Its Application to De-Interlacing.- A. Knoll, J. Zhang, T. Graf, A. Wolfram: Object Recognition and Visual Servoing: Two Case Studies of Employing Fuzzy Techniques in Robot Vision.- A. Nakamura, A. Rosenfeld: Topology-Preserving Deformations of Fuzzy Digital Pictures.- Appendix: Color Images of Chapter 9 and 10.- Index.-
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