Fuzzy filters for image processing
Author(s)
Bibliographic Information
Fuzzy filters for image processing
（Studies in fuzziness and soft computing, v. 122）
Springer, c2003
Available at / 5 libraries
-
No Libraries matched.
- Remove all filters.
Note
Includes bibliographical references and index
Description and Table of Contents
Description
The ongoing increase in scale of integration of electronics makes storage and computational power affordable to many applications. Also image process ing systems can benefit from this trend. A variety of algorithms for image processing tasks becomes close at hand. From the whole range of possible approaches, those based on fuzzy logic are the ones this book focusses on. A particular useful property of fuzzy logic techniques is their ability to represent knowledge in a way which is comprehensible to human interpretation. The theory of fuzzy sets and fuzzy logic 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 mem bership to nonmembership, providing partial degrees of membership. 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. The present book resulted from the workshop "Fuzzy Filters for Image Processing" which was organized at the 10th FUZZ-IEEE Conference in Mel bourne, Australia. At this event several speakers have given an overview of the current state-of-the-art of fuzzy filters for image processing. Afterwards, the book has been completed with contributions of other international re searchers.
Table of Contents
1. Fuzzy Filters for Noise Removal.- 2. Fuzzy Filters for Noise Reduction in Images.- 3. Real-time Image Noise Cancellation Based on Fuzzy Similarity.- 4. Fuzzy Rule-Based Color Filtering Using Statistical Indices.- 5. Fuzzy Based Image Segmentation.- 6. Fuzzy Thresholding and Histogram Analysis.- 7. Color Image Segmentation by Analysis of 3D Histogram with Fuzzy Morphological Filters.- 8. Fast and Robust Fuzzy Edge Detection.- 9. Fuzzy Data Fusion for Multiple Cue Image and Video Segmentation.- 10. Fuzzy Image Enhancement in the Framework of Logarithmic Models.- 11. Observer-Dependent Image Enhancement.- 12. Fuzzy Techniques in Digital Image Processing and Shape Analysis.- 13. Adaptive Fuzzy Filters and Their Application to Online Maneuvering Target Tracking.- 14. Lossy Image Compression and Reconstruction Based on Fuzzy Relational Equation.- 15. Avoidance of Highlights through ILFOs in Automated Visual Inspection.- Appendix Color Images.
by "Nielsen BookData"