Fuzzy Logic for Image Processing

This book provides an introduction to fuzzy logic approaches useful in image processing. The authors start by introducing image processing tasks of low and medium level such as thresholding, enhancement, edge detection, morphological filters, and segmentation and shows how fuzzy logic approaches apply. The book is divided into two parts. The first includes vagueness and ambiguity in digital images, fuzzy image processing, fuzzy rule based systems, and fuzzy clustering. The second part includes applications to image processing, image thresholding, color contrast enhancement, edge detection, morphological analysis, and image segmentation. Throughout, they describe image processing algorithms based on fuzzy logic under methodological aspects in addition to applicative aspects. Implementations in java are provided for the various applications.

Covers the most state-of-the-art topics in fuzzy logic as it pertains to image processing Presents a concise introduction to image processing algorithms based on fuzzy logic Outlines image processing tasks such as thresholding, enhancement, edge detection, morphological filters, and segmentation in relation to fuzzy logic Includes supplementary material: sn.pub/extras

Autorentext

Dr. Laura Caponetti received her degree in Physics at the University of Bari, Italy, in 1972. She is an associate professor (retired) at the Computer Science Department of the University of Bari A. Moro, where she has been working from 1982 as assistant professor. Her research interests are in Image Processing and Computer Vision. Her research (https://www.researchgate.net/profile/Laura_Caponetti) spans a range of topics including Image Segmentation, Three-Dimensional Object Recognition, 3D Scene Analysis, Fuzzy Image Processing. She has published over eighty papers and she is a referee of international journals and conferences. She has been a member of the scientific committee of the Master in Remote Sensing Techniques and a member of the Council of Phd in Computer Science at the Bari University. She has been a lecture of Information Processing Systems (Sistemi di Elaborazione della informazione) for the degree course in Computer Science and Computer System Foundations (Fondamenti di Informatica) for the degree course in Civil Engineering. Moreover she has been a lecturer of Image Processing for the degree course in Computer Science and for the Master in Remote Sensing Techniques. Currently she is a referee of the Ministero dell'Istruzione, dell'Università e della Ricerca (http://www.istruzione.it/). Finally she is a member of scientific associations such as IAPR (Italian Chapter), AICA, and AIIA.

Dr. Giovanna Castellano is Associate Professor at the Computer Science Department of the University of Bari A. Moro, Italy. In 1993 she received her degree in Informatics from the University of Bari. From 1993 to 1995 she was a fellow researcher at the CNR Institute for Signal and Image Processing in Bari, Italy. In 2001 she got a Ph.D. in Informatics from the University of Bari, where she became Assistant Professor in 2002. Her research interests are mainly focused on Computational Intelligence, with special focus on fuzzy systems, neural networks,neuro-fuzzy modeling, fuzzy clustering, granular computing, fuzzy image processing. Her current research activity concerns the application of fuzzy techniques in image processing and retrieval. Within these research areas, she has been co-author of more than 170 papers published on scientific journals, book collections and international conference proceedings. Working on these topics she joined a number of research projects and she organized a number of special sessions and workshops in international conferences. She is Associate Editor of the journal Information Sciences (ISSN:0020-0255) and member of the Editorial Board of several international journals.

Inhalt
Part 1. Fundamentals of Fuzzy Image Processing.- Image Representation Using Java.- Low-level Image Processing.- Basics of Fuzzy Logic.- Fuzzy Image Processing.- Java for Image Processing.- Part 2. Application to Image Processing.- Color Contrast Enhancement.- Image Segmentation.- Morphological Analysis.- Image Thresholding.- Appendix A: Java Code References.

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