Image analysis and processing is steadily gaining relevance within the large number of application fields to which genetic and evolutionary computation (GEC) techniques are applied. Although more and more examples of such applications can be found in literature, they are scattered, apart from a few exceptions, in proceedings and journals dedicated to more general topics. This book is the first attempt to offer a panoramic view on the field, by describing applications of most mainstream GEC techniques to a wide range of problems in image processing and analysis. More than 20 leading researchers in the field have contributed to this book, covering topics ranging from low-level image processing to high-level image analysis in advanced computer vision applications. Although the book is mainly application-oriented, particular care has been given to introducing GEC methods, in each chapter, at a level which makes them accessible to a wide audience. The expected target of the book comprises practitioners and researchers in image analysis and processing who may not be familiar with GEC techniques. At the same time, the book can as well be of interest for researchers in evolutionary computation, since most contributions focus on applications of genetic and evolutionary techniques which are based on nontrivial implementations of such methods. This feature reflects the nature of the contributions which are authored both by researchers for which GEC is the main field of interest and by researchers whose work is mainly focused on image processing and analysis.
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About the Author
Stefano Cagnoni graduated in Electronic Engineering at the University of Florence in 1988 where he has been a PhD student and a post-doc until 1997, working in the Bioengineering Lab of the Dept. of Electronic Engineering. He received the PhD degree in Bioengineering in 1993.
In 1994 he was a visiting scientist at the Whitaker College Biomedical Imaging and Computation Laboratory at the Massachusetts Institute of Technology. Since 1997, he has been with the Department of Computer Engineering of the University of Parma, where he is currently Associate Professor.
Gustavo Olague is a research scientist at the CICESE Research Center working within the Computer Science Department of the Applied Physics Division. He hold a Bachelor's degree (Honors) in Electronics Engineering and a Master's degree in Computer Science from the Instituto Tecnológico de Chihuahua, Mexico. He received the Ph.D. (Diplôme de Doctorat en Imagerie, Vision et Robotique) in Computer Graphics, Vision and Robotics from Institut National Polytechnique de Grenoble, France, working at the INRIA Rhône Alpes within the MOVI Research team.
He is presently a Professor of Computer Science at Centro de Investigación CientÃfica y de Educación Superior de Ensenada, B.C. Olague's research focuses on the principles of computational intelligence applied to close-range photogrammetry and computer vision. He is a member of the EvoNET, RSPSoc, ASPRS, ISGEC, IEEE, IEEE Computer Society, and is listed in Who's Who in Science and Engineering. Dr. Olague is recipient of the "2003 First Honorable Mention for the Talbert Abrams Award", offered by the American Society for Photogrammetry and Remote Sensing.
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After a long incubation in academia and in very specialized industrial environments, in the last ten to fifteen years research and development of image processing and computer vision applications have become mainstream industrial activities. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
soft computing, evolvable image filter, class boundary determination, gray level precision, photogrammetric network design, genetic snakes, detection training set, photogrammetric networks, step edge function, halftoning problem, object detection performance, detection test set, object classification problems, offspring configuration, shape datasets, prosthetic hand controller, composite feature vectors, visual feature space, homogeneity predicate, fitness map, qualitative mutation, extinctive selection, sweeping map, niche measure, extraction programmes Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Lecture Notes, Computer Science, Morgan Kaufmann, John Wiley, International Conference, San Francisco, The Netherlands, Stefano Cagnoni, Stanford University, Pattern Recognition, Academic Press, World Congress, Kluwer Academic Publishers, Oscar Cordon, San Diego, Anlei Dong, Signal Processing, Ann Arbor, Quick Bird, World Scientific, Machine Learning, University of Michigan, New Zealand, International Workshop Browse Sample Pages:
Front Cover | Front Flap | Table of Contents | First Pages | Back Flap | Back Cover | Surprise Me!
After a long incubation in academia and in very specialized industrial environments, in the last ten to fifteen years research and development of image processing and computer vision applications have become mainstream industrial activities. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
soft computing, evolvable image filter, class boundary determination, gray level precision, photogrammetric network design, genetic snakes, detection training set, photogrammetric networks, step edge function, halftoning problem, object detection performance, detection test set, object classification problems, offspring configuration, shape datasets, prosthetic hand controller, composite feature vectors, visual feature space, homogeneity predicate, fitness map, qualitative mutation, extinctive selection, sweeping map, niche measure, extraction programmes Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Lecture Notes, Computer Science, Morgan Kaufmann, John Wiley, International Conference, San Francisco, The Netherlands, Stefano Cagnoni, Stanford University, Pattern Recognition, Academic Press, World Congress, Kluwer Academic Publishers, Oscar Cordon, San Diego, Anlei Dong, Signal Processing, Ann Arbor, Quick Bird, World Scientific, Machine Learning, University of Michigan, New Zealand, International Workshop Browse Sample Pages:
Front Cover | Front Flap | Table of Contents | First Pages | Back Flap | Back Cover | Surprise Me!
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