Computational Intelligence in Multimedia Processing: Foundation and Trends
This chapter presents a broad overview of Computational Intelligence (CI) techniques including Neural Network (NN), Particle Swarm Optimization (PSO), Evolutionary Algorithm (GA), Fuzzy Set (FS), and Rough Sets (RS). In addition, a very brief introduction
- PDF / 2,235,156 Bytes
- 47 Pages / 595 x 842 pts (A4) Page_size
- 29 Downloads / 190 Views
2
3
4
5
Information Technology Department, FCI Cairo University 5 Ahamed Zewal Street, Orman, Giza, Egypt [email protected] Information System Department, CBA Kuwait University, Kuwait [email protected] Center for Quantifiable Quality of Service in Communication Systems Norwegian University of Science and Technology O.S. Bragstads plass 2E, N-7491 Trondheim, Norway [email protected], [email protected] Systems Research Institute Polish Academy of Sciences ul. Newelska 6 01-447 Warsaw, Poland [email protected] Department of Electrical and Computer Engineering University of Manitoba Winnipeg, Manitoba R3T 5V6, Canada [email protected]
Summary. This chapter presents a broad overview of Computational Intelligence (CI) techniques including Neural Network (NN), Particle Swarm Optimization (PSO), Evolutionary Algorithm (GA), Fuzzy Set (FS), and Rough Sets (RS). In addition, a very brief introduction to near sets and near images which offer a generalization of traditional rough set theory and a new approach to classifying perceptual objects by means of features in solving multimedia problems is presented. A review of the current literature on CI based approaches to various problems in multimedia computing such as speech, audio and image processing, video watermarking, content-based multimedia indexing and retrieval are presented. We discuss some representative methods to provide inspiring examples to illustrate how CI could be applied to resolve multimedia computing problems and how multimedia could be analyzed, processed, and characterized by computational intelligence. Challenges to be addressed and future directions of research are also presented.
A.-E. Hassanien et al.: Computational Intelligence in Multimedia Processing: Foundation and Trends, Studies in Computational Intelligence (SCI) 96, 3–49 (2008) c Springer-Verlag Berlin Heidelberg 2008 www.springerlink.com
4
A.-E. Hassanien et al.
1 Introduction Last few decades have seen a new era of artificial intelligence focusing on the principles, theoretical aspects, and design methodology of algorithms gleaned from nature. Examples are artificial neural networks inspired by mammalian neural systems, evolutionary computation inspired by natural selection in biology, simulated annealing inspired by thermodynamics principles and swarm intelligence inspired by collective behavior of insects or micro-organisms, etc., interacting locally with their environment causing coherent functional global patterns to emerge. Computational intelligence is a well-established paradigm, where new theories with a sound biological understanding have been evolving. The current experimental systems have many of the characteristics of biological computers (brains in other words) and are beginning to be built to perform a variety of tasks that are difficult or impossible to do with conventional computers. Defining computational intelligence is not an easy task [95]. In a nutshell, which becomes quite apparent in light of the current research pursuits, the area is hete
Data Loading...
