Artificial Intelligence for Maximizing Content Based Image Retrieval

Artificial Intelligence for Maximizing Content Based Image Retrieval

Indexed In: SCOPUS
Release Date: January, 2009|Copyright: © 2009 |Pages: 450
DOI: 10.4018/978-1-60566-174-2
ISBN13: 9781605661742|ISBN10: 1605661740|EISBN13: 9781605661759
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Description & Coverage
Description:

The increasing trend of multimedia data use is likely to accelerate creating an urgent need of providing a clear means of capturing, storing, indexing, retrieving, analyzing, and summarizing data through image data.

Artificial Intelligence for Maximizing Content Based Image Retrieval discusses major aspects of content-based image retrieval (CBIR) using current technologies and applications within the artificial intelligence (AI) field. Providing state-of-the-art research from leading international experts, this book offers a theoretical perspective and practical solutions for academicians, researchers, and industry practitioners.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Active-nets
  • Clustering
  • Content-based image classification and retrieval
  • Content-Based Image Retrieval
  • Content-based medical image retrieval
  • Image feature extraction and representation
  • Image Retrieval
  • Machine learning-based model
  • Object detection/recognition
  • Personalized content-based image retrieval
  • Preference extraction in image retrieval
  • Rough sets framework
  • Texture feature extraction
  • Time series and learned constraints
Reviews & Statements

The objective of the book is to provide the state of the art information to academics, researchers and industry practitioners who are involved or interested in the study, use, design and development of advanced and emerging AI technologies for CBIR with ultimate aim to empower individuals and organizations in building competencies for exploiting the opportunities of the knowledge society.

– Zongmin Ma, Northeastern University, China

This reference for academics, researchers, and industry practitioners discusses major theoretical aspects and practical solutions related to content-based image retrieval using current technologies and applications within the field of artificial intelligence.

– Book News Inc. (March 2009)

This book offers a theoretical perspective and practical solutions for academics, researchers and industry practitioners. This publication is intended for academic and research libraries, as well as those involved in the study and design of intelligent agents. Researchers, practitioners, mangers, educators and students seeking state-of-the-art research and practice on the application of artificial intelligence will also benefit.

– Marthie de Kock, University of South Africa, Online Information Review
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Editor/Author Biographies
Zongmin Ma (Z. M. Ma) received the Ph. D. degree from the City University of Hong Kong in 2001 and is currently a Full Professor in College of Information Science and Engineering at Northeastern University, China. His current research interests include intelligent database systems, knowledge representation and reasoning, the Semantic Web and XML, knowledge-bases systems, and semantic image retrieval. He has published over 80 papers in international journals, conferences, and books in these areas since 1999. He also authored and edited several scholarly books published by Springer-Verlag and IGI Global, respectively. He has served as member of the international program committees for several international conferences and also spent some time as a reviewer of several journals. Dr. Ma is a senior member of the IEEE.
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