Intelligent Retrieval From An Image Database

Intelligent Image Databases: Towards Advanced Image Retrieval addresses the image feature selection issue in developing content-based image retrieval systems. The book first discusses the four important issues in developing a complete content-based image retrieval system, and then demonstrates that image feature selection has significant impact on the remaining issues of system design. Next, it presents an in-depth literature survey on typical image features explored by contemporary content-based image retrieval systems for image matching and retrieval purposes. The goal of the survey is to determine the characteristics and the effectiveness of individual features, so as to establish guidelines for future development of content-based image retrieval systems. Intelligent Image Databases: Towards Advanced Image Retrieval describes the Advanced Region-Based Image Retrieval System (ARBIRS) developed by the authors for color images of real-world scenes. They have selected image regions for building ARBIRS as the literature survey suggests that prominent image regions, along with their associated features, provide a higher probability for achieving a higher level content-based image retrieval system. A major challenge in building a region-based image retrieval system is that prominent regions are rather difficult to capture in an accurate and error-free condition, particularly those in images of real-world scenes. To meet this challenge, the book proposes an integrated approach to tackle the problem via feature capturing, feature indexing, and database query. Through comprehensive system evaluation, it is demonstrated how these systematically integrated efforts work effectively to accomplish advanced image retrieval. Intelligent Image Databases: Towards Advanced Image Retrieval serves as an excellent reference and may be used as a text for advanced courses on the topic.

Discusses major aspects of content-based image retrieval (CBIR) using current technologies and applications within the artificial intelligence (AI) field.

Business intelligence has always been considered an essential ingredient for success. However, it is not until recently that the technology has enabled organizations to generate and deploy intelligence for global competition. These technologies can be leveraged to create the intelligent enterprises of the 21st century that will not only provide excellent and customized services to their customers, but will also create business efficiency for building relationships with suppliers and other business partners on a long term basis. Creating such intelligent enterprises requires the understanding and integration of diverse enterprise components into cohesive intelligent systems. Anticipating that future enterprises need to become intelligent, Intelligent Enterprises of the 21st Century brings together the experiences and knowledge from many parts of the world to provide a compendium of high quality theoretical and applied concepts, methodologies, and techniques that help diffuse knowledge and skills required to create and manage intelligent enterprises of the 21st century for gaining sustainable competitive advantage in a global environment. This book is a comprehensive compilation of the state of the art vision and thought processes needed to design and manage globally competitive business organizations.

This book covers the principles and recent research results in intelligent image database systems design. Special emphasis is placed on spatial reasoning and the techniques for image indexing and retrieval, mainly based on the Theory of Symbolic Projection. In addition, applications of the theory and techniques to intelligent image database systems design are also discussed. Contents: Spatial Reasoning, Image Indexing and Retrieval Using Symbolic Projections (S K Chang et al.)Iconic Indexing by 2D Strings (S K Chang et al.)A Normalized Index for Image Databases (G Petraglia et al.)Representation of 3D Symbolic and Binary Pictures Using 3D Strings (S K Chang & Y Li)Spatial Knowledge Representation for Iconic Image Database (S-Y Lee & F-J Hsu)Ordering Information and Symbolic Projection (C Schlieder)Determination of the Views of a Moving Agent by Means of Symbolic Projections (E Jungert)A Logical Framework for Spatio Temporal Indexing of Image Sequences (A Del Bimbo & E Vicario)A Generalized Approach to Image Indexing and Retrieval Based on 2D Strings (E G M Petrakis & S C Orphanoudakis)Using 2D-String Decision Trees for Symbolic Picture Retrieval (D J Buehrer et al.)Efficient Image Retrieval Algorithms for Large Spatial Databases (J C R Tseng et al.)A Prototype Multimedia Database System Incorporating Iconic Indexing (T Arndt & R Kuppanna)A Two and Three Dimensional Ship Database Application (J Hildebrandt & K Tang) Readership: Researchers and practitioners in computer science. keywords:

As consumer costs for multimedia devices such as digital cameras and Web phones have decreased and diversity in the market has skyrocketed, the amount of digital information has grown considerably. Intelligent Multimedia Databases and Information Retrieval: Advancing Applications and Technologies details the latest information retrieval technologies and applications, the research surrounding the field, and the methodologies and design related to multimedia databases. Together with academic researchers and developers from both information retrieval and artificial intelligence fields, this book details issues and semantics of data retrieval with contributions from around the globe. As the information and data from multimedia databases continues to expand, the research and documentation surrounding it should keep pace as best as possible, and this book provides an excellent resource for the latest developments.

"This book covers industrial databases and applications and offers generic database modeling techniques"--Provided by publisher.