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

Large amounts of digital images are created and accessed daily by the public, academia, and corporations. Keyword indexing is useful but limited in describing image content. Intelligent content-based retrieval is a key technology to address this problem and to facilitate efficient image-based knowledge. This dissertation presents an attempt to improve image segmentation and region-based image retrieval utilizing artificial intelligence methods of probabilistic perspective to achieve this goal. Two novel systems are proposed: fuzzy-logic expert system for objects labeling OLFES and cluster-based retrieval system CoIRS. The two systems are based on probabilistic learning framework called EMIS and are integrated for image segmentation and retrieval. The EMIS is based on Expectation-Maximization (EM) algorithm that estimates Bayesian Maximum Likelihood parameters to fit data into Gaussian Mixture Model. The color and texture features of the image's small patches are fed to EM.

Recent improvements in business process strategies have allowed more opportunities to attain greater developmental performances. This has led to higher success in day-to-day production and overall competitive advantage. The Handbook of Research on Manufacturing Process Modeling and Optimization Strategies is a pivotal reference source for the latest research on the various manufacturing methodologies and highlights the best optimization approaches to achieve boosted process performance. Featuring extensive coverage on relevant areas such as genetic algorithms, fuzzy set theory, and soft computing techniques, this publication is an ideal resource for researchers, practitioners, academicians, designers, manufacturing engineers, and institutions involved in design and manufacturing projects.

"This book disseminates current information on multimedia retrieval, advancing the field of multimedia databases, and educating the multimedia database community on machine learning techniques for adaptive multimedia retrieval research, design and applications"--Provided by publisher.

What Is Image Retrieval A computer system that is used for browsing, searching, and retrieving images from a vast collection of digital images is called an image retrieval system (sometimes abbreviated as IRMS). In order for image retrieval to be carried out over the annotation words, the majority of the conventional and widespread methods currently in use include the addition of information to the images themselves. This metadata can take the form of captioning, keywords, titles, or descriptions. Annotating images manually is a significant investment of time, effort, and money; as a result, a significant amount of effort and research has been put into developing automatic image annotation methods. In addition, the proliferation of social web apps as well as the semantic web has been a driving force behind the development of a number of picture annotation tools that are web-based. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Image retrieval Chapter 2: Information retrieval Chapter 3: MPEG-7 Chapter 4: Content-based image retrieval Chapter 5: Automatic image annotation Chapter 6: Image organizer Chapter 7: Google Images Chapter 8: Image meta search Chapter 9: Metadata Chapter 10: Reverse image search (II) Answering the public top questions about image retrieval. (III) Real world examples for the usage of image retrieval in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of image retrieval' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of image retrieval.

"This book offers the latest research on retrieval and storage methods for digital library systems, a burgeoning field of data sourcing"--Provided by publisher.

Aleksander Zgrzywa, Kazimierz Choroś, and Andrzej Siemiński (Eds.) Multimedia and Internet Systems: Theory and Practice During the last 20 years we have witnessed a rapid development of Multimedia and Network Information Systems. What is even more important, the pace of change does not show any sign of slowing. When we look back we see how many research projects that have originated at various universities or in research facilities are now part of our everyday life. This monograph offers the reader a very broad review of the most recent scientific investigations in that area. The book is a collection of carefully selected and the most representative investigations, solutions, and applications presented by scientific teams from several countries. The content of the monograph has been divided into four parts: 1. Multimedia Information Technology 2. Information Systems Specification 3. Information Systems Applications 4. Web Systems and Network Technologies The book is aiming to attract more scholars to work on the area of multimedia and Internet applications and to inspire the research community already working on the domain.

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.

Ongoing advancements in modern technology have led to significant developments in artificial intelligence. With the numerous applications available, it becomes imperative to conduct research and make further progress in this field. Artificial Intelligence: Concepts, Methodologies, Tools, and Applications provides a comprehensive overview of the latest breakthroughs and recent progress in artificial intelligence. Highlighting relevant technologies, uses, and techniques across various industries and settings, this publication is a pivotal reference source for researchers, professionals, academics, upper-level students, and practitioners interested in emerging perspectives in the field of artificial intelligence.

Multimedia represents information in novel and varied formats. One of the most prevalent examples of continuous media is video. Extracting underlying data from these videos can be an arduous task. From video indexing, surveillance, and mining, complex computational applications are required to process this data. Intelligent Analysis of Multimedia Information is a pivotal reference source for the latest scholarly research on the implementation of innovative techniques to a broad spectrum of multimedia applications by presenting emerging methods in continuous media processing and manipulation. This book offers a fresh perspective for students and researchers of information technology, media professionals, and programmers.