Exploratory Image Databases: Content-Based Retrieval [Kõva köide]

Calling it a very small and technical fragment of the current evolution of information technology, Santini (U. of California-La Jolla) explores computer systems for accessing and retrieving images from large databases, with a particular interest in retrieving based on the content of the images. He argues that content-based image retrieval can unveil and clarify some crucial aspects of the current and future modalities of human communication, and is independent of image analysis and computer vision. Annotation c. Book News, Inc., Portland, OR (booknews.com)

The explosion of computer use and internet communication has placed new emphasis on the ability to store, retrieve and search for all types of images, both still photo and video images. The success and the future of visual information retrieval depends on the cutting edge research and applications explored in this book. It combines the expertise from both computer vision and database research.

Unlike text retrieval and text/numeric databases the challenges of image databases are enormous. How do you use "data mining" to search for an image if you do not have "key words" to search? Exploratory Image Databases introduces the idea that it is possible to solve this problem by merging database systems into a single search and browse activity called "exploration."

Exploratory Image Databases is one of the first single-author books that unifies the critical emerging topic of image databases. A new approach to image databases, the work is divided into four central parts: introduction to the problems that image database research must solve; computer vision and information retrieval techniques; image database issues; and interface and engines for visual searches.

Example: Imagine the difficulty of building and using a database for "face recognition," where an image of a face is used. In order to effectively use the image a huge number of characteristics would need to be entered in the database. The goal of future image databases is to use hardware and software to recognize and categorize images without typing in characteristics.

* Comprehensive coverage of the image analysis as well as the database/theoretical aspects of image databases.
* Extensive coverage of interfaces and interaction models, with a theoretical framework for the development of new interaction schemes.
* Identifies three interaction models between users and image databases, two of which have no counterpart in traditional databases.
* Coverage of the relation between image and text, including mixed search models and the automatic determination of the relation between images and text on large corpuses like the web.
* Analysis of the process of signification in images and its influence on the interaction models and technological problems of image databases.

The explosion of computer use and internet communication has placed new emphasis on the ability to store, retrieve and search for all types of images, both still photo and video images. The success and the future of visual information retrieval depends on the cutting edge research and applications explored in this book. It combines the expertise from both computer vision and database research.

Unlike text retrieval and text/numeric databases the challenges of image databases are enormous. How do you use "data mining" to search for an image if you do not have "key words" to search? Exploratory Image Databases introduces the idea that it is possible to solve this problem by merging database systems into a single search and browse activity called "exploration."

Exploratory Image Databases is one of the first single-author books that unifies the critical emerging topic of image databases. A new approach to image databases, the work is divided into four central parts: introduction to the problems that image database research must solve; computer vision and information retrieval techniques; image database issues; and interface and engines for visual searches.

Example: Imagine the difficulty of building and using a database for "face recognition," where an image of a face is used. In order to effectively use the image a huge number of characteristics would need to be entered in the database. The goal of future image databases is to use hardware and software to recognize and categorize images without typing in characteristics.

* Comprehensive coverage of the image analysis as well as the database/theoretical aspects of image databases.
* Extensive coverage of interfaces and interaction models, with a theoretical framework for the development of new interaction schemes.
* Identifies three interaction models between users and image databases, two of which have no counterpart in traditional databases.
* Coverage of the relation between image and text, including mixed search models and the automatic determination of the relation between images and text on large corpuses like the web.
* Analysis of the process of signification in images and its influence on the interaction models and technological problems of image databases.