IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Content-Based Retrieval Concept

Content-Based Retrieval Concept
View Sample PDF
Author(s): Yung-Kuan Chan (National Chung Hsing University, Taiwan, R.O.C.)and Chin-Chen Chang (National Chung Cheng University, Taiwan, R.O.C.)
Copyright: 2009
Pages: 5
Source title: Encyclopedia of Information Science and Technology, Second Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-60566-026-4.ch122

Purchase

View Content-Based Retrieval Concept on the publisher's website for pricing and purchasing information.

Abstract

Because of the demand for efficient management in images, much attention has been paid to image retrieval over the past few years. The text-based image retrieval system is commonly used in traditional search engines (Ratha et al., 1996), where a query is represented by keywords that are usually identified and classified by human beings. Since people have different understandings on a particular image, the consistency is difficult to maintain. When the database is larger, it is arduous to describe and classify the images because most images are complicated and have many different objects. There has been a trend towards developing the content-based retrieval system, which tries to retrieve images directly and automatically based on their visual contents. A similar image retrieval system extracts the content of the query example q and compares it with that of each database image during querying. The answer to this query may be one or more images that are the most similar ones to q. Similarity retrieval can work effectively when the user fails to express queries in a precise way. In this case, it is no longer necessary to retrieve an image extremely similar to the query example. Hence, similarity retrieval has more practical applications than an exact match does.

Related Content

Christine Kosmopoulos. © 2022. 22 pages.
Melkamu Beyene, Solomon Mekonnen Tekle, Daniel Gelaw Alemneh. © 2022. 21 pages.
Rajkumari Sofia Devi, Ch. Ibohal Singh. © 2022. 21 pages.
Ida Fajar Priyanto. © 2022. 16 pages.
Murtala Ismail Adakawa. © 2022. 27 pages.
Shimelis Getu Assefa. © 2022. 17 pages.
Angela Y. Ford, Daniel Gelaw Alemneh. © 2022. 22 pages.
Body Bottom