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

A Stochastic and Content-Based Image Retrieval Mechanism

A Stochastic and Content-Based Image Retrieval Mechanism
View Sample PDF
Author(s): Mei-Ling Shyu (University of Miami, USA), Shu-Ching Chen (Florida International University, USA) and Chengcui Zhang (Florida International University, USA)
Copyright: 2008
Pages: 16
Source title: Multimedia Technologies: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Mahbubur Rahman Syed (Minnesota State University Mankato, USA)
DOI: 10.4018/978-1-59904-953-3.ch111

Purchase

View A Stochastic and Content-Based Image Retrieval Mechanism on the publisher's website for pricing and purchasing information.

Abstract

Multimedia information, typically image information, is growing rapidly across the Internet and elsewhere. To keep pace with the increasing volumes of image information, new techniques need to be investigated to retrieve images intelligently and efficiently. Content-based image retrieval (CBIR) is always a challenging task. In this chapter, a stochastic mechanism, called Markov Model Mediator (MMM), is used to facilitate the searching and retrieval process for content-based image retrieval, which serves as the retrieval engine of the CBIR systems and uses stochastic-based similarity measures. Different from the common methods, our stochastic mechanism carries out the searching and similarity computing process dynamically, taking into consideration not only the image content features but also other characteristics of images such as their access frequencies and access patterns. Our experimental results demonstrate that the MMM mechanism together with the stochastic process can assist in retrieving more accurate results for user queries.

Related Content

Kuki Singh. © 2022. 36 pages.
Hanshu Wang, Chenyang Zhang. © 2022. 23 pages.
Nkholedzeni Sidney Netshakhuma. © 2022. 21 pages.
Ileana Torres, Aubrey Statti, Kelly M. Torres. © 2022. 33 pages.
Margarida M. Pinheiro, Vanda Santos. © 2022. 28 pages.
María-Mercedes Rojas-de-Gracia, Ana Esteban, María J. Bentabol, María Dolores Rodríguez-Ruiz, Amparo Bentabol, Ana Paula Lopes, Filomena Soares, María M. Muñoz, Mariano Soler-Porta, Rocío Caña-Palma. © 2022. 23 pages.
Sergio Francisco Sargo Ferreira Lopes, Jorge Manuel de Azevedo Pereira Simões. © 2022. 23 pages.
Body Bottom