LMS: a Long-term knowledge-based Multimedia retrieval System for region-based image databases Online publication date: Sun, 06-Jul-2008
by Xin Chen, Chengcui Zhang, Shu-Ching Chen, Min Chen
International Journal of Applied Systemic Studies (IJASS), Vol. 1, No. 4, 2007
Abstract: The Content-Based Image Retrieval (CBIR) system is a special kind of knowledge-based multimedia retrieval system. Relevance Feedback (RF) is a widely used technique in CBIR for incorporating the user's knowledge with the learning process, which has been shown to significantly increase the retrieval accuracy. However, the user preferences obtained through RF are often discarded at the end of search, thus requiring the feedback process to restart for each new query. This paper proposes a Long-term knowledge-based Multimedia retrieval System (LMS) based on Latent Semantic Indexing (LSI) and human interaction (RF). Experiments show the effectiveness of the proposed system.
Online publication date: Sun, 06-Jul-2008
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Applied Systemic Studies (IJASS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org