Information embedding based on user's relevance feedback for image retrieval

Catherine S. Lee; Wei-Ying Ma; HongJiang Zhang

doi:10.1117/12.360434

24 August 1999 Information embedding based on user's relevance feedback for image retrieval

Catherine S. Lee, Wei-Ying Ma, HongJiang Zhang

Proceedings Volume 3846, Multimedia Storage and Archiving Systems IV; (1999) https://doi.org/10.1117/12.360434
Event: Photonics East '99, 1999, Boston, MA, United States

Abstract

An image retrieval system based on an information embedding scheme is proposed. Using relevance feedback, the system gradually embeds correlations between images from a high- level semantic perspective. The system starts with low-level image features and acquires knowledge from users to correlate different images in the database. Through the selection of positive and negative examples based on a given query, the semantic relationships between images are captured and embedded into the system by splitting/merging image clusters and updating the correlation matrix. Image retrieval is then based on the resulting image clusters and the correlation matrix obtained through relevance feedback.

Citation Download Citation

Catherine S. Lee, Wei-Ying Ma, and HongJiang Zhang "Information embedding based on user's relevance feedback for image retrieval", Proc. SPIE 3846, Multimedia Storage and Archiving Systems IV, (24 August 1999); https://doi.org/10.1117/12.360434

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available