Mapping low-level image features to semantic concepts

1 January 2001 Mapping low-level image features to semantic concepts

Daniela Stan, Ishwar K. Sethi

Proceedings Volume 4315, Storage and Retrieval for Media Databases 2001; (2001) https://doi.org/10.1117/12.410925
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

Abstract

Humans tend to use high-level semantic concepts when querying and browsing multimedia databases; there is thus, a need for systems that extract these concepts and make available annotations for the multimedia data. The system presented in this paper satisfies this need by automatically generating semantic concepts for images form their low-level visual features. The proposed system is built in two stages. First, an adaptation of k-means clustering using a non- Euclidean similarity metric is applied to discover the natural patterns of the data in the low-level feature space; the cluster prototype is designed to summarize the cluster in a manner that is suited for quick human comprehension of its components. Second, statistics measuring the variation within each cluster are used to derive a set of mappings between the most significant low-level features and the most frequent keywords of the corresponding cluster. The set of the derived rules could be used further to capture the semantic content and index new untagged images added to the image database. The attachment of semantic concepts to images will also give the system the advantage of handling queries expressed in terms of keywords and thus, it reduces the semantic gap between the user's conceptualization of a query and the query that is actually specified to the system. While the suggested scheme works with any kind of low-level features, our implementation and description of the system is centered on the use of image color information. Experiments using a 21 00 image database are presented to show the efficacy of the proposed system.

Citation Download Citation

Daniela Stan and Ishwar K. Sethi "Mapping low-level image features to semantic concepts", Proc. SPIE 4315, Storage and Retrieval for Media Databases 2001, (1 January 2001); https://doi.org/10.1117/12.410925

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