Fast indexing and searching strategies for feature-based image database systems

Li-Wei Kang; Jin-Jang Leou

doi:10.1117/1.1866148

1 January 2005 Fast indexing and searching strategies for feature-based image database systems

Li-Wei Kang, Jin-Jang Leou

Author Affiliations +

Journal of Electronic Imaging, Vol. 14, Issue 1, 013019 (January 2005). https://doi.org/10.1117/1.1866148

Abstract

Because visual data require a large amount of memory and computing power for storage and processing, it is greatly desired to efficiently index and retrieve the visual information from image database systems. We propose efficient indexing and searching strategies for feature-based image database systems, in which uncompressed and compressed domain image features are employed. Each query or stored image is represented by a set of features extracted from the image. The weighted square sum error distance is employed to evaluate the ranks of retrieved images. Many fast clustering and searching techniques exist for the square sum error distance used in vector quantization (VQ), in which different features have identical weighting coefficients. In practice, different features may have different dynamic ranges and different importances, i.e., different features may have different weighting coefficients. We derive a set of inequalities based on the weighted square sum error distance and employ it to speed up the indexing (clustering) and searching procedures for feature-based image database systems. Good simulation results show the feasibility of the proposed approaches.

©(2005) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Li-Wei Kang and Jin-Jang Leou "Fast indexing and searching strategies for feature-based image database systems," Journal of Electronic Imaging 14(1), 013019 (1 January 2005). https://doi.org/10.1117/1.1866148

Published: 1 January 2005

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