Image retrieval using wavelet-based salient points

Qi Tian; Nicu Sebe; Michael S. Lew; E. Loupias; Thomas S. Huang

doi:10.1117/1.1406945

1 October 2001 Image retrieval using wavelet-based salient points

Qi Tian, Nicu Sebe, Michael S. Lew, E. Loupias, Thomas S. Huang

Journal of Electronic Imaging, Vol. 10, Issue 4, (October 2001). https://doi.org/10.1117/1.1406945

Content-based image retrieval (CBIR) has become one of the most active research areas in the past few years. Most of the attention from the research has been focused on indexing techniques based on global feature distributions. However, these global distributions have limited discriminating power because they are unable to capture local image information. The use of interest points in content-based image retrieval allow image index to represent local properties of the image. Classic corner detectors can be used for this purpose. However, they have drawbacks when applied to various natural images for image retrieval, because visual features need not be corners and corners may gather in small regions. In this paper, we present a salient point detector. The detector is based on wavelet transform to detect global variations as well as local ones. The wavelet-based salient points are evaluated for image retrieval with a retrieval system using color and texture features. The results show that salient points with Gabor feature perform better than the other point detectors from the literature and the randomly chosen points. Significant improvements are achieved in terms of retrieval accuracy, computational complexity when compared to the global feature approaches.

©(2001) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Qi Tian, Nicu Sebe, Michael S. Lew, E. Loupias, and Thomas S. Huang "Image retrieval using wavelet-based salient points," Journal of Electronic Imaging 10(4), (1 October 2001). https://doi.org/10.1117/1.1406945

Published: 1 October 2001

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