An image retrieval algorithm using independent edge self-reinforcement and integrated salient edge matching

JunWei Han; Lei Guo

doi:10.1117/12.476248

10 January 2003 An image retrieval algorithm using independent edge self-reinforcement and integrated salient edge matching

JunWei Han, Lei Guo

Author Affiliations +

Proceedings Volume 5021, Storage and Retrieval for Media Databases 2003; (2003) https://doi.org/10.1117/12.476248
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

Digital image retrieval systems allow sophisticated querying and searching by image contents. Since 1990’s, Content-Based Image Retrieval (CBIR) has attracted great research attention. In this paper, we propose a new approach for shape-based image retrieval. We perform an independent edge self-reinforcement algorithm on the edge map to yield the salient edges. The content of a salient edge is characterized by its low-level features, including length, rotation angle histogram and corner frequency. Then, the image similarity measure are based on the EMD (Earth Mover’s Distance), named as integrated salient edge matching in this article. Preliminary experimental results on a database containing 7000 images demonstrate that the proposed method is promising.

Citation Download Citation

JunWei Han and Lei Guo "An image retrieval algorithm using independent edge self-reinforcement and integrated salient edge matching", Proc. SPIE 5021, Storage and Retrieval for Media Databases 2003, (10 January 2003); https://doi.org/10.1117/12.476248

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