Image retrieval algorithm using modified AAPSEG and weighted regions matching

Qingtao Meng; Shengrong Gong; Zhaohui Wang

doi:10.1117/12.832931

30 October 2009 Image retrieval algorithm using modified AAPSEG and weighted regions matching

Qingtao Meng, Shengrong Gong, Zhaohui Wang

Author Affiliations +

Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 74953A (2009) https://doi.org/10.1117/12.832931
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Image segmentation and region matching is the mainly issues of Region-Based Image Retrieval. In this paper we proposed adaptive image segmentation based on affinity propagation clustering (AAPSEG) and weighted region matching (WRM), APPSEG method calculated preference in Affinity Propagation clustering (AP) adaptively, and applied Adaptive Affinity Propagation clustering to nature image segmentation. WRM computed the weight between regions by location, size etc. It increased the influence of main region and decreased the secondary region. The Modified Hausdorff distance which was used to calculate similarity between quire image and candidate images effectively solved the problem of region matching in RBIR. The results of experiments demonstrated that the new method obviously improved precision in RBIR.

Citation Download Citation

Qingtao Meng, Shengrong Gong, and Zhaohui Wang "Image retrieval algorithm using modified AAPSEG and weighted regions matching", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74953A (30 October 2009); https://doi.org/10.1117/12.832931

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