By Topic

Image Hashing Algorithm via Iterative Scale Interaction Geometric Model

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Yuanyuan Hu ; Shenzhen Grad. Sch., Inf. Security Tech. Res. Center, Harbin Inst. of Technol., Shenzhen, China ; Xiamu Niu ; Hui Zhang

Directional content-preserving features are extracted instead of the global ones. It first detects the initial curvature feature points based on the scale interaction model using Gabor filters with various scales in different directions. Then, the iterative geometric method is proposed to exact the content-preserving feature points. Next, by the radon transform, the two-dimensional distributing is mapped to one-dimensional feature vector. Finally, the one-dimensional feature vectors are quantized to get the hashing. It is verified that the proposed algorithm has a better robustness of standard benchmark (e.g. Stirmark) attacks including JPEG compression (QF=5), geometric distortions of cropping (more than 30%), rotation (more than 10 degree), and common signal processing operations. Moreover, malicious content changing manipulations of image data are also detected. The algorithm has a wide application in identification/search of images in large databases and content-based image authentication, etc.

Published in:

Image and Signal Processing, 2009. CISP '09. 2nd International Congress on

Date of Conference:

17-19 Oct. 2009